diff --git a/docs/build/html/.buildinfo b/docs/build/html/.buildinfo index 241cac39c..d0b5e9e22 100644 --- a/docs/build/html/.buildinfo +++ b/docs/build/html/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 136f45bc6db8a54d889bf646df22a392 +config: 106d4f405b471b3dd6a82c4cc5ee12b0 tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/docs/build/html/_sources/dev/extensions.rst b/docs/build/html/_sources/dev/extensions.rst index c08614d03..4272371cb 100644 --- a/docs/build/html/_sources/dev/extensions.rst +++ b/docs/build/html/_sources/dev/extensions.rst @@ -22,12 +22,12 @@ You can do that in MLX directly: This function performs that operation while leaving the implementation and function transformations to MLX. -However you may need to customize the underlying implementation, perhaps to -make it faster or for custom differentiation. In this tutorial we will go -through adding custom extensions. It will cover: +However, you may want to customize the underlying implementation, perhaps to +make it faster. In this tutorial we will go through adding custom extensions. +It will cover: * The structure of the MLX library. -* Implementing a CPU operation that redirects to Accelerate_ when appropriate. +* Implementing a CPU operation. * Implementing a GPU operation using metal. * Adding the ``vjp`` and ``jvp`` function transformation. * Building a custom extension and binding it to python. @@ -45,7 +45,7 @@ Operations Operations are the front-end functions that operate on arrays. They are defined in the C++ API (:ref:`cpp_ops`), and the Python API (:ref:`ops`) binds them. -We would like an operation, :meth:`axpby` that takes in two arrays ``x`` and +We would like an operation :meth:`axpby` that takes in two arrays, ``x`` and ``y``, and two scalars, ``alpha`` and ``beta``. This is how to define it in C++: @@ -55,7 +55,7 @@ C++: * Scale and sum two vectors element-wise * z = alpha * x + beta * y * - * Follow numpy style broadcasting between x and y + * Use NumPy-style broadcasting between x and y * Inputs are upcasted to floats if needed **/ array axpby( @@ -66,7 +66,7 @@ C++: StreamOrDevice s = {} // Stream on which to schedule the operation ); -The simplest way to this operation is in terms of existing operations: +The simplest way to implement this is with existing operations: .. code-block:: C++ @@ -153,9 +153,6 @@ more concrete: private: float alpha_; float beta_; - - /** Fall back implementation for evaluation on CPU */ - void eval(const std::vector& inputs, array& out); }; The :class:`Axpby` class derives from the base :class:`Primitive` class. The @@ -188,7 +185,7 @@ Let's reimplement our operation now in terms of our :class:`Axpby` primitive. auto promoted_dtype = promote_types(x.dtype(), y.dtype()); // Upcast to float32 for non-floating point inputs x and y - auto out_dtype = is_floating_point(promoted_dtype) + auto out_dtype = issubdtype(promoted_dtype, float32) ? promoted_dtype : promote_types(promoted_dtype, float32); @@ -234,49 +231,59 @@ the execution of the computation graph, and calls :meth:`Axpby::eval_cpu` or Implementing the CPU Back-end ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -Let's start by implementing a naive and generic version of -:meth:`Axpby::eval_cpu`. We declared this as a private member function of -:class:`Axpby` earlier called :meth:`Axpby::eval`. +Let's start by implementing :meth:`Axpby::eval_cpu`. -Our naive method will go over each element of the output array, find the +The method will go over each element of the output array, find the corresponding input elements of ``x`` and ``y`` and perform the operation point-wise. This is captured in the templated function :meth:`axpby_impl`. .. code-block:: C++ - template - void axpby_impl( - const array& x, - const array& y, - array& out, - float alpha_, - float beta_) { - // We only allocate memory when we are ready to fill the output - // malloc_or_wait synchronously allocates available memory - // There may be a wait executed here if the allocation is requested - // under memory-pressured conditions - out.set_data(allocator::malloc_or_wait(out.nbytes())); + template + void axpby_impl( + const mx::array& x, + const mx::array& y, + mx::array& out, + float alpha_, + float beta_, + mx::Stream stream) { + // Allocate the output with `malloc_or_wait` which synchronously allocates + // memory, potentially waiting if the system is under memory pressure + out.set_data(mx::allocator::malloc_or_wait(out.nbytes())); - // Collect input and output data pointers - const T* x_ptr = x.data(); - const T* y_ptr = y.data(); - T* out_ptr = out.data(); + // Get the CPU command encoder and register input and output arrays + auto& encoder = mx::cpu::get_command_encoder(stream); + encoder.set_input_array(x); + encoder.set_input_array(y); + encoder.set_output_array(out); - // Cast alpha and beta to the relevant types - T alpha = static_cast(alpha_); - T beta = static_cast(beta_); + // Launch the CPU kernel + encoder.dispatch([x_ptr = x.data(), + y_ptr = y.data(), + out_ptr = out.data(), + size = out.size(), + shape = out.shape(), + x_strides = x.strides(), + y_strides = y.strides(), + alpha_, + beta_]() { - // Do the element-wise operation for each output - for (size_t out_idx = 0; out_idx < out.size(); out_idx++) { - // Map linear indices to offsets in x and y - auto x_offset = elem_to_loc(out_idx, x.shape(), x.strides()); - auto y_offset = elem_to_loc(out_idx, y.shape(), y.strides()); + // Cast alpha and beta to the relevant types + T alpha = static_cast(alpha_); + T beta = static_cast(beta_); - // We allocate the output to be contiguous and regularly strided - // (defaults to row major) and hence it doesn't need additional mapping - out_ptr[out_idx] = alpha * x_ptr[x_offset] + beta * y_ptr[y_offset]; - } - } + // Do the element-wise operation for each output + for (size_t out_idx = 0; out_idx < size; out_idx++) { + // Map linear indices to offsets in x and y + auto x_offset = mx::elem_to_loc(out_idx, shape, x_strides); + auto y_offset = mx::elem_to_loc(out_idx, shape, y_strides); + + // We allocate the output to be contiguous and regularly strided + // (defaults to row major) and hence it doesn't need additional mapping + out_ptr[out_idx] = alpha * x_ptr[x_offset] + beta * y_ptr[y_offset]; + } + }); + } Our implementation should work for all incoming floating point arrays. Accordingly, we add dispatches for ``float32``, ``float16``, ``bfloat16`` and @@ -284,112 +291,32 @@ Accordingly, we add dispatches for ``float32``, ``float16``, ``bfloat16`` and .. code-block:: C++ - /** Fall back implementation for evaluation on CPU */ - void Axpby::eval( - const std::vector& inputs, - const std::vector& outputs) { - auto& x = inputs[0]; - auto& y = inputs[1]; - auto& out = outputs[0]; - - // Dispatch to the correct dtype - if (out.dtype() == float32) { - return axpby_impl(x, y, out, alpha_, beta_); - } else if (out.dtype() == float16) { - return axpby_impl(x, y, out, alpha_, beta_); - } else if (out.dtype() == bfloat16) { - return axpby_impl(x, y, out, alpha_, beta_); - } else if (out.dtype() == complex64) { - return axpby_impl(x, y, out, alpha_, beta_); - } else { - throw std::runtime_error( - "[Axpby] Only supports floating point types."); - } - } - -This is good as a fallback implementation. We can use the ``axpby`` routine -provided by the Accelerate_ framework for a faster implementation in certain -cases: - -#. Accelerate does not provide implementations of ``axpby`` for half precision - floats. We can only use it for ``float32`` types. -#. Accelerate assumes the inputs ``x`` and ``y`` are contiguous and all - elements have fixed strides between them. We only direct to Accelerate - if both ``x`` and ``y`` are row contiguous or column contiguous. -#. Accelerate performs the routine ``Y = (alpha * X) + (beta * Y)`` in-place. - MLX expects to write the output to a new array. We must copy the elements - of ``y`` into the output and use that as an input to ``axpby``. - -Let's write an implementation that uses Accelerate in the right conditions. -It allocates data for the output, copies ``y`` into it, and then calls the -:func:`catlas_saxpby` from accelerate. - -.. code-block:: C++ - - template - void axpby_impl_accelerate( - const array& x, - const array& y, - array& out, - float alpha_, - float beta_) { - // Accelerate library provides catlas_saxpby which does - // Y = (alpha * X) + (beta * Y) in place - // To use it, we first copy the data in y over to the output array - out.set_data(allocator::malloc_or_wait(out.nbytes())); - - // We then copy over the elements using the contiguous vector specialization - copy_inplace(y, out, CopyType::Vector); - - // Get x and y pointers for catlas_saxpby - const T* x_ptr = x.data(); - T* y_ptr = out.data(); - - T alpha = static_cast(alpha_); - T beta = static_cast(beta_); - - // Call the inplace accelerate operator - catlas_saxpby( - /* N = */ out.size(), - /* ALPHA = */ alpha, - /* X = */ x_ptr, - /* INCX = */ 1, - /* BETA = */ beta, - /* Y = */ y_ptr, - /* INCY = */ 1); - } - -For inputs that do not fit the criteria for accelerate, we fall back to -:meth:`Axpby::eval`. With this in mind, let's finish our -:meth:`Axpby::eval_cpu`. - -.. code-block:: C++ - - /** Evaluate primitive on CPU using accelerate specializations */ void Axpby::eval_cpu( - const std::vector& inputs, - const std::vector& outputs) { - assert(inputs.size() == 2); - auto& x = inputs[0]; - auto& y = inputs[1]; - auto& out = outputs[0]; + const std::vector& inputs, + std::vector& outputs) { + auto& x = inputs[0]; + auto& y = inputs[1]; + auto& out = outputs[0]; - // Accelerate specialization for contiguous single precision float arrays - if (out.dtype() == float32 && - ((x.flags().row_contiguous && y.flags().row_contiguous) || - (x.flags().col_contiguous && y.flags().col_contiguous))) { - axpby_impl_accelerate(x, y, out, alpha_, beta_); - return; - } - - // Fall back to common back-end if specializations are not available - eval(inputs, outputs); + // Dispatch to the correct dtype + if (out.dtype() == mx::float32) { + return axpby_impl(x, y, out, alpha_, beta_, stream()); + } else if (out.dtype() == mx::float16) { + return axpby_impl(x, y, out, alpha_, beta_, stream()); + } else if (out.dtype() == mx::bfloat16) { + return axpby_impl(x, y, out, alpha_, beta_, stream()); + } else if (out.dtype() == mx::complex64) { + return axpby_impl(x, y, out, alpha_, beta_, stream()); + } else { + throw std::runtime_error( + "Axpby is only supported for floating point types."); + } } Just this much is enough to run the operation :meth:`axpby` on a CPU stream! If you do not plan on running the operation on the GPU or using transforms on computation graphs that contain :class:`Axpby`, you can stop implementing the -primitive here and enjoy the speed-ups you get from the Accelerate library. +primitive here. Implementing the GPU Back-end ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ @@ -824,7 +751,7 @@ Results ^^^^^^^ Let's run a quick benchmark and see how our new ``axpby`` operation compares -with the naive :meth:`simple_axpby` we first defined on the CPU. +with the naive :meth:`simple_axpby` we first defined. .. code-block:: python @@ -832,13 +759,11 @@ with the naive :meth:`simple_axpby` we first defined on the CPU. from mlx_sample_extensions import axpby import time - mx.set_default_device(mx.cpu) - def simple_axpby(x: mx.array, y: mx.array, alpha: float, beta: float) -> mx.array: return alpha * x + beta * y - M = 256 - N = 512 + M = 4096 + N = 4096 x = mx.random.normal((M, N)) y = mx.random.normal((M, N)) @@ -849,24 +774,24 @@ with the naive :meth:`simple_axpby` we first defined on the CPU. def bench(f): # Warm up - for i in range(100): + for i in range(5): z = f(x, y, alpha, beta) mx.eval(z) # Timed run s = time.time() - for i in range(5000): + for i in range(100): z = f(x, y, alpha, beta) mx.eval(z) e = time.time() - return e - s + return 1000 * (e - s) / 100 simple_time = bench(simple_axpby) custom_time = bench(axpby) - print(f"Simple axpby: {simple_time:.3f} s | Custom axpby: {custom_time:.3f} s") + print(f"Simple axpby: {simple_time:.3f} ms | Custom axpby: {custom_time:.3f} ms") -The results are ``Simple axpby: 0.114 s | Custom axpby: 0.109 s``. We see +The results are ``Simple axpby: 1.559 ms | Custom axpby: 0.774 ms``. We see modest improvements right away! This operation is now good to be used to build other operations, in diff --git a/docs/build/html/_static/documentation_options.js b/docs/build/html/_static/documentation_options.js index b42e8215e..bcbb1c4d0 100644 --- a/docs/build/html/_static/documentation_options.js +++ b/docs/build/html/_static/documentation_options.js @@ -1,5 +1,5 @@ const DOCUMENTATION_OPTIONS = { - VERSION: '0.23.2', + VERSION: '0.24.0', LANGUAGE: 'en', COLLAPSE_INDEX: false, BUILDER: 'html', diff --git a/docs/build/html/annotated.html b/docs/build/html/annotated.html index dca09161f..f3dad488c 100644 --- a/docs/build/html/annotated.html +++ b/docs/build/html/annotated.html @@ -123,301 +123,304 @@ $(function(){initNavTree('annotated.html',''); initResizable(true); });  CAllocator  CBuffer  CCommonAllocator - ►Ndetail - CAbs - CAdd - CArcCos - CArcCosh - CArcSin - CArcSinh - CArcTan - CArcTan2 - CArcTanh - CBitwiseAnd - CBitwiseInvert - CBitwiseOr - CBitwiseXor - CCeil - CConjugate - CCos - CCosh - CDivide - CEqual - CErf - CErfInv - CExp - CExpm1 - CFloor - CGreater - CGreaterEqual - CImag - CInTracing - CLeftShift - CLess - CLessEqual - CLog - CLog10 - CLog1p - CLog2 - CLogAddExp - CLogicalAnd - CLogicalNot - CLogicalOr - CMaximum - CMinimum - CMultiply - CNaNEqual - CNegative - CNotEqual - CPower - CReal - CRemainder - CRetainGraph - CRightShift - CRound - CRsqrt - CSelect - CSigmoid - CSign - CSin - CSinh - CSqrt - CSquare - CSubtract - CTan - CTanh - ►Ndistributed - ►Ndetail - CGroupImplAbstract base class of a distributed group implementation - CAllGather - CAllReduce - CDistPrimitive - CGroupA distributed::Group represents a group of independent mlx processes that can communicate - CRecv - CSend - ►Nfast - CAffineQuantize - CCustom - CCustomKernel - CCustomKernelShapeInfo - CLayerNorm - CLayerNormVJP - CRMSNorm - CRMSNormVJP - CRoPE - CScaledDotProductAttention - ►Nio - CFileWriter - CParallelFileReader - CReader - CWriter - ►Nmetal - CBuffer - ►CCommandEncoder - CConcurrentContext - CDevice - CDeviceStream - CFence - CMetalAllocator - CResidencySet - ►Nrandom - CKeySequence - ►Nscheduler - CScheduler - CStreamThread - ►Nsimd - CScalarT - CScalarT< bool, N > - CScalarT< int64_t, N > - CScalarT< int8_t, N > - CScalarT< uint64_t, N > - CSimd - CSimd< float16_t, N > - CSimd< T, 1 > - C_MLX_BFloat16 - C_MLX_Float16 - CAbs - CAdd - CAddMM - CArange - CArcCos - CArcCosh - CArcSin - CArcSinh - CArcTan - CArcTan2 - CArcTanh - CArgPartition - CArgReduce - CArgSort - ►Carray - CArrayIterator - CData - CFlags - CAsStrided - CAsType - CBitwiseBinary - CBitwiseInvert - CBlockMaskedMM - CBroadcast - CBroadcastAxes - CCeil - CCholesky - ►CCommandEncoder - CConcurrentContext - CCompiled - Ccomplex128_t - Ccomplex64_t - CConcatenate - CConjugate - CContiguous - CContiguousIterator - CConvolution - CCopy - CCos - CCosh - CCustomTransforms - CDepends - CDevice - CDivide - CDivMod - CDtype - CDynamicSlice - CDynamicSliceUpdate - CEigh - CEqual - CErf - CErfInv - CEvent - CExp - CExpandDims - CExpm1 - CFence - CFFT - CfinfoHolds information about floating-point types - CFlatten - CFloor - CFull - CFunctionExporter - CGather - CGatherAxis - CGatherMM - CGatherQMM - CGreater - CGreaterEqual - CHadamard - CImag - CImportedFunction - CInverse - CJitCompiler - CLess - CLessEqual - CLoad - CLog - CLog1p - CLogAddExp - CLogicalAnd - CLogicalNot - CLogicalOr - CLUF - CMatmul - CMaximum - CMinimum - CMultiply - CNegative - CNodeNamer - CNotEqual - CNumberOfElements - Cnumeric_limits - Cnumeric_limits< bfloat16_t > - Cnumeric_limits< double > - Cnumeric_limits< float > - Cnumeric_limits< float16_t > - CPad - CPartition - CPower - CPrimitive - CPrintFormatter - CQRF - CQuantizedMatmul - CRandomBits - CReal - CReduce - CReductionPlan - CRemainder - CReshape - CRound - CScalarVector - CScan - CScatter - CScatterAxis - CSelect - CSigmoid - CSign - CSin - CSinh - CSlice - CSliceUpdate - CSoftmax - CSort - CSplit - CSqrt - CSquare - CSqueeze - CStopGradient - CStream - CStreamContext - CSubtract - CSVD - CTan - CTanh - CTranspose - CTypeToDtype - CUnaryPrimitive - CUnflatten - CVectorScalar - CVectorVector - CView + ►Ncpu + CCommandEncoder + ►Ndetail + CAbs + CAdd + CArcCos + CArcCosh + CArcSin + CArcSinh + CArcTan + CArcTan2 + CArcTanh + CBitwiseAnd + CBitwiseInvert + CBitwiseOr + CBitwiseXor + CCeil + CConjugate + CCos + CCosh + CDivide + CEqual + CErf + CErfInv + CExp + CExpm1 + CFloor + CGreater + CGreaterEqual + CImag + CInTracing + CLeftShift + CLess + CLessEqual + CLog + CLog10 + CLog1p + CLog2 + CLogAddExp + CLogicalAnd + CLogicalNot + CLogicalOr + CMaximum + CMinimum + CMultiply + CNaNEqual + CNegative + CNotEqual + CPower + CReal + CRemainder + CRetainGraph + CRightShift + CRound + CRsqrt + CSelect + CSigmoid + CSign + CSin + CSinh + CSqrt + CSquare + CSubtract + CTan + CTanh + ►Ndistributed + ►Ndetail + CGroupImplAbstract base class of a distributed group implementation + CAllGather + CAllReduce + CDistPrimitive + CGroupA distributed::Group represents a group of independent mlx processes that can communicate + CRecv + CSend + ►Nfast + CAffineQuantize + CCustom + CCustomKernel + CCustomKernelShapeInfo + CLayerNorm + CLayerNormVJP + CRMSNorm + CRMSNormVJP + CRoPE + CScaledDotProductAttention + ►Nio + CFileWriter + CParallelFileReader + CReader + CWriter + ►Nmetal + CBuffer + ►CCommandEncoder + CConcurrentContext + CDevice + CDeviceStream + CFence + CMetalAllocator + CResidencySet + ►Nrandom + CKeySequence + ►Nscheduler + CScheduler + CStreamThread + ►Nsimd + CScalarT + CScalarT< bool, N > + CScalarT< int64_t, N > + CScalarT< int8_t, N > + CScalarT< uint64_t, N > + CSimd + CSimd< float16_t, N > + CSimd< T, 1 > + C_MLX_BFloat16 + C_MLX_Float16 + CAbs + CAdd + CAddMM + CArange + CArcCos + CArcCosh + CArcSin + CArcSinh + CArcTan + CArcTan2 + CArcTanh + CArgPartition + CArgReduce + CArgSort + ►Carray + CArrayIterator + CData + CFlags + CAsStrided + CAsType + CBitwiseBinary + CBitwiseInvert + CBlockMaskedMM + CBroadcast + CBroadcastAxes + CCeil + CCholesky + ►CCommandEncoder + CConcurrentContext + CCompiled + Ccomplex128_t + Ccomplex64_t + CConcatenate + CConjugate + CContiguous + CContiguousIterator + CConvolution + CCopy + CCos + CCosh + CCustomTransforms + CDepends + CDevice + CDivide + CDivMod + CDtype + CDynamicSlice + CDynamicSliceUpdate + CEigh + CEqual + CErf + CErfInv + CEvent + CExp + CExpandDims + CExpm1 + CFence + CFFT + CfinfoHolds information about floating-point types + CFlatten + CFloor + CFull + CFunctionExporter + CGather + CGatherAxis + CGatherMM + CGatherQMM + CGreater + CGreaterEqual + CHadamard + CImag + CImportedFunction + CInverse + CJitCompiler + CLess + CLessEqual + CLoad + CLog + CLog1p + CLogAddExp + CLogicalAnd + CLogicalNot + CLogicalOr + CLUF + CMatmul + CMaximum + CMinimum + CMultiply + CNegative + CNodeNamer + CNotEqual + CNumberOfElements + Cnumeric_limits + Cnumeric_limits< bfloat16_t > + Cnumeric_limits< double > + Cnumeric_limits< float > + Cnumeric_limits< float16_t > + CPad + CPartition + CPower + CPrimitive + CPrintFormatter + CQRF + CQuantizedMatmul + CRandomBits + CReal + CReduce + CReductionPlan + CRemainder + CReshape + CRound + CScalarVector + CScan + CScatter + CScatterAxis + CSelect + CSigmoid + CSign + CSin + CSinh + CSlice + CSliceUpdate + CSoftmax + CSort + CSplit + CSqrt + CSquare + CSqueeze + CStopGradient + CStream + CStreamContext + CSubtract + CSVD + CTan + CTanh + CTranspose + CTypeToDtype + CUnaryPrimitive + CUnflatten + CVectorScalar + CVectorVector + CView  ►Nsteel  CAccumHelper - CAttnParams - CBaseMMAFrag - CBaseMMAFrag< T, 8, 8 > - ►CBlockLoader - CReadVector - CBlockLoaderT - CBlockMMA - CBlockSwizzle - CChannelHelper - CChannelHelper< 1 > - CChannelHelper< 2 > - CChannelHelper< 3 > - CChannelHelper< 4 > - CConv2DGeneralBaseInfo - CConv2DGeneralJumpParams - CConv2DInputBlockLoaderGeneral - CConv2DInputBlockLoaderLargeFilter - CConv2DInputBlockLoaderSmallChannels - CConv2DInputBlockLoaderSmallFilter - CConv2DWeightBlockLoader - CConv2DWeightBlockLoaderGeneral - CConv2DWeightBlockLoaderSmallChannels - CCShape - CGEMMAddMMParams - CGEMMKernel - CGEMMParams - CGEMMSpiltKParams - CImplicitGemmConv2DParams - Cintegral_constant - Cis_integral - Cis_integral< integral_constant< T, v > > - CLayout2D - CLoopAlignment - CMMATile - CShape2D - CTransformAdd - CTransformAxpby - CTransformNone + CAttnMaskParams + CAttnParams + CBaseMMAFrag + CBaseMMAFrag< T, 8, 8 > + ►CBlockLoader + CReadVector + CBlockLoaderT + CBlockMMA + CBlockSwizzle + CChannelHelper + CChannelHelper< 1 > + CChannelHelper< 2 > + CChannelHelper< 3 > + CChannelHelper< 4 > + CConv2DGeneralBaseInfo + CConv2DGeneralJumpParams + CConv2DInputBlockLoaderGeneral + CConv2DInputBlockLoaderLargeFilter + CConv2DInputBlockLoaderSmallChannels + CConv2DInputBlockLoaderSmallFilter + CConv2DWeightBlockLoader + CConv2DWeightBlockLoaderGeneral + CConv2DWeightBlockLoaderSmallChannels + CCShape + CGEMMAddMMParams + CGEMMKernel + CGEMMParams + CGEMMSpiltKParams + CImplicitGemmConv2DParams + Cintegral_constant + Cis_integral + Cis_integral< integral_constant< T, v > > + CLayout2D + CLoopAlignment + CMMATile + CShape2D + CTransformAdd + CTransformAxpby + CTransformNone  ►Npocketfft  ►Ndetail  ►Nthreading diff --git a/docs/build/html/annotated_dup.js b/docs/build/html/annotated_dup.js index 47263365a..3d1aa66b4 100644 --- a/docs/build/html/annotated_dup.js +++ b/docs/build/html/annotated_dup.js @@ -18,6 +18,9 @@ var annotated_dup = [ "Buffer", "classmlx_1_1core_1_1allocator_1_1_buffer.html", "classmlx_1_1core_1_1allocator_1_1_buffer" ], [ "CommonAllocator", "classmlx_1_1core_1_1allocator_1_1_common_allocator.html", "classmlx_1_1core_1_1allocator_1_1_common_allocator" ] ] ], + [ "cpu", "namespacemlx_1_1core_1_1cpu.html", [ + [ "CommandEncoder", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html", "structmlx_1_1core_1_1cpu_1_1_command_encoder" ] + ] ], [ "detail", "namespacemlx_1_1core_1_1detail.html", [ [ "Abs", "structmlx_1_1core_1_1detail_1_1_abs.html", "structmlx_1_1core_1_1detail_1_1_abs" ], [ "Add", "structmlx_1_1core_1_1detail_1_1_add.html", "structmlx_1_1core_1_1detail_1_1_add" ], @@ -280,6 +283,7 @@ var annotated_dup = ] ], [ "steel", "namespacemlx_1_1steel.html", [ [ "AccumHelper", "structmlx_1_1steel_1_1_accum_helper.html", "structmlx_1_1steel_1_1_accum_helper" ], + [ "AttnMaskParams", "structmlx_1_1steel_1_1_attn_mask_params.html", "structmlx_1_1steel_1_1_attn_mask_params" ], [ "AttnParams", "structmlx_1_1steel_1_1_attn_params.html", "structmlx_1_1steel_1_1_attn_params" ], [ "BaseMMAFrag", "structmlx_1_1steel_1_1_base_m_m_a_frag.html", null ], [ "BaseMMAFrag< T, 8, 8 >", "structmlx_1_1steel_1_1_base_m_m_a_frag_3_01_t_00_018_00_018_01_4.html", "structmlx_1_1steel_1_1_base_m_m_a_frag_3_01_t_00_018_00_018_01_4" ], diff --git a/docs/build/html/array_8h_source.html b/docs/build/html/array_8h_source.html index b4507c380..6c4e4e996 100644 --- a/docs/build/html/array_8h_source.html +++ b/docs/build/html/array_8h_source.html @@ -314,515 +314,497 @@ $(function(){initNavTree('array_8h_source.html',''); initResizable(true); });
199 const std::shared_ptr<Primitive>& primitive,
200 const std::vector<array>& inputs);
201
-
-
203 std::uintptr_t id() const {
-
204 return reinterpret_cast<std::uintptr_t>(array_desc_.get());
-
205 }
+
207 static array unsafe_weak_copy(const array& other);
+
208
+
+
210 std::uintptr_t id() const {
+
211 return reinterpret_cast<std::uintptr_t>(array_desc_.get());
+
212 }
-
206
-
-
208 std::uintptr_t primitive_id() const {
-
209 return reinterpret_cast<std::uintptr_t>(array_desc_->primitive.get());
-
210 }
-
-
211
-
-
212 struct Data {
-
213 allocator::Buffer buffer;
-
214 Deleter d;
+
213
-
215 Data(allocator::Buffer buffer, Deleter d = allocator::free)
-
216 : buffer(buffer), d(d) {}
+
215 std::uintptr_t primitive_id() const {
+
216 return reinterpret_cast<std::uintptr_t>(array_desc_->primitive.get());
+
217 }
-
217 // Not copyable
-
218 Data(const Data& d) = delete;
-
219 Data& operator=(const Data& d) = delete;
-
-
220 ~Data() {
-
221 d(buffer);
-
222 }
+
218
+
+
219 struct Data {
+
220 allocator::Buffer buffer;
+
221 Deleter d;
+ -
223 };
+
224 // Not copyable
+
225 Data(const Data& d) = delete;
+
226 Data& operator=(const Data& d) = delete;
+
+
227 ~Data() {
+
228 d(buffer);
+
229 }
-
224
-
-
225 struct Flags {
-
226 // True iff there are no gaps in the underlying data. Each item
-
227 // in the underlying data buffer belongs to at least one index.
-
228 //
-
229 // True iff:
-
230 // prod(shape[i] for i in range(ndim) if strides[i] > 0) == data_size()
-
231 bool contiguous : 1;
-
232
-
233 // True iff:
-
234 // strides[-1] == 1 and
-
235 // all(strides[i] == (shape[i+1]*strides[i+1]) or shape[i] == 1 for i in
-
236 // range(ndim - 1))
-
237 bool row_contiguous : 1;
-
238
-
239 // True iff:
-
240 // strides[0] == 1 and
-
241 // all(strides[i] == (shape[i-1]*strides[i-1]) or shape[i] == 1 for i in
-
242 // range(1, ndim))
-
243 bool col_contiguous : 1;
-
244 };
+
230 };
+
+
231
+
+
232 struct Flags {
+
233 // True iff there are no gaps in the underlying data. Each item
+
234 // in the underlying data buffer belongs to at least one index.
+
235 //
+
236 // True iff:
+
237 // prod(shape[i] for i in range(ndim) if strides[i] > 0) == data_size()
+
238 bool contiguous : 1;
+
239
+
240 // True iff:
+
241 // strides[-1] == 1 and
+
242 // all(strides[i] == (shape[i+1]*strides[i+1]) or shape[i] == 1 for i in
+
243 // range(ndim - 1))
+
244 bool row_contiguous : 1;
+
245
+
246 // True iff:
+
247 // strides[0] == 1 and
+
248 // all(strides[i] == (shape[i-1]*strides[i-1]) or shape[i] == 1 for i in
+
249 // range(1, ndim))
+
250 bool col_contiguous : 1;
+
251 };
+
+
252
+
+
254 Primitive& primitive() const {
+
255 return *(array_desc_->primitive);
+
256 }
-
245
-
249 explicit array(
-
250 allocator::Buffer data,
-
251 Shape shape,
-
252 Dtype dtype,
-
253 Strides strides,
-
254 size_t data_size,
-
255 Flags flags,
-
256 Deleter deleter = allocator::free);
257
-
259 Primitive& primitive() const {
-
260 return *(array_desc_->primitive);
+
259 std::shared_ptr<Primitive>& primitive_ptr() const {
+
260 return array_desc_->primitive;
261 }
262
-
264 std::shared_ptr<Primitive>& primitive_ptr() const {
-
265 return array_desc_->primitive;
+
264 bool has_primitive() const {
+
265 return array_desc_->primitive != nullptr;
266 }
267
-
269 bool has_primitive() const {
-
270 return array_desc_->primitive != nullptr;
+
269 const std::vector<array>& inputs() const {
+
270 return array_desc_->inputs;
271 }
-
272
-
-
274 const std::vector<array>& inputs() const {
-
275 return array_desc_->inputs;
-
276 }
+
272
+
+
273 std::vector<array>& inputs() {
+
274 return array_desc_->inputs;
+
275 }
-
277
+
276
-
278 std::vector<array>& inputs() {
-
279 return array_desc_->inputs;
+
278 bool is_donatable() const {
+
279 return array_desc_.use_count() == 1 && (array_desc_->data.use_count() == 1);
280 }
281
-
283 bool is_donatable() const {
-
284 return array_desc_.use_count() == 1 && (array_desc_->data.use_count() == 1);
+
283 const std::vector<array>& siblings() const {
+
284 return array_desc_->siblings;
285 }
286
-
288 const std::vector<array>& siblings() const {
+
288 std::vector<array>& siblings() {
289 return array_desc_->siblings;
290 }
-
291
-
-
293 std::vector<array>& siblings() {
-
294 return array_desc_->siblings;
+
291
+
+
292 void set_siblings(std::vector<array> siblings, uint16_t position) {
+
293 array_desc_->siblings = std::move(siblings);
+
294 array_desc_->position = position;
295 }
-
296
-
-
297 void set_siblings(std::vector<array> siblings, uint16_t position) {
-
298 array_desc_->siblings = std::move(siblings);
-
299 array_desc_->position = position;
-
300 }
+
296
+
+
299 std::vector<array> outputs() const {
+
300 auto idx = array_desc_->position;
+
301 std::vector<array> outputs;
+
302 outputs.reserve(siblings().size() + 1);
+
303 outputs.insert(outputs.end(), siblings().begin(), siblings().begin() + idx);
+
304 outputs.push_back(*this);
+
305 outputs.insert(outputs.end(), siblings().begin() + idx, siblings().end());
+
306 return outputs;
+
307 }
-
301
-
-
304 std::vector<array> outputs() const {
-
305 auto idx = array_desc_->position;
-
306 std::vector<array> outputs;
-
307 outputs.reserve(siblings().size() + 1);
-
308 outputs.insert(outputs.end(), siblings().begin(), siblings().begin() + idx);
-
309 outputs.push_back(*this);
-
310 outputs.insert(outputs.end(), siblings().begin() + idx, siblings().end());
-
311 return outputs;
-
312 }
+
308
+
310 void detach();
+
311
+
+
313 const Flags& flags() const {
+
314 return array_desc_->flags;
+
315 }
-
313
-
315 void detach();
316
-
-
318 const Flags& flags() const {
-
319 return array_desc_->flags;
-
320 }
+
+
327 size_t data_size() const {
+
328 return array_desc_->data_size;
+
329 }
-
321
-
-
332 size_t data_size() const {
-
333 return array_desc_->data_size;
-
334 }
+
330
+
+
331 allocator::Buffer& buffer() {
+
332 return array_desc_->data->buffer;
+
333 }
-
335
-
-
336 allocator::Buffer& buffer() {
-
337 return array_desc_->data->buffer;
-
338 }
+
+
334 const allocator::Buffer& buffer() const {
+
335 return array_desc_->data->buffer;
+
336 }
-
-
339 const allocator::Buffer& buffer() const {
-
340 return array_desc_->data->buffer;
-
341 }
+
337
+
+
338 size_t buffer_size() const {
+
339 return allocator::allocator().size(buffer());
+
340 }
-
342
-
-
343 size_t buffer_size() const {
-
344 return allocator::allocator().size(buffer());
-
345 }
+
341
+
342 // Return a copy of the shared pointer
+
343 // to the array::Data struct
+
+
344 std::shared_ptr<Data> data_shared_ptr() const {
+
345 return array_desc_->data;
+
346 }
-
346
-
347 // Return a copy of the shared pointer
-
348 // to the array::Data struct
+
347 // Return a raw pointer to the arrays data
+
348 template <typename T>
-
349 std::shared_ptr<Data> data_shared_ptr() const {
-
350 return array_desc_->data;
+
349 T* data() {
+
350 return static_cast<T*>(array_desc_->data_ptr);
351 }
-
352 // Return a raw pointer to the arrays data
+
352
353 template <typename T>
-
354 T* data() {
+
354 const T* data() const {
355 return static_cast<T*>(array_desc_->data_ptr);
356 }
357
-
358 template <typename T>
-
-
359 const T* data() const {
-
360 return static_cast<T*>(array_desc_->data_ptr);
-
361 }
-
+
+
358 enum Status {
+
359 // The ouptut of a computation which has not been scheduled.
+
360 // For example, the status of `x` in `auto x = a + b`.
+
361 unscheduled,
362
-
-
363 enum Status {
-
364 // The ouptut of a computation which has not been scheduled.
-
365 // For example, the status of `x` in `auto x = a + b`.
-
366 unscheduled,
+
363 // The array's `eval_*` function has been run, but the computation is not
+
364 // necessarily complete. The array will have memory allocated and if it is
+
365 // not a tracer then it will be detached from the graph.
+
366 evaluated,
367
-
368 // The ouptut of a computation which has been scheduled but `eval_*` has
-
369 // not yet been called on the array's primitive. A possible
-
370 // status of `x` in `auto x = a + b; eval(x);`
-
371 scheduled,
-
372
-
373 // The array's `eval_*` function has been run, but the computation is not
-
374 // necessarily complete. The array will have memory allocated and if it is
-
375 // not a tracer then it will be detached from the graph.
-
376 evaluated,
-
377
-
378 // If the array is the output of a computation then the computation
-
379 // is complete. Constant arrays are always available (e.g. `array({1, 2,
-
380 // 3})`)
-
381 available
-
382 };
+
368 // If the array is the output of a computation then the computation
+
369 // is complete. Constant arrays are always available (e.g. `array({1, 2,
+
370 // 3})`)
+
371 available
+
372 };
-
383
-
384 // Check if the array is safe to read.
-
385 bool is_available() const;
-
386
-
387 // Wait on the array to be available. After this `is_available` returns
-
388 // `true`.
-
389 void wait();
-
390
-
-
391 Status status() const {
-
392 return array_desc_->status;
-
393 }
+
373
+
374 // Check if the array is safe to read.
+
375 bool is_available() const;
+
376
+
377 // Wait on the array to be available. After this `is_available` returns
+
378 // `true`.
+
379 void wait();
+
380
+
+
381 Status status() const {
+
382 return array_desc_->status;
+
383 }
-
394
+
384
+
+
385 void set_status(Status s) const {
+
386 array_desc_->status = s;
+
387 }
+
+
388
+
389 // Get the array's shared event
+
+
390 Event& event() const {
+
391 return array_desc_->event;
+
392 }
+
+
393
+
394 // Attach an event to a not yet evaluated array
-
395 void set_status(Status s) const {
-
396 array_desc_->status = s;
+
395 void attach_event(Event e) const {
+
396 array_desc_->event = std::move(e);
397 }
398
-
399 // Get the array's shared event
-
-
400 Event& event() const {
-
401 return array_desc_->event;
-
402 }
+
+
399 void detach_event() const {
+
400 array_desc_->event = Event{};
+
401 }
-
403
-
404 // Attach an event to a not yet evaluated array
-
-
405 void attach_event(Event e) const {
-
406 array_desc_->event = std::move(e);
-
407 }
+
402
+
403 // Mark the array as a tracer array (true) or not.
+
+
404 void set_tracer(bool is_tracer) {
+
405 array_desc_->is_tracer = is_tracer;
+
406 }
-
408
-
409 // Mark the array as a tracer array (true) or not.
-
-
410 void set_tracer(bool is_tracer) {
-
411 array_desc_->is_tracer = is_tracer;
-
412 }
-
-
413 // Check if the array is a tracer array
-
414 bool is_tracer() const;
-
415
-
416 void set_data(allocator::Buffer buffer, Deleter d = allocator::free);
-
417
-
418 void set_data(
-
419 allocator::Buffer buffer,
-
420 size_t data_size,
-
421 Strides strides,
+
407 // Check if the array is a tracer array
+
408 bool is_tracer() const;
+
409
+
410 void set_data(allocator::Buffer buffer, Deleter d = allocator::free);
+
411
+
412 void set_data(
+
413 allocator::Buffer buffer,
+
414 size_t data_size,
+
415 Strides strides,
+
416 Flags flags,
+
417 Deleter d = allocator::free);
+
418
+
419 void copy_shared_buffer(
+
420 const array& other,
+
421 const Strides& strides,
422 Flags flags,
-
423 Deleter d = allocator::free);
-
424
-
425 void copy_shared_buffer(
-
426 const array& other,
-
427 const Strides& strides,
-
428 Flags flags,
-
429 size_t data_size,
-
430 size_t offset = 0);
-
431
-
432 void copy_shared_buffer(const array& other);
-
433
-
434 void move_shared_buffer(
-
435 array other,
-
436 const Strides& strides,
-
437 Flags flags,
-
438 size_t data_size,
-
439 size_t offset = 0);
-
440
-
441 void move_shared_buffer(array other);
-
442
-
-
443 void overwrite_descriptor(const array& other) {
-
444 array_desc_ = other.array_desc_;
-
445 }
+
423 size_t data_size,
+
424 size_t offset = 0);
+
425
+
426 void copy_shared_buffer(const array& other);
+
427
+
+
428 void overwrite_descriptor(const array& other) {
+
429 array_desc_ = other.array_desc_;
+
430 }
-
446
-
447 ~array();
-
448
-
449 private:
-
450 // Initialize the arrays data
-
451 template <typename It>
-
452 void init(const It src);
-
453
-
454 struct ArrayDesc {
-
455 Shape shape;
-
456 Strides strides;
-
457 size_t size;
-
458 Dtype dtype;
-
459 std::shared_ptr<Primitive> primitive;
-
460
-
461 Status status;
-
462
-
463 // An event on the array used for synchronization
-
464 Event event;
-
465
-
466 // Indicates an array is being used in a graph transform
-
467 // and should not be detached from the graph
-
468 bool is_tracer{false};
-
469
-
470 // This is a shared pointer so that *different* arrays
-
471 // can share the underlying data buffer.
-
472 std::shared_ptr<Data> data;
-
473
-
474 // Properly offset data pointer
-
475 void* data_ptr{nullptr};
+
431
+
432 ~array();
+
433
+
434 private:
+
435 // Initialize the arrays data
+
436 template <typename It>
+
437 void init(const It src);
+
438
+
439 struct ArrayDesc {
+
440 Shape shape;
+
441 Strides strides;
+
442 size_t size;
+
443 Dtype dtype;
+
444 std::shared_ptr<Primitive> primitive;
+
445
+
446 Status status;
+
447
+
448 // An event on the array used for synchronization
+
449 Event event;
+
450
+
451 // Indicates an array is being used in a graph transform
+
452 // and should not be detached from the graph
+
453 bool is_tracer{false};
+
454
+
455 // This is a shared pointer so that *different* arrays
+
456 // can share the underlying data buffer.
+
457 std::shared_ptr<Data> data;
+
458
+
459 // Properly offset data pointer
+
460 void* data_ptr{nullptr};
+
461
+
462 // The size in elements of the data buffer the array accesses
+
463 size_t data_size;
+
464
+
465 // Contains useful meta data about the array
+
466 Flags flags;
+
467
+
468 std::vector<array> inputs;
+
469 // An array to keep track of the siblings from a multi-output
+
470 // primitive.
+
471 std::vector<array> siblings;
+
472 // The arrays position in the output list
+
473 uint32_t position{0};
+
474
+
475 explicit ArrayDesc(Shape shape, Dtype dtype);
476
-
477 // The size in elements of the data buffer the array accesses
-
478 size_t data_size;
-
479
-
480 // Contains useful meta data about the array
-
481 Flags flags;
+
477 explicit ArrayDesc(
+
478 Shape shape,
+
479 Dtype dtype,
+
480 std::shared_ptr<Primitive> primitive,
+
481 std::vector<array> inputs);
482
-
483 std::vector<array> inputs;
-
484 // An array to keep track of the siblings from a multi-output
-
485 // primitive.
-
486 std::vector<array> siblings;
-
487 // The arrays position in the output list
-
488 uint32_t position{0};
+
483 ~ArrayDesc();
+
484
+
485 private:
+
486 // Initialize size, strides, and other metadata
+
487 void init();
+
488 };
489
-
490 explicit ArrayDesc(Shape shape, Dtype dtype);
-
491
-
492 explicit ArrayDesc(
-
493 Shape shape,
-
494 Dtype dtype,
-
495 std::shared_ptr<Primitive> primitive,
-
496 std::vector<array> inputs);
-
497
-
498 ~ArrayDesc();
-
499
-
500 private:
-
501 // Initialize size, strides, and other metadata
-
502 void init();
-
503 };
-
504
-
505 // The ArrayDesc contains the details of the materialized array including the
-
506 // shape, strides, the data type. It also includes
-
507 // the primitive which knows how to compute the array's data from its inputs
-
508 // and the list of array's inputs for the primitive.
-
509 std::shared_ptr<ArrayDesc> array_desc_;
-
510};
+
490 // The ArrayDesc contains the details of the materialized array including the
+
491 // shape, strides, the data type. It also includes
+
492 // the primitive which knows how to compute the array's data from its inputs
+
493 // and the list of array's inputs for the primitive.
+
494 std::shared_ptr<ArrayDesc> array_desc_;
+
495};
+
+
496
+
497template <typename T>
+
+
498array::array(T val, Dtype dtype /* = TypeToDtype<T>() */)
+
499 : array_desc_(std::make_shared<ArrayDesc>(Shape{}, dtype)) {
+
500 init(&val);
+
501}
+
+
502
+
503template <typename It>
+
+
504array::array(
+
505 It data,
+
506 Shape shape,
+
507 Dtype dtype /* = TypeToDtype<typename std::iterator_traits<It>::value_type>() */) :
+
508 array_desc_(std::make_shared<ArrayDesc>(std::move(shape), dtype)) {
+
509 init(data);
+
510}
511
512template <typename T>
-
513array::array(T val, Dtype dtype /* = TypeToDtype<T>() */)
-
514 : array_desc_(std::make_shared<ArrayDesc>(Shape{}, dtype)) {
-
515 init(&val);
-
516}
+
513array::array(
+
514 std::initializer_list<T> data,
+
515 Dtype dtype /* = TypeToDtype<T>() */)
+
516 : array_desc_(std::make_shared<ArrayDesc>(
+
517 Shape{static_cast<ShapeElem>(data.size())},
+
518 dtype)) {
+
519 init(data.begin());
+
520}
-
517
-
518template <typename It>
-
-
519array::array(
-
520 It data,
-
521 Shape shape,
-
522 Dtype dtype /* = TypeToDtype<typename std::iterator_traits<It>::value_type>() */) :
-
523 array_desc_(std::make_shared<ArrayDesc>(std::move(shape), dtype)) {
-
524 init(data);
-
525}
+
521
+
522template <typename T>
+
+
523array::array(
+
524 std::initializer_list<T> data,
+
525 Shape shape,
+
526 Dtype dtype /* = TypeToDtype<T>() */)
+
527 : array_desc_(std::make_shared<ArrayDesc>(std::move(shape), dtype)) {
+
528 if (data.size() != size()) {
+
529 throw std::invalid_argument(
+
530 "Data size and provided shape mismatch in array construction.");
+
531 }
+
532 init(data.begin());
+
533}
-
526
-
527template <typename T>
-
-
528array::array(
-
529 std::initializer_list<T> data,
-
530 Dtype dtype /* = TypeToDtype<T>() */)
-
531 : array_desc_(std::make_shared<ArrayDesc>(
-
532 Shape{static_cast<ShapeElem>(data.size())},
-
533 dtype)) {
-
534 init(data.begin());
-
535}
+
534
+
535template <typename T>
+
+
536T array::item() {
+
537 if (size() != 1) {
+
538 throw std::invalid_argument("item can only be called on arrays of size 1.");
+
539 }
+
540 eval();
+
541 return *data<T>();
+
542}
-
536
-
537template <typename T>
-
-
538array::array(
-
539 std::initializer_list<T> data,
-
540 Shape shape,
-
541 Dtype dtype /* = TypeToDtype<T>() */)
-
542 : array_desc_(std::make_shared<ArrayDesc>(std::move(shape), dtype)) {
-
543 if (data.size() != size()) {
-
544 throw std::invalid_argument(
-
545 "Data size and provided shape mismatch in array construction.");
-
546 }
-
547 init(data.begin());
-
548}
+
543
+
544template <typename T>
+
+
545T array::item() const {
+
546 if (size() != 1) {
+
547 throw std::invalid_argument("item can only be called on arrays of size 1.");
+
548 }
+
549 if (status() == Status::unscheduled) {
+
550 throw std::invalid_argument(
+
551 "item() const can only be called on evaled arrays");
+
552 }
+
553 const_cast<array*>(this)->eval();
+
554 return *data<T>();
+
555}
-
549
-
550template <typename T>
-
-
551T array::item() {
-
552 if (size() != 1) {
-
553 throw std::invalid_argument("item can only be called on arrays of size 1.");
-
554 }
-
555 eval();
-
556 return *data<T>();
-
557}
-
-
558
-
559template <typename T>
-
-
560T array::item() const {
-
561 if (size() != 1) {
-
562 throw std::invalid_argument("item can only be called on arrays of size 1.");
-
563 }
-
564 if (status() == Status::unscheduled) {
-
565 throw std::invalid_argument(
-
566 "item() const can only be called on evaled arrays");
-
567 }
-
568 const_cast<array*>(this)->eval();
-
569 return *data<T>();
-
570}
-
-
571
-
572template <typename It>
-
573void array::init(It src) {
-
574 set_data(allocator::malloc(size() * size_of(dtype())));
-
575 switch (dtype()) {
-
576 case bool_:
-
577 std::copy(src, src + size(), data<bool>());
+
556
+
557template <typename It>
+
558void array::init(It src) {
+
559 set_data(allocator::malloc(size() * size_of(dtype())));
+
560 switch (dtype()) {
+
561 case bool_:
+
562 std::copy(src, src + size(), data<bool>());
+
563 break;
+
564 case uint8:
+
565 std::copy(src, src + size(), data<uint8_t>());
+
566 break;
+
567 case uint16:
+
568 std::copy(src, src + size(), data<uint16_t>());
+
569 break;
+
570 case uint32:
+
571 std::copy(src, src + size(), data<uint32_t>());
+
572 break;
+
573 case uint64:
+
574 std::copy(src, src + size(), data<uint64_t>());
+
575 break;
+
576 case int8:
+
577 std::copy(src, src + size(), data<int8_t>());
578 break;
-
579 case uint8:
-
580 std::copy(src, src + size(), data<uint8_t>());
+
579 case int16:
+
580 std::copy(src, src + size(), data<int16_t>());
581 break;
-
582 case uint16:
-
583 std::copy(src, src + size(), data<uint16_t>());
+
582 case int32:
+
583 std::copy(src, src + size(), data<int32_t>());
584 break;
-
585 case uint32:
-
586 std::copy(src, src + size(), data<uint32_t>());
+
585 case int64:
+
586 std::copy(src, src + size(), data<int64_t>());
587 break;
-
588 case uint64:
-
589 std::copy(src, src + size(), data<uint64_t>());
+
588 case float16:
+
589 std::copy(src, src + size(), data<float16_t>());
590 break;
-
591 case int8:
-
592 std::copy(src, src + size(), data<int8_t>());
+
591 case float32:
+
592 std::copy(src, src + size(), data<float>());
593 break;
-
594 case int16:
-
595 std::copy(src, src + size(), data<int16_t>());
+
594 case float64:
+
595 std::copy(src, src + size(), data<double>());
596 break;
-
597 case int32:
-
598 std::copy(src, src + size(), data<int32_t>());
+
597 case bfloat16:
+
598 std::copy(src, src + size(), data<bfloat16_t>());
599 break;
-
600 case int64:
-
601 std::copy(src, src + size(), data<int64_t>());
+
600 case complex64:
+
601 std::copy(src, src + size(), data<complex64_t>());
602 break;
-
603 case float16:
-
604 std::copy(src, src + size(), data<float16_t>());
-
605 break;
-
606 case float32:
-
607 std::copy(src, src + size(), data<float>());
-
608 break;
-
609 case float64:
-
610 std::copy(src, src + size(), data<double>());
-
611 break;
-
612 case bfloat16:
-
613 std::copy(src, src + size(), data<bfloat16_t>());
-
614 break;
-
615 case complex64:
-
616 std::copy(src, src + size(), data<complex64_t>());
-
617 break;
-
618 }
-
619}
-
620
-
621/* Utilities for determining whether a template parameter is array. */
-
622template <typename T>
-
623inline constexpr bool is_array_v =
-
624 std::is_same_v<std::remove_cv_t<std::remove_reference_t<T>>, array>;
-
625
-
626template <typename... T>
-
627inline constexpr bool is_arrays_v = (is_array_v<T> && ...);
-
628
-
629template <typename... T>
-
630using enable_for_arrays_t = typename std::enable_if_t<is_arrays_v<T...>>;
-
631
-
632} // namespace mlx::core
+
603 }
+
604}
+
605
+
606/* Utilities for determining whether a template parameter is array. */
+
607template <typename T>
+
608inline constexpr bool is_array_v =
+
609 std::is_same_v<std::remove_cv_t<std::remove_reference_t<T>>, array>;
+
610
+
611template <typename... T>
+
612inline constexpr bool is_arrays_v = (is_array_v<T> && ...);
+
613
+
614template <typename... T>
+
615using enable_for_arrays_t = typename std::enable_if_t<is_arrays_v<T...>>;
+
616
+
617} // namespace mlx::core
mlx::core::Event
Definition event.h:11
mlx::core::Primitive
Definition primitives.h:48
mlx::core::allocator::Allocator::size
virtual size_t size(Buffer buffer) const =0
mlx::core::allocator::Buffer
Definition allocator.h:12
mlx::core::array
Definition array.h:24
-
mlx::core::array::attach_event
void attach_event(Event e) const
Definition array.h:405
-
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:318
-
mlx::core::array::event
Event & event() const
Definition array.h:400
-
mlx::core::array::Status
Status
Definition array.h:363
-
mlx::core::array::available
@ available
Definition array.h:381
-
mlx::core::array::evaluated
@ evaluated
Definition array.h:376
-
mlx::core::array::unscheduled
@ unscheduled
Definition array.h:366
-
mlx::core::array::scheduled
@ scheduled
Definition array.h:371
+
mlx::core::array::attach_event
void attach_event(Event e) const
Definition array.h:395
+
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:313
+
mlx::core::array::event
Event & event() const
Definition array.h:390
+
mlx::core::array::Status
Status
Definition array.h:358
+
mlx::core::array::available
@ available
Definition array.h:371
+
mlx::core::array::evaluated
@ evaluated
Definition array.h:366
+
mlx::core::array::unscheduled
@ unscheduled
Definition array.h:361
mlx::core::array::shape
const Shape & shape() const
The shape of the array as a vector of integers.
Definition array.h:103
-
mlx::core::array::array
array(allocator::Buffer data, Shape shape, Dtype dtype, Strides strides, size_t data_size, Flags flags, Deleter deleter=allocator::free)
Build an array from all the info held by the array description.
mlx::core::array::eval
void eval()
Evaluate the array.
mlx::core::array::strides
const Strides & strides() const
The strides of the array.
Definition array.h:117
-
mlx::core::array::inputs
const std::vector< array > & inputs() const
The array's inputs.
Definition array.h:274
+
mlx::core::array::inputs
const std::vector< array > & inputs() const
The array's inputs.
Definition array.h:269
mlx::core::array::array
array(const array &other)=default
-
mlx::core::array::outputs
std::vector< array > outputs() const
The outputs of the array's primitive (i.e.
Definition array.h:304
+
mlx::core::array::outputs
std::vector< array > outputs() const
The outputs of the array's primitive (i.e.
Definition array.h:299
mlx::core::array::nbytes
size_t nbytes() const
The number of bytes in the array.
Definition array.h:93
-
mlx::core::array::move_shared_buffer
void move_shared_buffer(array other)
mlx::core::array::make_arrays
static std::vector< array > make_arrays(std::vector< Shape > shapes, const std::vector< Dtype > &dtypes, const std::shared_ptr< Primitive > &primitive, const std::vector< array > &inputs)
mlx::core::array::array
array(std::initializer_list< float > data)
-
mlx::core::array::is_donatable
bool is_donatable() const
True indicates the arrays buffer is safe to reuse.
Definition array.h:283
+
mlx::core::array::is_donatable
bool is_donatable() const
True indicates the arrays buffer is safe to reuse.
Definition array.h:278
mlx::core::array::array
array(allocator::Buffer data, Shape shape, Dtype dtype, Deleter deleter=allocator::free)
-
mlx::core::array::primitive_ptr
std::shared_ptr< Primitive > & primitive_ptr() const
A shared pointer to the array's primitive.
Definition array.h:264
+
mlx::core::array::primitive_ptr
std::shared_ptr< Primitive > & primitive_ptr() const
A shared pointer to the array's primitive.
Definition array.h:259
mlx::core::array::ndim
size_t ndim() const
The number of dimensions of the array.
Definition array.h:98
mlx::core::array::size
size_t size() const
The number of elements in the array.
Definition array.h:88
mlx::core::array::operator=
array & operator=(array &&other) &&=delete
@@ -830,45 +812,46 @@ $(function(){initNavTree('array_8h_source.html',''); initResizable(true); });
mlx::core::array::end
ArrayIterator end() const
Definition array.h:180
mlx::core::array::array
array(std::initializer_list< int > data, Dtype dtype)
mlx::core::array::set_data
void set_data(allocator::Buffer buffer, size_t data_size, Strides strides, Flags flags, Deleter d=allocator::free)
-
mlx::core::array::buffer
const allocator::Buffer & buffer() const
Definition array.h:339
-
mlx::core::array::set_status
void set_status(Status s) const
Definition array.h:395
+
mlx::core::array::buffer
const allocator::Buffer & buffer() const
Definition array.h:334
+
mlx::core::array::set_status
void set_status(Status s) const
Definition array.h:385
mlx::core::array::array
array(const std::complex< float > &val, Dtype dtype=complex64)
-
mlx::core::array::status
Status status() const
Definition array.h:391
-
mlx::core::array::siblings
std::vector< array > & siblings()
The array's siblings.
Definition array.h:293
-
mlx::core::array::data
T * data()
Definition array.h:354
-
mlx::core::array::array
array(T val, Dtype dtype=TypeToDtype< T >())
Construct a scalar array with zero dimensions.
Definition array.h:513
+
mlx::core::array::status
Status status() const
Definition array.h:381
+
mlx::core::array::siblings
std::vector< array > & siblings()
The array's siblings.
Definition array.h:288
+
mlx::core::array::data
T * data()
Definition array.h:349
+
mlx::core::array::array
array(T val, Dtype dtype=TypeToDtype< T >())
Construct a scalar array with zero dimensions.
Definition array.h:498
mlx::core::array::begin
ArrayIterator begin() const
Definition array.h:177
-
mlx::core::array::primitive
Primitive & primitive() const
The array's primitive.
Definition array.h:259
+
mlx::core::array::primitive
Primitive & primitive() const
The array's primitive.
Definition array.h:254
+
mlx::core::array::unsafe_weak_copy
static array unsafe_weak_copy(const array &other)
Get a new array that refers to the same data as the input but with a non-owning pointer to it.
mlx::core::array::detach
void detach()
Detach the array from the graph.
mlx::core::array::operator=
array & operator=(const array &other) &&=delete
Assignment to rvalue does not compile.
-
mlx::core::array::set_siblings
void set_siblings(std::vector< array > siblings, uint16_t position)
Definition array.h:297
-
mlx::core::array::item
T item()
Get the value from a scalar array.
Definition array.h:551
-
mlx::core::array::buffer_size
size_t buffer_size() const
Definition array.h:343
+
mlx::core::array::set_siblings
void set_siblings(std::vector< array > siblings, uint16_t position)
Definition array.h:292
+
mlx::core::array::item
T item()
Get the value from a scalar array.
Definition array.h:536
+
mlx::core::array::buffer_size
size_t buffer_size() const
Definition array.h:338
mlx::core::array::copy_shared_buffer
void copy_shared_buffer(const array &other)
-
mlx::core::array::overwrite_descriptor
void overwrite_descriptor(const array &other)
Definition array.h:443
-
mlx::core::array::data
const T * data() const
Definition array.h:359
-
mlx::core::array::has_primitive
bool has_primitive() const
Check if the array has an attached primitive or is a leaf node.
Definition array.h:269
-
mlx::core::array::buffer
allocator::Buffer & buffer()
Definition array.h:336
+
mlx::core::array::overwrite_descriptor
void overwrite_descriptor(const array &other)
Definition array.h:428
+
mlx::core::array::data
const T * data() const
Definition array.h:354
+
mlx::core::array::detach_event
void detach_event() const
Definition array.h:399
+
mlx::core::array::has_primitive
bool has_primitive() const
Check if the array has an attached primitive or is a leaf node.
Definition array.h:264
+
mlx::core::array::buffer
allocator::Buffer & buffer()
Definition array.h:331
mlx::core::array::array
array(array &&other)=default
-
mlx::core::array::data_shared_ptr
std::shared_ptr< Data > data_shared_ptr() const
Definition array.h:349
+
mlx::core::array::data_shared_ptr
std::shared_ptr< Data > data_shared_ptr() const
Definition array.h:344
mlx::core::array::array
array(Shape shape, Dtype dtype, std::shared_ptr< Primitive > primitive, std::vector< array > inputs)
The following methods should be used with caution.
mlx::core::array::shape
auto shape(int dim) const
Get the size of the corresponding dimension.
Definition array.h:112
mlx::core::array::strides
auto strides(int dim) const
Get the stride of the corresponding dimension.
Definition array.h:126
-
mlx::core::array::siblings
const std::vector< array > & siblings() const
The array's siblings.
Definition array.h:288
-
mlx::core::array::inputs
std::vector< array > & inputs()
Definition array.h:278
+
mlx::core::array::siblings
const std::vector< array > & siblings() const
The array's siblings.
Definition array.h:283
+
mlx::core::array::inputs
std::vector< array > & inputs()
Definition array.h:273
mlx::core::array::copy_shared_buffer
void copy_shared_buffer(const array &other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
mlx::core::array::operator=
array & operator=(array &&other) &=default
Default copy and move constructors otherwise.
-
mlx::core::array::move_shared_buffer
void move_shared_buffer(array other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
-
mlx::core::array::id
std::uintptr_t id() const
A unique identifier for an array.
Definition array.h:203
+
mlx::core::array::id
std::uintptr_t id() const
A unique identifier for an array.
Definition array.h:210
mlx::core::array::dtype
Dtype dtype() const
Get the arrays data type.
Definition array.h:131
mlx::core::array::is_available
bool is_available() const
-
mlx::core::array::set_tracer
void set_tracer(bool is_tracer)
Definition array.h:410
+
mlx::core::array::set_tracer
void set_tracer(bool is_tracer)
Definition array.h:404
mlx::core::array::itemsize
size_t itemsize() const
The size of the array's datatype in bytes.
Definition array.h:83
-
mlx::core::array::primitive_id
std::uintptr_t primitive_id() const
A unique identifier for an arrays primitive.
Definition array.h:208
+
mlx::core::array::primitive_id
std::uintptr_t primitive_id() const
A unique identifier for an arrays primitive.
Definition array.h:215
mlx::core::array::is_tracer
bool is_tracer() const
mlx::core::array::set_data
void set_data(allocator::Buffer buffer, Deleter d=allocator::free)
-
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:332
+
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:327
mlx::core::std
array std(const array &a, bool keepdims, int ddof=0, StreamOrDevice s={})
Computes the standard deviation of the elements of an array.
@@ -876,7 +859,7 @@ $(function(){initNavTree('array_8h_source.html',''); initResizable(true); });
mlx::core::allocator::free
void free(Buffer buffer)
mlx::core::allocator::allocator
Allocator & allocator()
mlx::core
Definition allocator.h:7
-
mlx::core::is_array_v
constexpr bool is_array_v
Definition array.h:623
+
mlx::core::is_array_v
constexpr bool is_array_v
Definition array.h:608
mlx::core::bool_
constexpr Dtype bool_
Definition dtype.h:68
mlx::core::ShapeElem
int32_t ShapeElem
Definition array.h:20
mlx::core::uint64
constexpr Dtype uint64
Definition dtype.h:73
@@ -890,13 +873,13 @@ $(function(){initNavTree('array_8h_source.html',''); initResizable(true); });
mlx::core::Strides
std::vector< int64_t > Strides
Definition array.h:22
mlx::core::int8
constexpr Dtype int8
Definition dtype.h:75
mlx::core::int64
constexpr Dtype int64
Definition dtype.h:78
-
mlx::core::is_arrays_v
constexpr bool is_arrays_v
Definition array.h:627
+
mlx::core::is_arrays_v
constexpr bool is_arrays_v
Definition array.h:612
mlx::core::uint8
constexpr Dtype uint8
Definition dtype.h:70
mlx::core::float16
constexpr Dtype float16
Definition dtype.h:80
mlx::core::uint32
constexpr Dtype uint32
Definition dtype.h:72
mlx::core::size_of
uint8_t size_of(const Dtype &t)
Definition dtype.h:104
mlx::core::Deleter
std::function< void(allocator::Buffer)> Deleter
Definition array.h:19
-
mlx::core::enable_for_arrays_t
typename std::enable_if_t< is_arrays_v< T... > > enable_for_arrays_t
Definition array.h:630
+
mlx::core::enable_for_arrays_t
typename std::enable_if_t< is_arrays_v< T... > > enable_for_arrays_t
Definition array.h:615
mlx::core::complex64
constexpr Dtype complex64
Definition dtype.h:84
mlx::core::Dtype
Definition dtype.h:13
mlx::core::TypeToDtype
Definition dtype.h:111
@@ -911,16 +894,16 @@ $(function(){initNavTree('array_8h_source.html',''); initResizable(true); });
mlx::core::array::ArrayIterator::difference_type
size_t difference_type
Definition array.h:147
mlx::core::array::ArrayIterator::value_type
const array value_type
Definition array.h:148
mlx::core::array::ArrayIterator::operator+
ArrayIterator & operator+(difference_type diff)
Definition array.h:155
-
mlx::core::array::Data::d
Deleter d
Definition array.h:214
-
mlx::core::array::Data::Data
Data(allocator::Buffer buffer, Deleter d=allocator::free)
Definition array.h:215
-
mlx::core::array::Data::~Data
~Data()
Definition array.h:220
+
mlx::core::array::Data::d
Deleter d
Definition array.h:221
+
mlx::core::array::Data::Data
Data(allocator::Buffer buffer, Deleter d=allocator::free)
Definition array.h:222
+
mlx::core::array::Data::~Data
~Data()
Definition array.h:227
mlx::core::array::Data::Data
Data(const Data &d)=delete
mlx::core::array::Data::operator=
Data & operator=(const Data &d)=delete
-
mlx::core::array::Data::buffer
allocator::Buffer buffer
Definition array.h:213
-
mlx::core::array::Flags
Definition array.h:225
-
mlx::core::array::Flags::row_contiguous
bool row_contiguous
Definition array.h:237
-
mlx::core::array::Flags::col_contiguous
bool col_contiguous
Definition array.h:243
-
mlx::core::array::Flags::contiguous
bool contiguous
Definition array.h:231
+
mlx::core::array::Data::buffer
allocator::Buffer buffer
Definition array.h:220
+
mlx::core::array::Flags
Definition array.h:232
+
mlx::core::array::Flags::row_contiguous
bool row_contiguous
Definition array.h:244
+
mlx::core::array::Flags::col_contiguous
bool col_contiguous
Definition array.h:250
+
mlx::core::array::Flags::contiguous
bool contiguous
Definition array.h:238
diff --git a/docs/build/html/attn_2mma_8h_source.html b/docs/build/html/attn_2mma_8h_source.html index 9de433931..d946a9747 100644 --- a/docs/build/html/attn_2mma_8h_source.html +++ b/docs/build/html/attn_2mma_8h_source.html @@ -228,7 +228,7 @@ $(function(){initNavTree('attn_2mma_8h_source.html',''); initResizable(true); })
111 for (short j = 0; j < kElemCols; j++) {
112 if ((off_x + i) < lim_x && (off_y + j) < lim_y) {
113 dst[i * kElemCols + j] =
-
114 static_cast<T>(src[(off_x + i) * str_x + (off_x + j) * str_y]);
+
114 static_cast<T>(src[(off_x + i) * str_x + (off_y + j) * str_y]);
115 } else {
116 dst[i * kElemCols + j] = T(0);
117 }
diff --git a/docs/build/html/attn_2params_8h.html b/docs/build/html/attn_2params_8h.html index eb1590053..7947a653e 100644 --- a/docs/build/html/attn_2params_8h.html +++ b/docs/build/html/attn_2params_8h.html @@ -115,6 +115,8 @@ $(function(){initNavTree('attn_2params_8h.html',''); initResizable(true); }); Classes struct  mlx::steel::AttnParams   +struct  mlx::steel::AttnMaskParams +  diff --git a/docs/build/html/attn_2params_8h.js b/docs/build/html/attn_2params_8h.js index f9f62aac2..bc0247386 100644 --- a/docs/build/html/attn_2params_8h.js +++ b/docs/build/html/attn_2params_8h.js @@ -1,4 +1,5 @@ var attn_2params_8h = [ - [ "mlx::steel::AttnParams", "structmlx_1_1steel_1_1_attn_params.html", "structmlx_1_1steel_1_1_attn_params" ] + [ "mlx::steel::AttnParams", "structmlx_1_1steel_1_1_attn_params.html", "structmlx_1_1steel_1_1_attn_params" ], + [ "mlx::steel::AttnMaskParams", "structmlx_1_1steel_1_1_attn_mask_params.html", "structmlx_1_1steel_1_1_attn_mask_params" ] ]; \ No newline at end of file diff --git a/docs/build/html/attn_2params_8h_source.html b/docs/build/html/attn_2params_8h_source.html index 9c099d6bf..9f8a8ee8b 100644 --- a/docs/build/html/attn_2params_8h_source.html +++ b/docs/build/html/attn_2params_8h_source.html @@ -132,20 +132,33 @@ $(function(){initNavTree('attn_2params_8h_source.html',''); initResizable(true);
26 int NQ_aligned;
27 int NK_aligned;
28
-
29 int64_t Q_strides[3];
-
30 int64_t K_strides[3];
-
31 int64_t V_strides[3];
-
32 int64_t O_strides[3];
-
33};
+
29 int qL_rem;
+
30 int kL_rem;
+
31 int qL_off;
+
32
+
33 int64_t Q_strides[3];
+
34 int64_t K_strides[3];
+
35 int64_t V_strides[3];
+
36 int64_t O_strides[3];
+
37};
-
34
-
35} // namespace steel
-
36} // namespace mlx
+
38
+
+
39struct AttnMaskParams {
+
40 int64_t M_strides[3];
+
41};
+
+
42
+
43} // namespace steel
+
44} // namespace mlx
mlx::steel
Definition attn.h:19
mlx
Definition allocator.h:7
+
mlx::steel::AttnMaskParams
Definition params.h:39
+
mlx::steel::AttnMaskParams::M_strides
int64_t M_strides[3]
Mask strides (B, H, qL, kL = 1)
Definition params.h:40
mlx::steel::AttnParams
Definition params.h:12
mlx::steel::AttnParams::D
int D
Head Dim.
Definition params.h:15
mlx::steel::AttnParams::B
int B
Batch Size.
Definition params.h:13
+
mlx::steel::AttnParams::qL_off
int qL_off
Offset in query sequence start.
Definition params.h:31
mlx::steel::AttnParams::gqa_factor
int gqa_factor
Group Query factor.
Definition params.h:20
mlx::steel::AttnParams::H
int H
Heads.
Definition params.h:14
mlx::steel::AttnParams::NQ
int NQ
Number of query blocks.
Definition params.h:23
@@ -153,12 +166,14 @@ $(function(){initNavTree('attn_2params_8h_source.html',''); initResizable(true);
mlx::steel::AttnParams::NQ_aligned
int NQ_aligned
Number of full query blocks.
Definition params.h:26
mlx::steel::AttnParams::qL
int qL
Query Sequence Length.
Definition params.h:17
mlx::steel::AttnParams::NK
int NK
Number of key/value blocks.
Definition params.h:24
-
mlx::steel::AttnParams::Q_strides
int64_t Q_strides[3]
Query strides (B, H, L, D = 1)
Definition params.h:29
+
mlx::steel::AttnParams::kL_rem
int kL_rem
Remainder in last key/value block.
Definition params.h:30
+
mlx::steel::AttnParams::Q_strides
int64_t Q_strides[3]
Query strides (B, H, L, D = 1)
Definition params.h:33
mlx::steel::AttnParams::NK_aligned
int NK_aligned
Number of full key/value blocks.
Definition params.h:27
-
mlx::steel::AttnParams::O_strides
int64_t O_strides[3]
Output strides (B, H, L, D = 1)
Definition params.h:32
-
mlx::steel::AttnParams::V_strides
int64_t V_strides[3]
Value strides (B, H, L, D = 1)
Definition params.h:31
+
mlx::steel::AttnParams::O_strides
int64_t O_strides[3]
Output strides (B, H, L, D = 1)
Definition params.h:36
+
mlx::steel::AttnParams::V_strides
int64_t V_strides[3]
Value strides (B, H, L, D = 1)
Definition params.h:35
mlx::steel::AttnParams::scale
float scale
Attention scale.
Definition params.h:21
-
mlx::steel::AttnParams::K_strides
int64_t K_strides[3]
Key strides (B, H, L, D = 1)
Definition params.h:30
+
mlx::steel::AttnParams::qL_rem
int qL_rem
Remainder in last query block.
Definition params.h:29
+
mlx::steel::AttnParams::K_strides
int64_t K_strides[3]
Key strides (B, H, L, D = 1)
Definition params.h:34
diff --git a/docs/build/html/backend_2common_2load_8h.js b/docs/build/html/backend_2common_2load_8h.js deleted file mode 100644 index 452297e46..000000000 --- a/docs/build/html/backend_2common_2load_8h.js +++ /dev/null @@ -1,4 +0,0 @@ -var backend_2common_2load_8h = -[ - [ "mlx::core::load", "namespacemlx_1_1core.html#a954de19249da7c1fa39b89bdc47368aa", null ] -]; \ No newline at end of file diff --git a/docs/build/html/backend_2common_2utils_8h.html b/docs/build/html/backend_2common_2utils_8h.html index 88924b13c..bff3735c0 100644 --- a/docs/build/html/backend_2common_2utils_8h.html +++ b/docs/build/html/backend_2common_2utils_8h.html @@ -149,10 +149,6 @@ Functions - - - - diff --git a/docs/build/html/backend_2common_2utils_8h.js b/docs/build/html/backend_2common_2utils_8h.js index e85f82ea1..56bbb881c 100644 --- a/docs/build/html/backend_2common_2utils_8h.js +++ b/docs/build/html/backend_2common_2utils_8h.js @@ -11,8 +11,6 @@ var backend_2common_2utils_8h = [ "mlx::core::elem_to_loc", "namespacemlx_1_1core.html#a59c0af06c5325c04ad8d69563c1c6b0a", null ], [ "mlx::core::is_donatable", "namespacemlx_1_1core.html#af650e831ce21759da1ac103037d08d84", null ], [ "mlx::core::make_contiguous_strides", "namespacemlx_1_1core.html#a449ef1148816a37bbc7ffd43d3c586a0", null ], - [ "mlx::core::move_or_copy", "namespacemlx_1_1core.html#a830a47d8a317dffb0c88e5a7afe6aee2", null ], - [ "mlx::core::move_or_copy", "namespacemlx_1_1core.html#a9fcb3711b150cb65c7778a35c51284b2", null ], [ "mlx::core::prepare_reshape", "namespacemlx_1_1core.html#a6783cfc7dbe1a116ba84a3904a37145f", null ], [ "mlx::core::shared_buffer_reshape", "namespacemlx_1_1core.html#a88d88987bd8bf3ca46bf3b5e8aacce9d", null ] ]; \ No newline at end of file diff --git a/docs/build/html/backend_2common_2utils_8h_source.html b/docs/build/html/backend_2common_2utils_8h_source.html index f347cbbfb..93218013f 100644 --- a/docs/build/html/backend_2common_2utils_8h_source.html +++ b/docs/build/html/backend_2common_2utils_8h_source.html @@ -292,30 +292,21 @@ $(function(){initNavTree('backend_2common_2utils_8h_source.html',''); initResiza
160}
161
-
162void move_or_copy(const array& in, array& out);
-
163void move_or_copy(
-
164 const array& in,
-
165 array& out,
-
166 const Strides& strides,
-
167 array::Flags flags,
-
168 size_t data_size,
-
169 size_t offset = 0);
-
170
-
171std::pair<bool, Strides> prepare_reshape(const array& in, const array& out);
-
172
-
173void shared_buffer_reshape(
-
174 const array& in,
-
175 const Strides& out_strides,
-
176 array& out);
-
177} // namespace mlx::core
+
162std::pair<bool, Strides> prepare_reshape(const array& in, const array& out);
+
163
+
164void shared_buffer_reshape(
+
165 const array& in,
+
166 const Strides& out_strides,
+
167 array& out);
+
168} // namespace mlx::core
mlx::core::array
Definition array.h:24
-
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:318
+
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:313
mlx::core::array::shape
const Shape & shape() const
The shape of the array as a vector of integers.
Definition array.h:103
mlx::core::array::strides
const Strides & strides() const
The strides of the array.
Definition array.h:117
mlx::core::array::nbytes
size_t nbytes() const
The number of bytes in the array.
Definition array.h:93
-
mlx::core::array::is_donatable
bool is_donatable() const
True indicates the arrays buffer is safe to reuse.
Definition array.h:283
-
mlx::core::array::buffer_size
size_t buffer_size() const
Definition array.h:343
+
mlx::core::array::is_donatable
bool is_donatable() const
True indicates the arrays buffer is safe to reuse.
Definition array.h:278
+
mlx::core::array::buffer_size
size_t buffer_size() const
Definition array.h:338
mlx::core::array::itemsize
size_t itemsize() const
The size of the array's datatype in bytes.
Definition array.h:83
mlx::core
Definition allocator.h:7
mlx::core::make_contiguous_strides
Strides make_contiguous_strides(const Shape &shape)
Definition utils.h:29
@@ -324,11 +315,10 @@ $(function(){initNavTree('backend_2common_2utils_8h_source.html',''); initResiza
mlx::core::prepare_reshape
std::pair< bool, Strides > prepare_reshape(const array &in, const array &out)
mlx::core::Shape
std::vector< ShapeElem > Shape
Definition array.h:21
mlx::core::Strides
std::vector< int64_t > Strides
Definition array.h:22
-
mlx::core::move_or_copy
void move_or_copy(const array &in, array &out)
mlx::core::shared_buffer_reshape
void shared_buffer_reshape(const array &in, const Strides &out_strides, array &out)
mlx::core::check_contiguity
auto check_contiguity(const Shape &shape, const Strides &strides)
Definition utils.h:134
mlx::core::is_donatable
bool is_donatable(const array &in, const array &out)
Definition utils.h:155
-
mlx::core::enable_for_arrays_t
typename std::enable_if_t< is_arrays_v< T... > > enable_for_arrays_t
Definition array.h:630
+
mlx::core::enable_for_arrays_t
typename std::enable_if_t< is_arrays_v< T... > > enable_for_arrays_t
Definition array.h:615
mlx::core::ContiguousIterator::loc
int64_t loc
Definition utils.h:126
mlx::core::ContiguousIterator::ContiguousIterator
ContiguousIterator()
Definition utils.h:104
mlx::core::ContiguousIterator::ContiguousIterator
ContiguousIterator(const Shape &shape, const Strides &strides, int dims)
Definition utils.h:114
@@ -336,8 +326,7 @@ $(function(){initNavTree('backend_2common_2utils_8h_source.html',''); initResiza
mlx::core::ContiguousIterator::step
void step()
Definition utils.h:74
mlx::core::ContiguousIterator::seek
void seek(int64_t n)
Definition utils.h:89
mlx::core::ContiguousIterator::reset
void reset()
Definition utils.h:99
-
mlx::core::array::Flags
Definition array.h:225
-
mlx::core::array::Flags::row_contiguous
bool row_contiguous
Definition array.h:237
+
mlx::core::array::Flags::row_contiguous
bool row_contiguous
Definition array.h:244
diff --git a/docs/build/html/backend_2metal_2device_8h_source.html b/docs/build/html/backend_2metal_2device_8h_source.html index 1e3401fba..e3e09e3cd 100644 --- a/docs/build/html/backend_2metal_2device_8h_source.html +++ b/docs/build/html/backend_2metal_2device_8h_source.html @@ -178,7 +178,7 @@ $(function(){initNavTree('backend_2metal_2device_8h_source.html',''); initResiza
62
63 void set_input_array(const array& a, int idx, int64_t offset = 0);
64 void set_output_array(array& a, int idx, int64_t offset = 0);
-
65 void register_output_array(array& a);
+
65 void register_output_array(const array& a);
66 void dispatch_threadgroups(MTL::Size grid_dims, MTL::Size group_dims);
67 void dispatch_threads(MTL::Size grid_dims, MTL::Size group_dims);
68 void maybeInsertBarrier();
@@ -472,6 +472,7 @@ $(function(){initNavTree('backend_2metal_2device_8h_source.html',''); initResiza
mlx::core::metal::CommandEncoder
Definition device.h:43
mlx::core::metal::CommandEncoder::dispatch_threads
void dispatch_threads(MTL::Size grid_dims, MTL::Size group_dims)
mlx::core::metal::CommandEncoder::inputs
std::unordered_set< const void * > & inputs()
Definition device.h:108
+
mlx::core::metal::CommandEncoder::register_output_array
void register_output_array(const array &a)
mlx::core::metal::CommandEncoder::operator=
CommandEncoder & operator=(const CommandEncoder &)=delete
mlx::core::metal::CommandEncoder::start_concurrent
ConcurrentContext start_concurrent()
Definition device.h:102
mlx::core::metal::CommandEncoder::set_vector_bytes
void set_vector_bytes(const std::vector< T > &vec, size_t nelems, int idx)
Definition device.h:84
@@ -487,7 +488,6 @@ $(function(){initNavTree('backend_2metal_2device_8h_source.html',''); initResiza
mlx::core::metal::CommandEncoder::set_bytes
void set_bytes(const T &v, int idx)
Definition device.h:98
mlx::core::metal::CommandEncoder::CommandEncoder
CommandEncoder(const CommandEncoder &)=delete
-
mlx::core::metal::CommandEncoder::set_buffer
void set_buffer(const MTL::Buffer *buf, int idx, int64_t offset=0)
mlx::core::metal::CommandEncoder::update_fence
void update_fence(MTL::Fence *fence)
Definition device.h:79
mlx::core::metal::CommandEncoder::outputs
std::unordered_set< const void * > outputs()
Definition device.h:113
diff --git a/docs/build/html/backend_2metal_2event_8h.js b/docs/build/html/backend_2metal_2event_8h.js deleted file mode 100644 index e2170ce94..000000000 --- a/docs/build/html/backend_2metal_2event_8h.js +++ /dev/null @@ -1,5 +0,0 @@ -var backend_2metal_2event_8h = -[ - [ "mlx::core::encode_signal", "namespacemlx_1_1core.html#a6d452306f0f046a7d021bd94f8713a89", null ], - [ "mlx::core::encode_wait", "namespacemlx_1_1core.html#a2874ba55b73057b76c23a7429fdd2d6e", null ] -]; \ No newline at end of file diff --git a/docs/build/html/backend_2metal_2utils_8h.html b/docs/build/html/backend_2metal_2utils_8h.html index ac6674994..200f869bc 100644 --- a/docs/build/html/backend_2metal_2utils_8h.html +++ b/docs/build/html/backend_2metal_2utils_8h.html @@ -147,9 +147,6 @@ Functions - - -

Namespaces

 
bool mlx::core::is_donatable (const array &in, const array &out)
 
void mlx::core::move_or_copy (const array &in, array &out)
 
void mlx::core::move_or_copy (const array &in, array &out, const Strides &strides, array::Flags flags, size_t data_size, size_t offset=0)
 
std::pair< bool, Strides > mlx::core::prepare_reshape (const array &in, const array &out)
 
void mlx::core::shared_buffer_reshape (const array &in, const Strides &out_strides, array &out)
template<typename T, typename... Args>
void mlx::core::concatenate (std::string &acc, T first, Args... args)
 
array mlx::core::unsafe_weak_copy (const array &x)
 Get a new array that refers to the same data but has a non-owning pointer to them.
 
diff --git a/docs/build/html/backend_2metal_2utils_8h.js b/docs/build/html/backend_2metal_2utils_8h.js index bc0d55b36..b67a9d3f9 100644 --- a/docs/build/html/backend_2metal_2utils_8h.js +++ b/docs/build/html/backend_2metal_2utils_8h.js @@ -10,6 +10,5 @@ var backend_2metal_2utils_8h = [ "mlx::core::get_primitive_string", "namespacemlx_1_1core.html#ad4be35b310a252edd80d9cf04f094a60", null ], [ "mlx::core::make_string", "namespacemlx_1_1core.html#aed148d95e7b5221f1312473deded0d27", null ], [ "mlx::core::type_to_name", "namespacemlx_1_1core.html#af1fdfdaa5644394362e6baba30701bae", null ], - [ "mlx::core::type_to_name", "namespacemlx_1_1core.html#aef60e3a8d9c987c9c338b193673d2164", null ], - [ "mlx::core::unsafe_weak_copy", "namespacemlx_1_1core.html#a357f4172305d2021bde8cf07d99adb7d", null ] + [ "mlx::core::type_to_name", "namespacemlx_1_1core.html#aef60e3a8d9c987c9c338b193673d2164", null ] ]; \ No newline at end of file diff --git a/docs/build/html/backend_2metal_2utils_8h_source.html b/docs/build/html/backend_2metal_2utils_8h_source.html index 8b09f8ba0..2567c0a28 100644 --- a/docs/build/html/backend_2metal_2utils_8h_source.html +++ b/docs/build/html/backend_2metal_2utils_8h_source.html @@ -185,35 +185,15 @@ $(function(){initNavTree('backend_2metal_2utils_8h_source.html',''); initResizab
69 concatenate(acc, args...);
70}
-
71
-
-
76inline array unsafe_weak_copy(const array& x) {
-
77 return array(
-
78 x.buffer(),
-
79 x.shape(),
-
80 x.dtype(),
-
81 x.strides(),
-
82 x.data_size(),
-
83 x.flags(),
-
84 [](auto b) {});
-
85}
-
-
86
-
87} // namespace mlx::core
+
71
+
72} // namespace mlx::core
mlx::core::Primitive
Definition primitives.h:48
mlx::core::Primitive::print
virtual void print(std::ostream &os)=0
Print the primitive.
mlx::core::array
Definition array.h:24
-
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:318
-
mlx::core::array::shape
const Shape & shape() const
The shape of the array as a vector of integers.
Definition array.h:103
-
mlx::core::array::strides
const Strides & strides() const
The strides of the array.
Definition array.h:117
-
mlx::core::array::buffer
allocator::Buffer & buffer()
Definition array.h:336
-
mlx::core::array::dtype
Dtype dtype() const
Get the arrays data type.
Definition array.h:131
-
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:332
mlx::core
Definition allocator.h:7
mlx::core::get_block_dims
MTL::Size get_block_dims(int dim0, int dim1, int dim2, int pow2=10)
-
mlx::core::unsafe_weak_copy
array unsafe_weak_copy(const array &x)
Get a new array that refers to the same data but has a non-owning pointer to them.
Definition utils.h:76
mlx::core::debug_set_primitive_buffer_label
void debug_set_primitive_buffer_label(MTL::CommandBuffer *command_buffer, Primitive &primitive)
Definition utils.h:46
mlx::core::Shape
std::vector< ShapeElem > Shape
Definition array.h:21
mlx::core::concatenate
void concatenate(std::string &acc, T first)
Definition utils.h:62
diff --git a/docs/build/html/classes.html b/docs/build/html/classes.html index 9ed2c8f37..2f916eb16 100644 --- a/docs/build/html/classes.html +++ b/docs/build/html/classes.html @@ -109,13 +109,13 @@ $(function(){initNavTree('classes.html',''); initResizable(true); });
A
-
Abs
Abs (mlx::core)
Abs (mlx::core::detail)
AccumHelper (mlx::steel)
Add
Add (mlx::core)
Add (mlx::core::detail)
add_vec (pocketfft::detail)
add_vec< cmplx< T > > (pocketfft::detail)
AddMM (mlx::core)
AffineQuantize (mlx::core::fast)
aligned_allocator (pocketfft::detail::threading)
AllGather (mlx::core::distributed)
Allocator (mlx::core::allocator)
AllReduce (mlx::core::distributed)
And
Arange (mlx::core)
ArcCos
ArcCos (mlx::core)
ArcCos (mlx::core::detail)
ArcCosh
ArcCosh (mlx::core)
ArcCosh (mlx::core::detail)
ArcSin
ArcSin (mlx::core)
ArcSin (mlx::core::detail)
ArcSinh
ArcSinh (mlx::core)
ArcSinh (mlx::core::detail)
ArcTan
ArcTan (mlx::core)
ArcTan (mlx::core::detail)
ArcTan2
ArcTan2 (mlx::core)
ArcTan2 (mlx::core::detail)
ArcTanh
ArcTanh (mlx::core)
ArcTanh (mlx::core::detail)
ArgPartition (mlx::core)
ArgReduce (mlx::core)
ArgSort (mlx::core)
arr (pocketfft::detail)
arr_info (pocketfft::detail)
array (mlx::core)
array::ArrayIterator (mlx::core)
AsStrided (mlx::core)
AsType (mlx::core)
AttnParams (mlx::steel)
+
Abs
Abs (mlx::core)
Abs (mlx::core::detail)
AccumHelper (mlx::steel)
Add
Add (mlx::core)
Add (mlx::core::detail)
add_vec (pocketfft::detail)
add_vec< cmplx< T > > (pocketfft::detail)
AddMM (mlx::core)
AffineQuantize (mlx::core::fast)
aligned_allocator (pocketfft::detail::threading)
AllGather (mlx::core::distributed)
Allocator (mlx::core::allocator)
AllReduce (mlx::core::distributed)
And
Arange (mlx::core)
ArcCos
ArcCos (mlx::core)
ArcCos (mlx::core::detail)
ArcCosh
ArcCosh (mlx::core)
ArcCosh (mlx::core::detail)
ArcSin
ArcSin (mlx::core)
ArcSin (mlx::core::detail)
ArcSinh
ArcSinh (mlx::core)
ArcSinh (mlx::core::detail)
ArcTan
ArcTan (mlx::core)
ArcTan (mlx::core::detail)
ArcTan2
ArcTan2 (mlx::core)
ArcTan2 (mlx::core::detail)
ArcTanh
ArcTanh (mlx::core)
ArcTanh (mlx::core::detail)
ArgPartition (mlx::core)
ArgReduce (mlx::core)
ArgSort (mlx::core)
arr (pocketfft::detail)
arr_info (pocketfft::detail)
array (mlx::core)
array::ArrayIterator (mlx::core)
AsStrided (mlx::core)
AsType (mlx::core)
AttnMaskParams (mlx::steel)
AttnParams (mlx::steel)
B
BaseMMAFrag (mlx::steel)
BaseMMAFrag< T, 8, 8 > (mlx::steel)
_MLX_BFloat16::bits_to_bfloat_struct
BitwiseAnd
BitwiseAnd (mlx::core::detail)
BitwiseBinary (mlx::core)
BitwiseInvert
BitwiseInvert (mlx::core)
BitwiseInvert (mlx::core::detail)
BitwiseOr
BitwiseOr (mlx::core::detail)
BitwiseXor
BitwiseXor (mlx::core::detail)
BlockLoader (mlx::steel)
BlockLoaderT (mlx::steel)
BlockMaskedMM (mlx::core)
BlockMergeSort
BlockMMA (mlx::steel)
BlockSwizzle (mlx::steel)
bool4_or_uint
Broadcast (mlx::core)
BroadcastAxes (mlx::core)
Buffer (mlx::core::allocator)
Buffer (mlx::core::metal)
C
-
Ceil
Ceil (mlx::core)
Ceil (mlx::core::detail)
cfftp (pocketfft::detail)
ChannelHelper (mlx::steel)
ChannelHelper< 1 > (mlx::steel)
ChannelHelper< 2 > (mlx::steel)
ChannelHelper< 3 > (mlx::steel)
ChannelHelper< 4 > (mlx::steel)
Cholesky (mlx::core)
cmplx (pocketfft::detail)
cndarr (pocketfft::detail)
CommandEncoder (mlx::core)
CommandEncoder (mlx::core::metal)
CommonAllocator (mlx::core::allocator)
Compiled (mlx::core)
complex128_t (mlx::core)
complex64_t
complex64_t (mlx::core)
Concatenate (mlx::core)
concurrent_queue (pocketfft::detail::threading)
CommandEncoder::ConcurrentContext (mlx::core)
CommandEncoder::ConcurrentContext (mlx::core::metal)
ConditionalType
ConditionalType< true, T, U >
Conjugate
Conjugate (mlx::core)
Conjugate (mlx::core::detail)
Contiguous (mlx::core)
ContiguousIterator (mlx::core)
Conv2DGeneralBaseInfo (mlx::steel)
Conv2DGeneralJumpParams (mlx::steel)
Conv2DInputBlockLoaderGeneral (mlx::steel)
Conv2DInputBlockLoaderLargeFilter (mlx::steel)
Conv2DInputBlockLoaderSmallChannels (mlx::steel)
Conv2DInputBlockLoaderSmallFilter (mlx::steel)
Conv2DWeightBlockLoader (mlx::steel)
Conv2DWeightBlockLoaderGeneral (mlx::steel)
Conv2DWeightBlockLoaderSmallChannels (mlx::steel)
Convolution (mlx::core)
Copy (mlx::core)
Cos
Cos (mlx::core)
Cos (mlx::core::detail)
Cosh
Cosh (mlx::core)
Cosh (mlx::core::detail)
CShape (mlx::steel)
CumMax
CumMin
CumProd
CumProd< bool >
CumSum
Custom (mlx::core::fast)
CustomKernel (mlx::core::fast)
CustomKernelShapeInfo (mlx::core::fast)
CustomTransforms (mlx::core)
+
Ceil
Ceil (mlx::core)
Ceil (mlx::core::detail)
cfftp (pocketfft::detail)
ChannelHelper (mlx::steel)
ChannelHelper< 1 > (mlx::steel)
ChannelHelper< 2 > (mlx::steel)
ChannelHelper< 3 > (mlx::steel)
ChannelHelper< 4 > (mlx::steel)
Cholesky (mlx::core)
cmplx (pocketfft::detail)
cndarr (pocketfft::detail)
CommandEncoder (mlx::core)
CommandEncoder (mlx::core::cpu)
CommandEncoder (mlx::core::metal)
CommonAllocator (mlx::core::allocator)
Compiled (mlx::core)
complex128_t (mlx::core)
complex64_t
complex64_t (mlx::core)
Concatenate (mlx::core)
concurrent_queue (pocketfft::detail::threading)
CommandEncoder::ConcurrentContext (mlx::core)
CommandEncoder::ConcurrentContext (mlx::core::metal)
ConditionalType
ConditionalType< true, T, U >
Conjugate
Conjugate (mlx::core)
Conjugate (mlx::core::detail)
Contiguous (mlx::core)
ContiguousIterator (mlx::core)
Conv2DGeneralBaseInfo (mlx::steel)
Conv2DGeneralJumpParams (mlx::steel)
Conv2DInputBlockLoaderGeneral (mlx::steel)
Conv2DInputBlockLoaderLargeFilter (mlx::steel)
Conv2DInputBlockLoaderSmallChannels (mlx::steel)
Conv2DInputBlockLoaderSmallFilter (mlx::steel)
Conv2DWeightBlockLoader (mlx::steel)
Conv2DWeightBlockLoaderGeneral (mlx::steel)
Conv2DWeightBlockLoaderSmallChannels (mlx::steel)
Convolution (mlx::core)
Copy (mlx::core)
Cos
Cos (mlx::core)
Cos (mlx::core::detail)
Cosh
Cosh (mlx::core)
Cosh (mlx::core::detail)
CShape (mlx::steel)
CumMax
CumMin
CumProd
CumProd< bool >
CumSum
Custom (mlx::core::fast)
CustomKernel (mlx::core::fast)
CustomKernelShapeInfo (mlx::core::fast)
CustomTransforms (mlx::core)
D
array::Data (mlx::core)
Depends (mlx::core)
Device (mlx::core)
Device (mlx::core::metal)
DeviceStream (mlx::core::metal)
DistPrimitive (mlx::core::distributed)
Divide
Divide (mlx::core::detail)
Divide (mlx::core)
DivMod
DivMod (mlx::core)
DivOp
Dtype (mlx::core)
DynamicSlice (mlx::core)
DynamicSliceUpdate (mlx::core)
diff --git a/docs/build/html/classmlx_1_1core_1_1_event-members.html b/docs/build/html/classmlx_1_1core_1_1_event-members.html index d55e6a71e..aeb61c819 100644 --- a/docs/build/html/classmlx_1_1core_1_1_event-members.html +++ b/docs/build/html/classmlx_1_1core_1_1_event-members.html @@ -108,16 +108,17 @@ $(function(){initNavTree('classmlx_1_1core_1_1_event.html',''); initResizable(tr

This is the complete list of members for mlx::core::Event, including all inherited members.

- - + + - - - + + + +
Event()=defaultmlx::core::Event
Event(const Stream &steam)mlx::core::Event
Event()mlx::core::Eventinline
Event(Stream stream)mlx::core::Eventexplicit
is_signaled() constmlx::core::Event
raw_event() constmlx::core::Eventinline
set_value(uint64_t v)mlx::core::Eventinline
signal()mlx::core::Event
set_value(uint64_t v)mlx::core::Eventinline
signal()mlx::core::Event
signal(Stream stream)mlx::core::Event
stream() constmlx::core::Eventinline
valid() constmlx::core::Eventinline
value() constmlx::core::Eventinline
wait()mlx::core::Event
wait(Stream stream)mlx::core::Event
diff --git a/docs/build/html/classmlx_1_1core_1_1_event.html b/docs/build/html/classmlx_1_1core_1_1_event.html index 19634f0b1..f058182d8 100644 --- a/docs/build/html/classmlx_1_1core_1_1_event.html +++ b/docs/build/html/classmlx_1_1core_1_1_event.html @@ -113,14 +113,18 @@ $(function(){initNavTree('classmlx_1_1core_1_1_event.html',''); initResizable(tr - - - - + + + + + + + + @@ -131,12 +135,10 @@ Public Member Functions - -

Public Member Functions

 Event ()=default
 
 Event (const Stream &steam)
 
 Event ()
 
 Event (Stream stream)
 
void wait ()
 
void signal ()
 
void wait (Stream stream)
 
void signal (Stream stream)
 
bool is_signaled () const
 
bool valid () const
 
const Stream & stream () const
 
const std::shared_ptr< void > & raw_event () const
 

Constructor & Destructor Documentation

- -

◆ Event() [1/2]

+ +

◆ Event() [1/2]

@@ -153,26 +155,34 @@ Public Member Functions -default +inline
- -

◆ Event() [2/2]

+ +

◆ Event() [2/2]

+ + + + + +
- +
mlx::core::Event::Event (const Stream & steam)Stream stream)
+ 		+explicit
@@ -193,31 +203,6 @@ Public Member Functions
-
-
- -

◆ raw_event()

- -
-
- - - - - -
- - - - - - - -
const std::shared_ptr< void > & mlx::core::Event::raw_event () const
- 		-inline
-
-
@@ -246,7 +231,7 @@ Public Member Functions
-

◆ signal()

+

◆ signal() [1/2]

@@ -260,6 +245,23 @@ Public Member Functions
+
+
+ +

◆ signal() [2/2]

+ +
+
+ + + + + + + +
void mlx::core::Event::signal (Stream stream)
+
+
@@ -338,7 +340,7 @@ Public Member Functions
-

◆ wait()

+

◆ wait() [1/2]

@@ -352,6 +354,23 @@ Public Member Functions
+
+
+ +

◆ wait() [2/2]

+ +
+
+ + + + + + + +
void mlx::core::Event::wait (Stream stream)
+
+
The documentation for this class was generated from the following file:
    diff --git a/docs/build/html/classmlx_1_1core_1_1_event.js b/docs/build/html/classmlx_1_1core_1_1_event.js index 924cdc8ad..dc4288d3a 100644 --- a/docs/build/html/classmlx_1_1core_1_1_event.js +++ b/docs/build/html/classmlx_1_1core_1_1_event.js @@ -1,13 +1,14 @@ var classmlx_1_1core_1_1_event = [ - [ "Event", "classmlx_1_1core_1_1_event.html#a833506419b2110ad1abd89b2dd238b4d", null ], - [ "Event", "classmlx_1_1core_1_1_event.html#a13e4835f2ffb2cc22e29148a448ea184", null ], + [ "Event", "classmlx_1_1core_1_1_event.html#a98f1f98d6cac43ddb682522acdce63d5", null ], + [ "Event", "classmlx_1_1core_1_1_event.html#acdc48fc71fcf3f8d128be029d63b7826", null ], [ "is_signaled", "classmlx_1_1core_1_1_event.html#a05a9a3de88185b4a89e154242b4e770a", null ], - [ "raw_event", "classmlx_1_1core_1_1_event.html#af408d30df17c4771e9e2aa550cb6e921", null ], [ "set_value", "classmlx_1_1core_1_1_event.html#a0d077b11f4b28f882b42440b7ac6d40d", null ], [ "signal", "classmlx_1_1core_1_1_event.html#a65a858445506a61be5889ae0e3651b89", null ], + [ "signal", "classmlx_1_1core_1_1_event.html#ab514bd9e9c21d1fdd7c1460dc7d0ec7f", null ], [ "stream", "classmlx_1_1core_1_1_event.html#a193143bad31b68c699fa27f135b45614", null ], [ "valid", "classmlx_1_1core_1_1_event.html#aa77afd9669e2ef9d5e9ae1c2c6fd24fa", null ], [ "value", "classmlx_1_1core_1_1_event.html#ab71c7baee3d1d02ad6a2001bbf90b970", null ], - [ "wait", "classmlx_1_1core_1_1_event.html#a634afd918e6ed847f354531ba9f48252", null ] + [ "wait", "classmlx_1_1core_1_1_event.html#a634afd918e6ed847f354531ba9f48252", null ], + [ "wait", "classmlx_1_1core_1_1_event.html#ac58282a36a02aed7a5bd59b1602d11a8", null ] ]; \ No newline at end of file diff --git a/docs/build/html/classmlx_1_1core_1_1_fence-members.html b/docs/build/html/classmlx_1_1core_1_1_fence-members.html index b34cc2219..04b89ac52 100644 --- a/docs/build/html/classmlx_1_1core_1_1_fence-members.html +++ b/docs/build/html/classmlx_1_1core_1_1_fence-members.html @@ -108,11 +108,10 @@ $(function(){initNavTree('classmlx_1_1core_1_1_fence.html',''); initResizable(tr

    This is the complete list of members for mlx::core::Fence, including all inherited members.

    - - - - - + + + +
    Fence(const Stream &stream)mlx::core::Fence
    update()mlx::core::Fence
    update_gpu(const array &x)mlx::core::Fence
    wait()mlx::core::Fence
    wait_gpu(array &x)mlx::core::Fence
    Fence()mlx::core::Fenceinline
    Fence(Stream stream)mlx::core::Fenceexplicit
    update(Stream stream, const array &x)mlx::core::Fence
    wait(Stream stream, const array &x)mlx::core::Fence
diff --git a/docs/build/html/classmlx_1_1core_1_1_fence.html b/docs/build/html/classmlx_1_1core_1_1_fence.html index a1408c747..ff96358c6 100644 --- a/docs/build/html/classmlx_1_1core_1_1_fence.html +++ b/docs/build/html/classmlx_1_1core_1_1_fence.html @@ -113,38 +113,69 @@ $(function(){initNavTree('classmlx_1_1core_1_1_fence.html',''); initResizable(tr - - - - - - - - - - + + + + + + + +

Public Member Functions

 Fence (const Stream &stream)
 
void update_gpu (const array &x)
 
void wait_gpu (array &x)
 
void wait ()
 
void update ()
 
 Fence ()
 
 Fence (Stream stream)
 
void update (Stream stream, const array &x)
 
void wait (Stream stream, const array &x)
 

Constructor & Destructor Documentation

- -

◆ Fence()

+ +

◆ Fence() [1/2]

+ + + + + +
- +
mlx::core::Fence::Fence (const Stream & stream))
+ 		+inline
+
+ +
+
+ +

◆ Fence() [2/2]

+ +
+
+ + + + + +
+ + + + + + + +
mlx::core::Fence::Fence (Stream stream)
+ 		+explicit

Member Function Documentation

- -

◆ update()

+ +

◆ update()

@@ -152,33 +183,20 @@ Public Member Functions void mlx::core::Fence::update ( - ) - + Stream stream, - -
- -
-
- -

◆ update_gpu()

- -
-
- - - - + +
void mlx::core::Fence::update_gpu (const array & x) const array & x )
- -

◆ wait()

+ +

◆ wait()

@@ -186,25 +204,12 @@ Public Member Functions void mlx::core::Fence::wait ( - ) - + Stream stream, - -
- -
-
- -

◆ wait_gpu()

- -
-
- - - - + +
void mlx::core::Fence::wait_gpu (array & x) const array & x )
@@ -212,7 +217,7 @@ Public Member Functions
The documentation for this class was generated from the following file:
diff --git a/docs/build/html/classmlx_1_1core_1_1_fence.js b/docs/build/html/classmlx_1_1core_1_1_fence.js index d4342d49e..06bd98467 100644 --- a/docs/build/html/classmlx_1_1core_1_1_fence.js +++ b/docs/build/html/classmlx_1_1core_1_1_fence.js @@ -1,8 +1,7 @@ var classmlx_1_1core_1_1_fence = [ - [ "Fence", "classmlx_1_1core_1_1_fence.html#a3e3ed08eb6a1025b051b5a435f6f95f7", null ], - [ "update", "classmlx_1_1core_1_1_fence.html#a653279d4023d69751a930a91d3bf010a", null ], - [ "update_gpu", "classmlx_1_1core_1_1_fence.html#a6c5652aad6e93b06c72258bb8d9c19fc", null ], - [ "wait", "classmlx_1_1core_1_1_fence.html#a1ccbe354d043e6c4d76286c6635a38e2", null ], - [ "wait_gpu", "classmlx_1_1core_1_1_fence.html#ab6d783dee02656ebb8ffcbbfa6de5b53", null ] + [ "Fence", "classmlx_1_1core_1_1_fence.html#aeb09655b3ef4db12810defebdbbdac33", null ], + [ "Fence", "classmlx_1_1core_1_1_fence.html#a7cabe72d8b165344ff9f7118975b6214", null ], + [ "update", "classmlx_1_1core_1_1_fence.html#a19438c60b5e9c6f64529c8f0329ead13", null ], + [ "wait", "classmlx_1_1core_1_1_fence.html#a9d9bc0b57f741577a34f8dfd3b1de8f2", null ] ]; \ No newline at end of file diff --git a/docs/build/html/classmlx_1_1core_1_1array-members.html b/docs/build/html/classmlx_1_1core_1_1array-members.html index 091d2d41a..a46519ca2 100644 --- a/docs/build/html/classmlx_1_1core_1_1array-members.html +++ b/docs/build/html/classmlx_1_1core_1_1array-members.html @@ -119,20 +119,20 @@ $(function(){initNavTree('classmlx_1_1core_1_1array.html',''); initResizable(tru array(const array &other)=defaultmlx::core::array array(array &&other)=defaultmlx::core::array array(Shape shape, Dtype dtype, std::shared_ptr< Primitive > primitive, std::vector< array > inputs)mlx::core::array - array(allocator::Buffer data, Shape shape, Dtype dtype, Strides strides, size_t data_size, Flags flags, Deleter deleter=allocator::free)mlx::core::arrayexplicit - attach_event(Event e) constmlx::core::arrayinline - available enum valuemlx::core::array - begin() constmlx::core::arrayinline - buffer()mlx::core::arrayinline - buffer() constmlx::core::arrayinline - buffer_size() constmlx::core::arrayinline - copy_shared_buffer(const array &other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)mlx::core::array - copy_shared_buffer(const array &other)mlx::core::array - data()mlx::core::arrayinline - data() constmlx::core::arrayinline - data_shared_ptr() constmlx::core::arrayinline - data_size() constmlx::core::arrayinline - detach()mlx::core::array + attach_event(Event e) constmlx::core::arrayinline + available enum valuemlx::core::array + begin() constmlx::core::arrayinline + buffer()mlx::core::arrayinline + buffer() constmlx::core::arrayinline + buffer_size() constmlx::core::arrayinline + copy_shared_buffer(const array &other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)mlx::core::array + copy_shared_buffer(const array &other)mlx::core::array + data()mlx::core::arrayinline + data() constmlx::core::arrayinline + data_shared_ptr() constmlx::core::arrayinline + data_size() constmlx::core::arrayinline + detach()mlx::core::array + detach_event() constmlx::core::arrayinline dtype() constmlx::core::arrayinline end() constmlx::core::arrayinline eval()mlx::core::array @@ -150,8 +150,6 @@ $(function(){initNavTree('classmlx_1_1core_1_1array.html',''); initResizable(tru item() constmlx::core::array itemsize() constmlx::core::arrayinline make_arrays(std::vector< Shape > shapes, const std::vector< Dtype > &dtypes, const std::shared_ptr< Primitive > &primitive, const std::vector< array > &inputs)mlx::core::arraystatic - move_shared_buffer(array other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)mlx::core::array - move_shared_buffer(array other)mlx::core::array nbytes() constmlx::core::arrayinline ndim() constmlx::core::arrayinline operator=(const array &other) &&=deletemlx::core::array @@ -163,21 +161,21 @@ $(function(){initNavTree('classmlx_1_1core_1_1array.html',''); initResizable(tru primitive() constmlx::core::arrayinline primitive_id() constmlx::core::arrayinline primitive_ptr() constmlx::core::arrayinline - scheduled enum valuemlx::core::array - set_data(allocator::Buffer buffer, Deleter d=allocator::free)mlx::core::array - set_data(allocator::Buffer buffer, size_t data_size, Strides strides, Flags flags, Deleter d=allocator::free)mlx::core::array - set_siblings(std::vector< array > siblings, uint16_t position)mlx::core::arrayinline - set_status(Status s) constmlx::core::arrayinline - set_tracer(bool is_tracer)mlx::core::arrayinline - shape() constmlx::core::arrayinline - shape(int dim) constmlx::core::arrayinline - siblings() constmlx::core::arrayinline - siblings()mlx::core::arrayinline - size() constmlx::core::arrayinline - Status enum namemlx::core::array - status() constmlx::core::arrayinline - strides() constmlx::core::arrayinline - strides(int dim) constmlx::core::arrayinline + set_data(allocator::Buffer buffer, Deleter d=allocator::free)mlx::core::array + set_data(allocator::Buffer buffer, size_t data_size, Strides strides, Flags flags, Deleter d=allocator::free)mlx::core::array + set_siblings(std::vector< array > siblings, uint16_t position)mlx::core::arrayinline + set_status(Status s) constmlx::core::arrayinline + set_tracer(bool is_tracer)mlx::core::arrayinline + shape() constmlx::core::arrayinline + shape(int dim) constmlx::core::arrayinline + siblings() constmlx::core::arrayinline + siblings()mlx::core::arrayinline + size() constmlx::core::arrayinline + Status enum namemlx::core::array + status() constmlx::core::arrayinline + strides() constmlx::core::arrayinline + strides(int dim) constmlx::core::arrayinline + unsafe_weak_copy(const array &other)mlx::core::arraystatic unscheduled enum valuemlx::core::array wait()mlx::core::array ~array()mlx::core::array diff --git a/docs/build/html/classmlx_1_1core_1_1array.html b/docs/build/html/classmlx_1_1core_1_1array.html index b020815bb..4a033352b 100644 --- a/docs/build/html/classmlx_1_1core_1_1array.html +++ b/docs/build/html/classmlx_1_1core_1_1array.html @@ -126,7 +126,6 @@ Classes

Public Types

enum  Status { unscheduled -, scheduled , evaluated , available } @@ -219,9 +218,6 @@ Public Member Functions std::uintptr_t primitive_id () const  A unique identifier for an arrays primitive.
  - array (allocator::Buffer data, Shape shape, Dtype dtype, Strides strides, size_t data_size, Flags flags, Deleter deleter=allocator::free) - Build an array from all the info held by the array description.
-  Primitive & primitive () const  The array's primitive.
  @@ -285,6 +281,8 @@ Public Member Functions   void attach_event (Event e) const   +void detach_event () const +  void set_tracer (bool is_tracer)   bool is_tracer () const @@ -297,10 +295,6 @@ Public Member Functions   void copy_shared_buffer (const array &other)   -void move_shared_buffer (array other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0) -  -void move_shared_buffer (array other) -  void overwrite_descriptor (const array &other)    ~array () @@ -310,6 +304,9 @@ Public Member Functions Static Public Member Functions static std::vector< array > make_arrays (std::vector< Shape > shapes, const std::vector< Dtype > &dtypes, const std::shared_ptr< Primitive > &primitive, const std::vector< array > &inputs)   +static array unsafe_weak_copy (const array &other) + Get a new array that refers to the same data as the input but with a non-owning pointer to it.
+ 

Member Enumeration Documentation

@@ -325,7 +322,6 @@ Static Public Member Functions
-
Enumerator
unscheduled 
scheduled 
evaluated 
available 
@@ -334,7 +330,7 @@ Static Public Member Functions

Constructor & Destructor Documentation

-

◆ array() [1/12]

+

◆ array() [1/11]

@@ -367,7 +363,7 @@ template<typename T>
-

◆ array() [2/12]

+

◆ array() [2/11]

@@ -396,7 +392,7 @@ template<typename T>
-

◆ array() [3/12]

+

◆ array() [3/11]

@@ -432,7 +428,7 @@ template<typename It>
-

◆ array() [4/12]

+

◆ array() [4/11]

@@ -463,7 +459,7 @@ template<typename T>
-

◆ array() [5/12]

+

◆ array() [5/11]

@@ -488,7 +484,7 @@ template<typename T>
-

◆ array() [6/12]

+

◆ array() [6/11]

@@ -517,7 +513,7 @@ template<typename T>
-

◆ array() [7/12]

+

◆ array() [7/11]

@@ -553,7 +549,7 @@ template<typename T>
-

◆ array() [8/12]

+

◆ array() [8/11]

@@ -592,7 +588,7 @@ template<typename T>
-

◆ array() [9/12]

+

◆ array() [9/11]

@@ -617,7 +613,7 @@ template<typename T>
-

◆ array() [10/12]

+

◆ array() [10/11]

@@ -642,7 +638,7 @@ template<typename T>
-

◆ array() [11/12]

+

◆ array() [11/11]

@@ -673,63 +669,6 @@ template<typename T>

The following methods should be used with caution.

They are intended for use by the backend implementation and the API may change.

-
- - -

◆ array() [12/12]

- -
-
- - - - - -
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
mlx::core::array::array (allocator::Buffer data,
Shape shape,
Dtype dtype,
Strides strides,
size_t data_size,
Flags flags,
Deleter deleter = allocator::free )
- 		-explicit
-
- -

Build an array from all the info held by the array description.

-

Including the buffer, strides, flags.

-
@@ -1052,6 +991,31 @@ template<typename T>

Detach the array from the graph.

+ + + +

◆ detach_event()

+ +
+
+ + + + + +
+ + + + + + + +
void mlx::core::array::detach_event () const
+ 		+inline
+
+
@@ -1448,59 +1412,6 @@ template<typename T>
-
- - -

◆ move_shared_buffer() [1/2]

- -
-
- - - - - - - -
void mlx::core::array::move_shared_buffer (array other)
-
- -
-
- -

◆ move_shared_buffer() [2/2]

- -
-
- - - - - - - - - - - - - - - - - - - - - - - - - - -
void mlx::core::array::move_shared_buffer (array other,
const Strides & strides,
Flags flags,
size_t data_size,
size_t offset = 0 )
-
-
@@ -2145,6 +2056,34 @@ template<typename T>

Get the stride of the corresponding dimension.

This function supports negative indexing and provides bounds checking.

+ + + +

◆ unsafe_weak_copy()

+ +
+
+ + + + + +
+ + + + + + + +
static array mlx::core::array::unsafe_weak_copy (const array & other)
+ 		+static
+
+ +

Get a new array that refers to the same data as the input but with a non-owning pointer to it.

+

Note the array is detached from the graph and has no inputs, siblings or primitive.

+
diff --git a/docs/build/html/classmlx_1_1core_1_1array.js b/docs/build/html/classmlx_1_1core_1_1array.js index dc9be6583..c364bff6b 100644 --- a/docs/build/html/classmlx_1_1core_1_1array.js +++ b/docs/build/html/classmlx_1_1core_1_1array.js @@ -5,7 +5,6 @@ var classmlx_1_1core_1_1array = [ "Flags", "structmlx_1_1core_1_1array_1_1_flags.html", "structmlx_1_1core_1_1array_1_1_flags" ], [ "Status", "classmlx_1_1core_1_1array.html#a199726612fa8a4bcd5c2d05eadad7078", [ [ "unscheduled", "classmlx_1_1core_1_1array.html#a199726612fa8a4bcd5c2d05eadad7078ae8a9988458b0355001674020a45656fb", null ], - [ "scheduled", "classmlx_1_1core_1_1array.html#a199726612fa8a4bcd5c2d05eadad7078af8a6f8eed2395ab89a758dec434393ae", null ], [ "evaluated", "classmlx_1_1core_1_1array.html#a199726612fa8a4bcd5c2d05eadad7078a6fc3d7595445dd877584495f47535268", null ], [ "available", "classmlx_1_1core_1_1array.html#a199726612fa8a4bcd5c2d05eadad7078a308bd3e5bf976888b120dd36d0c2d2ae", null ] ] ], @@ -20,7 +19,6 @@ var classmlx_1_1core_1_1array = [ "array", "classmlx_1_1core_1_1array.html#a297df274e2da5cb884257bbeffd6b187", null ], [ "array", "classmlx_1_1core_1_1array.html#ab6cbccbba66cc54acda4390b19f0397c", null ], [ "array", "classmlx_1_1core_1_1array.html#abc26528271076510822e374d1668a94b", null ], - [ "array", "classmlx_1_1core_1_1array.html#a2476f987ec7a5afb7665d3b3974db0b2", null ], [ "~array", "classmlx_1_1core_1_1array.html#a2f16c1ef8ee248d2fba95520c86dfad2", null ], [ "attach_event", "classmlx_1_1core_1_1array.html#a000c3cfe13cb378bf0523b62816190da", null ], [ "begin", "classmlx_1_1core_1_1array.html#a76b258b169d7d73419ebbf85340fb914", null ], @@ -34,6 +32,7 @@ var classmlx_1_1core_1_1array = [ "data_shared_ptr", "classmlx_1_1core_1_1array.html#ab84c792117e29cdf90ef3433303f6141", null ], [ "data_size", "classmlx_1_1core_1_1array.html#afaf2a370fa35d96af1b27a4b814e3bfd", null ], [ "detach", "classmlx_1_1core_1_1array.html#a84948c29df8c957904919c8602692bd2", null ], + [ "detach_event", "classmlx_1_1core_1_1array.html#a9ff36a88bfd7c99a2662136ee9315f4e", null ], [ "dtype", "classmlx_1_1core_1_1array.html#ae29e7d6fbfbea1e5e321a8d1ea3cfacd", null ], [ "end", "classmlx_1_1core_1_1array.html#a5daf64552fb450825c9b382f3a5fa2d4", null ], [ "eval", "classmlx_1_1core_1_1array.html#a2820c45188071a22175e9fa42e10a49a", null ], @@ -50,8 +49,6 @@ var classmlx_1_1core_1_1array = [ "item", "classmlx_1_1core_1_1array.html#a8650a99a6b7549bc823b03ad92590ff7", null ], [ "itemsize", "classmlx_1_1core_1_1array.html#af329d9432c92de87cbaa2de8454eefc0", null ], [ "make_arrays", "classmlx_1_1core_1_1array.html#a45b1c9763fe921fe5880ca28316ae98c", null ], - [ "move_shared_buffer", "classmlx_1_1core_1_1array.html#a38d7ad605f8282e5e49d0c09e0555c78", null ], - [ "move_shared_buffer", "classmlx_1_1core_1_1array.html#ad41cc5e7aebfcad849ad15d697584cf8", null ], [ "nbytes", "classmlx_1_1core_1_1array.html#a387b67cd3ef5cfc1e749c371766c4a05", null ], [ "ndim", "classmlx_1_1core_1_1array.html#a53006e77d13d9d88b525ef577748939f", null ], [ "operator=", "classmlx_1_1core_1_1array.html#a5c89c2406a610b32943955f9a5060fbd", null ], @@ -76,5 +73,6 @@ var classmlx_1_1core_1_1array = [ "status", "classmlx_1_1core_1_1array.html#a7102659be87e9ef62966696ab9b07dad", null ], [ "strides", "classmlx_1_1core_1_1array.html#a28cf1928f5ec2f972a94ff1c0e71187d", null ], [ "strides", "classmlx_1_1core_1_1array.html#ac9bfc251a9937eaefbe7f8c5ffd304d1", null ], + [ "unsafe_weak_copy", "classmlx_1_1core_1_1array.html#a797ae8a1708a7c67d62e6c55c321d802", null ], [ "wait", "classmlx_1_1core_1_1array.html#a648592006f1c92287734ba2428eaa45e", null ] ]; \ No newline at end of file diff --git a/docs/build/html/classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl-members.html b/docs/build/html/classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl-members.html index dc6e1204a..4733b8101 100644 --- a/docs/build/html/classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl-members.html +++ b/docs/build/html/classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl-members.html @@ -108,11 +108,11 @@ $(function(){initNavTree('classmlx_1_1core_1_1distributed_1_1detail_1_1_group_im

This is the complete list of members for mlx::core::distributed::detail::GroupImpl, including all inherited members.

- - + + - - + + diff --git a/docs/build/html/classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html b/docs/build/html/classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html index b4785e760..a57280b56 100644 --- a/docs/build/html/classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html +++ b/docs/build/html/classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html @@ -124,14 +124,14 @@ Public Member Functions - - - - - - - - + + + + + + + +
all_gather(const array &input, array &output)=0mlx::core::distributed::detail::GroupImplpure virtual
all_sum(const array &input, array &output)=0mlx::core::distributed::detail::GroupImplpure virtual
all_gather(const array &input, array &output, Stream stream)=0mlx::core::distributed::detail::GroupImplpure virtual
all_sum(const array &input, array &output, Stream stream)=0mlx::core::distributed::detail::GroupImplpure virtual
rank()=0mlx::core::distributed::detail::GroupImplpure virtual
recv(array &out, int src)=0mlx::core::distributed::detail::GroupImplpure virtual
send(const array &input, int dst)=0mlx::core::distributed::detail::GroupImplpure virtual
recv(array &out, int src, Stream stream)=0mlx::core::distributed::detail::GroupImplpure virtual
send(const array &input, int dst, Stream stream)=0mlx::core::distributed::detail::GroupImplpure virtual
size()=0mlx::core::distributed::detail::GroupImplpure virtual
split(int color, int key=-1)=0mlx::core::distributed::detail::GroupImplpure virtual
~GroupImpl()mlx::core::distributed::detail::GroupImplinlinevirtual
 
virtual std::shared_ptr< GroupImpl > split (int color, int key=-1)=0
 
virtual void all_sum (const array &input, array &output)=0
 
virtual void all_gather (const array &input, array &output)=0
 
virtual void send (const array &input, int dst)=0
 
virtual void recv (array &out, int src)=0
 
virtual void all_sum (const array &input, array &output, Stream stream)=0
 
virtual void all_gather (const array &input, array &output, Stream stream)=0
 
virtual void send (const array &input, int dst, Stream stream)=0
 
virtual void recv (array &out, int src, Stream stream)=0
 

Detailed Description

Abstract base class of a distributed group implementation.

@@ -162,8 +162,8 @@ Public Member Functions

Member Function Documentation

- -

◆ all_gather()

+ +

◆ all_gather()

@@ -179,7 +179,12 @@ Public Member Functions - array & output ) + array & output, + + + + + Stream stream ) @@ -191,8 +196,8 @@ Public Member Functions
- -

◆ all_sum()

+ +

◆ all_sum()

@@ -208,7 +213,12 @@ Public Member Functions - array & output ) + array & output, + + + + + Stream stream ) @@ -245,8 +255,8 @@ Public Member Functions
- -

◆ recv()

+ +

◆ recv()

@@ -262,7 +272,12 @@ Public Member Functions - int src ) + int src, + + + + + Stream stream ) @@ -274,8 +289,8 @@ Public Member Functions
- -

◆ send()

+ +

◆ send()

@@ -291,7 +306,12 @@ Public Member Functions - int dst ) + int dst, + + + + + Stream stream ) diff --git a/docs/build/html/classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.js b/docs/build/html/classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.js index 870d3297e..b3ca20065 100644 --- a/docs/build/html/classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.js +++ b/docs/build/html/classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.js @@ -1,11 +1,11 @@ var classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl = [ [ "~GroupImpl", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html#a83f119b87210f53438c5ba675a78065e", null ], - [ "all_gather", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html#a04bb1df23abe5b1f3fa0126375c6cea4", null ], - [ "all_sum", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html#ae163a6f444c6cc8820288b20f294e483", null ], + [ "all_gather", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html#a65ae9485d2b1a2fd769744d50b0dd225", null ], + [ "all_sum", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html#a23f620ec55d75f236d5371e05a52fd64", null ], [ "rank", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html#ae0838a40ce58442cdc73d57d7969a702", null ], - [ "recv", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html#ac4af5fc16a82ba8c72df04d7694f8352", null ], - [ "send", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html#ac8472eb2f96d1b14c7e4ccef56268ba0", null ], + [ "recv", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html#a7ce5b7a19d0fb8e189986c84845c5898", null ], + [ "send", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html#a74befcdc600669cb87761106ae0bd9a5", null ], [ "size", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html#ab1c8044b05f185c4bcc53002d4587599", null ], [ "split", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html#a87800a23c8160933a2d77a55a959194d", null ] ]; \ No newline at end of file diff --git a/docs/build/html/classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention-members.html b/docs/build/html/classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention-members.html index 7f2bd75b6..347eb20db 100644 --- a/docs/build/html/classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention-members.html +++ b/docs/build/html/classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention-members.html @@ -124,7 +124,7 @@ $(function(){initNavTree('classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attent Primitive(const Primitive &other)=deletemlx::core::Primitive Primitive(Primitive &&other)=deletemlx::core::Primitive print(std::ostream &os)=0mlx::core::Primitivepure virtual - ScaledDotProductAttention(Stream stream, std::function< std::vector< array >(std::vector< array >)> fallback, const float scale)mlx::core::fast::ScaledDotProductAttentioninlineexplicit + ScaledDotProductAttention(Stream stream, std::function< std::vector< array >(std::vector< array >)> fallback, const float scale, const bool do_causal)mlx::core::fast::ScaledDotProductAttentioninlineexplicit stream()mlx::core::Primitiveinline vjp(const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs) overridemlx::core::fast::Customvirtual vmap(const std::vector< array > &inputs, const std::vector< int > &axes) overridemlx::core::fast::Customvirtual diff --git a/docs/build/html/classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.html b/docs/build/html/classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.html index 544d88762..49fdf1728 100644 --- a/docs/build/html/classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.html +++ b/docs/build/html/classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.html @@ -123,8 +123,8 @@ Inheritance diagram for mlx::core::fast::ScaledDotProductAttention:
- - + + @@ -178,8 +178,8 @@ Public Member Functions

Public Member Functions

 ScaledDotProductAttention (Stream stream, std::function< std::vector< array >(std::vector< array >)> fallback, const float scale)
 
 ScaledDotProductAttention (Stream stream, std::function< std::vector< array >(std::vector< array >)> fallback, const float scale, const bool do_causal)
 
void eval_cpu (const std::vector< array > &inputs, std::vector< array > &outputs) override
 A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the output arrays.
 
 

Constructor & Destructor Documentation

- -

◆ ScaledDotProductAttention()

+ +

◆ ScaledDotProductAttention()

@@ -200,7 +200,12 @@ Public Member Functions - const float scale ) + const float scale, + + + + + const bool do_causal ) diff --git a/docs/build/html/classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.js b/docs/build/html/classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.js index 85665e2e5..c0dd43cd3 100644 --- a/docs/build/html/classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.js +++ b/docs/build/html/classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.js @@ -1,6 +1,6 @@ var classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention = [ - [ "ScaledDotProductAttention", "classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.html#ab3f78d30e5bb3e76cfe701f2358e4748", null ], + [ "ScaledDotProductAttention", "classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.html#a09c99b460cca606b2ebb22f90b3d13a2", null ], [ "DEFINE_INPUT_OUTPUT_SHAPE", "classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.html#a64d2ce4b46b529a6a9ef068947bc623e", null ], [ "DEFINE_PRINT", "classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.html#a6cc2092fa5b8e7585921b8e0f3ec3db7", null ], [ "eval_cpu", "classmlx_1_1core_1_1fast_1_1_scaled_dot_product_attention.html#ae20851e002f7fcb6d4f97817596f6328", null ], diff --git a/docs/build/html/classmlx_1_1core_1_1io_1_1_file_writer.html b/docs/build/html/classmlx_1_1core_1_1io_1_1_file_writer.html index f14504dc8..5eb23ed90 100644 --- a/docs/build/html/classmlx_1_1core_1_1io_1_1_file_writer.html +++ b/docs/build/html/classmlx_1_1core_1_1io_1_1_file_writer.html @@ -109,7 +109,7 @@ $(function(){initNavTree('classmlx_1_1core_1_1io_1_1_file_writer.html',''); init
-

#include <load.h>

+

#include <load.h>

Inheritance diagram for mlx::core::io::FileWriter:
@@ -446,7 +446,7 @@ Public Member Functions
The documentation for this class was generated from the following file:
diff --git a/docs/build/html/classmlx_1_1core_1_1io_1_1_parallel_file_reader.html b/docs/build/html/classmlx_1_1core_1_1io_1_1_parallel_file_reader.html index b29c4f35c..ed8a6956d 100644 --- a/docs/build/html/classmlx_1_1core_1_1io_1_1_parallel_file_reader.html +++ b/docs/build/html/classmlx_1_1core_1_1io_1_1_parallel_file_reader.html @@ -109,7 +109,7 @@ $(function(){initNavTree('classmlx_1_1core_1_1io_1_1_parallel_file_reader.html',
-

#include <load.h>

+

#include <load.h>

Inheritance diagram for mlx::core::io::ParallelFileReader:
@@ -403,7 +403,7 @@ Public Member Functions
The documentation for this class was generated from the following file: diff --git a/docs/build/html/classmlx_1_1core_1_1io_1_1_reader.html b/docs/build/html/classmlx_1_1core_1_1io_1_1_reader.html index bf6ff736a..be1e31276 100644 --- a/docs/build/html/classmlx_1_1core_1_1io_1_1_reader.html +++ b/docs/build/html/classmlx_1_1core_1_1io_1_1_reader.html @@ -109,7 +109,7 @@ $(function(){initNavTree('classmlx_1_1core_1_1io_1_1_reader.html',''); initResiz
-

#include <load.h>

+

#include <load.h>

Inheritance diagram for mlx::core::io::Reader:
@@ -373,7 +373,7 @@ Public Member Functions
The documentation for this class was generated from the following file: diff --git a/docs/build/html/classmlx_1_1core_1_1io_1_1_writer.html b/docs/build/html/classmlx_1_1core_1_1io_1_1_writer.html index daf1e3626..a87cb24da 100644 --- a/docs/build/html/classmlx_1_1core_1_1io_1_1_writer.html +++ b/docs/build/html/classmlx_1_1core_1_1io_1_1_writer.html @@ -109,7 +109,7 @@ $(function(){initNavTree('classmlx_1_1core_1_1io_1_1_writer.html',''); initResiz
-

#include <load.h>

+

#include <load.h>

Inheritance diagram for mlx::core::io::Writer:
@@ -335,7 +335,7 @@ Public Member Functions
The documentation for this class was generated from the following file: diff --git a/docs/build/html/common_2binary_8h.html b/docs/build/html/common_2binary_8h.html index c5d095d36..9fd7b7cb0 100644 --- a/docs/build/html/common_2binary_8h.html +++ b/docs/build/html/common_2binary_8h.html @@ -139,8 +139,8 @@ Enumerations Functions BinaryOpType mlx::core::get_binary_op_type (const array &a, const array &b)   -void mlx::core::set_binary_op_output_data (const array &a, const array &b, array &out, BinaryOpType bopt, bool donate_with_move=false) -  +void mlx::core::set_binary_op_output_data (const array &a, const array &b, array &out, BinaryOpType bopt) +  diff --git a/docs/build/html/common_2binary_8h.js b/docs/build/html/common_2binary_8h.js index 030091e38..7a3932ea3 100644 --- a/docs/build/html/common_2binary_8h.js +++ b/docs/build/html/common_2binary_8h.js @@ -8,5 +8,5 @@ var common_2binary_8h = [ "mlx::core::BinaryOpType::General", "namespacemlx_1_1core.html#a546e3d3c8957fbf2758f9504f4a2d0b6a0db377921f4ce762c62526131097968f", null ] ] ], [ "mlx::core::get_binary_op_type", "namespacemlx_1_1core.html#a24eef9908f164adeece3be7c6924919a", null ], - [ "mlx::core::set_binary_op_output_data", "namespacemlx_1_1core.html#a6a52856325c2eb031d3983eba2108d59", null ] + [ "mlx::core::set_binary_op_output_data", "namespacemlx_1_1core.html#a9f22a9ed98104aaffb929381055b966d", null ] ]; \ No newline at end of file diff --git a/docs/build/html/common_2binary_8h_source.html b/docs/build/html/common_2binary_8h_source.html index 50a81be57..d8983f679 100644 --- a/docs/build/html/common_2binary_8h_source.html +++ b/docs/build/html/common_2binary_8h_source.html @@ -146,106 +146,80 @@ $(function(){initNavTree('common_2binary_8h_source.html',''); initResizable(true
36
-
37inline void set_binary_op_output_data(
+
37inline void set_binary_op_output_data(
38 const array& a,
39 const array& b,
40 array& out,
-
41 BinaryOpType bopt,
-
42 bool donate_with_move = false) {
-
43 bool b_donatable = is_donatable(b, out);
-
44 bool a_donatable = is_donatable(a, out);
-
45 switch (bopt) {
-
46 case BinaryOpType::ScalarScalar:
-
47 out.set_data(
-
48 allocator::malloc_or_wait(out.itemsize()), 1, a.strides(), a.flags());
-
49 break;
-
50 case BinaryOpType::ScalarVector:
-
51 if (b_donatable) {
-
52 if (donate_with_move) {
-
53 out.move_shared_buffer(b);
-
54 } else {
-
55 out.copy_shared_buffer(b);
-
56 }
-
57 } else {
-
58 out.set_data(
-
59 allocator::malloc_or_wait(b.data_size() * out.itemsize()),
-
60 b.data_size(),
-
61 b.strides(),
-
62 b.flags());
-
63 }
-
64 break;
-
65 case BinaryOpType::VectorScalar:
-
66 if (a_donatable) {
-
67 if (donate_with_move) {
-
68 out.move_shared_buffer(a);
-
69 } else {
-
70 out.copy_shared_buffer(a);
-
71 }
-
72 } else {
-
73 out.set_data(
-
74 allocator::malloc_or_wait(a.data_size() * out.itemsize()),
-
75 a.data_size(),
-
76 a.strides(),
-
77 a.flags());
-
78 }
-
79 break;
-
80 case BinaryOpType::VectorVector:
-
81 if (a_donatable) {
-
82 if (donate_with_move) {
-
83 out.move_shared_buffer(a);
-
84 } else {
-
85 out.copy_shared_buffer(a);
-
86 }
-
87 } else if (b_donatable) {
-
88 if (donate_with_move) {
-
89 out.move_shared_buffer(b);
-
90 } else {
-
91 out.copy_shared_buffer(b);
-
92 }
-
93 } else {
-
94 out.set_data(
-
95 allocator::malloc_or_wait(a.data_size() * out.itemsize()),
-
96 a.data_size(),
-
97 a.strides(),
-
98 a.flags());
-
99 }
-
100 break;
-
101 case BinaryOpType::General:
-
102 if (a_donatable && a.flags().row_contiguous && a.size() == out.size()) {
-
103 if (donate_with_move) {
-
104 out.move_shared_buffer(a);
-
105 } else {
-
106 out.copy_shared_buffer(a);
-
107 }
-
108 } else if (
-
109 b_donatable && b.flags().row_contiguous && b.size() == out.size()) {
-
110 if (donate_with_move) {
-
111 out.move_shared_buffer(b);
-
112 } else {
-
113 out.copy_shared_buffer(b);
-
114 }
-
115 } else {
-
116 out.set_data(allocator::malloc_or_wait(out.nbytes()));
-
117 }
-
118 break;
-
119 }
-
120}
+
41 BinaryOpType bopt) {
+
42 bool b_donatable = is_donatable(b, out);
+
43 bool a_donatable = is_donatable(a, out);
+
44 switch (bopt) {
+
45 case BinaryOpType::ScalarScalar:
+
46 out.set_data(
+
47 allocator::malloc_or_wait(out.itemsize()), 1, a.strides(), a.flags());
+
48 break;
+
49 case BinaryOpType::ScalarVector:
+
50 if (b_donatable) {
+
51 out.copy_shared_buffer(b);
+
52 } else {
+
53 out.set_data(
+
54 allocator::malloc_or_wait(b.data_size() * out.itemsize()),
+
55 b.data_size(),
+
56 b.strides(),
+
57 b.flags());
+
58 }
+
59 break;
+
60 case BinaryOpType::VectorScalar:
+
61 if (a_donatable) {
+
62 out.copy_shared_buffer(a);
+
63 } else {
+
64 out.set_data(
+
65 allocator::malloc_or_wait(a.data_size() * out.itemsize()),
+
66 a.data_size(),
+
67 a.strides(),
+
68 a.flags());
+
69 }
+
70 break;
+
71 case BinaryOpType::VectorVector:
+
72 if (a_donatable) {
+
73 out.copy_shared_buffer(a);
+
74 } else if (b_donatable) {
+
75 out.copy_shared_buffer(b);
+
76 } else {
+
77 out.set_data(
+
78 allocator::malloc_or_wait(a.data_size() * out.itemsize()),
+
79 a.data_size(),
+
80 a.strides(),
+
81 a.flags());
+
82 }
+
83 break;
+
84 case BinaryOpType::General:
+
85 if (a_donatable && a.flags().row_contiguous && a.size() == out.size()) {
+
86 out.copy_shared_buffer(a);
+
87 } else if (
+
88 b_donatable && b.flags().row_contiguous && b.size() == out.size()) {
+
89 out.copy_shared_buffer(b);
+
90 } else {
+
91 out.set_data(allocator::malloc_or_wait(out.nbytes()));
+
92 }
+
93 break;
+
94 }
+
95}
-
121
-
122} // namespace mlx::core
+
96
+
97} // namespace mlx::core
mlx::core::array
Definition array.h:24
-
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:318
+
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:313
mlx::core::array::strides
const Strides & strides() const
The strides of the array.
Definition array.h:117
mlx::core::array::nbytes
size_t nbytes() const
The number of bytes in the array.
Definition array.h:93
mlx::core::array::size
size_t size() const
The number of elements in the array.
Definition array.h:88
mlx::core::array::copy_shared_buffer
void copy_shared_buffer(const array &other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
-
mlx::core::array::move_shared_buffer
void move_shared_buffer(array other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
mlx::core::array::itemsize
size_t itemsize() const
The size of the array's datatype in bytes.
Definition array.h:83
mlx::core::array::set_data
void set_data(allocator::Buffer buffer, Deleter d=allocator::free)
-
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:332
+
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:327
mlx::core::allocator::malloc_or_wait
Buffer malloc_or_wait(size_t size)
mlx::core
Definition allocator.h:7
mlx::core::get_binary_op_type
BinaryOpType get_binary_op_type(const array &a, const array &b)
Definition binary.h:19
@@ -255,14 +229,14 @@ $(function(){initNavTree('common_2binary_8h_source.html',''); initResizable(true
mlx::core::BinaryOpType::ScalarScalar
@ ScalarScalar
Definition binary.h:12
mlx::core::BinaryOpType::VectorScalar
@ VectorScalar
Definition binary.h:14
mlx::core::BinaryOpType::ScalarVector
@ ScalarVector
Definition binary.h:13
-
mlx::core::set_binary_op_output_data
void set_binary_op_output_data(const array &a, const array &b, array &out, BinaryOpType bopt, bool donate_with_move=false)
Definition binary.h:37
+
mlx::core::set_binary_op_output_data
void set_binary_op_output_data(const array &a, const array &b, array &out, BinaryOpType bopt)
Definition binary.h:37
mlx::core::is_donatable
bool is_donatable(const array &in, const array &out)
Definition utils.h:155
-
mlx::core::ScalarVector
Definition binary.h:40
-
mlx::core::VectorScalar
Definition binary.h:16
-
mlx::core::VectorVector
Definition binary.h:64
-
mlx::core::array::Flags::row_contiguous
bool row_contiguous
Definition array.h:237
-
mlx::core::array::Flags::col_contiguous
bool col_contiguous
Definition array.h:243
-
mlx::core::array::Flags::contiguous
bool contiguous
Definition array.h:231
+
mlx::core::ScalarVector
Definition binary.h:35
+
mlx::core::VectorScalar
Definition binary.h:15
+
mlx::core::VectorVector
Definition binary.h:55
+
mlx::core::array::Flags::row_contiguous
bool row_contiguous
Definition array.h:244
+
mlx::core::array::Flags::col_contiguous
bool col_contiguous
Definition array.h:250
+
mlx::core::array::Flags::contiguous
bool contiguous
Definition array.h:238
diff --git a/docs/build/html/common_2copy_8h.html b/docs/build/html/common_2copy_8h.html index ee0ef1cc1..5c7c28500 100644 --- a/docs/build/html/common_2copy_8h.html +++ b/docs/build/html/common_2copy_8h.html @@ -104,7 +104,8 @@ $(function(){initNavTree('common_2copy_8h.html',''); initResizable(true); });
Namespaces | -Enumerations
+Enumerations | +Functions
copy.h File Reference
@@ -127,6 +128,11 @@ Enumerations , mlx::core::GeneralGeneral }   + + + +

+Functions

bool mlx::core::set_copy_output_data (const array &in, array &out, CopyType ctype)
 
diff --git a/docs/build/html/common_2copy_8h.js b/docs/build/html/common_2copy_8h.js index 3397f32d4..371998e03 100644 --- a/docs/build/html/common_2copy_8h.js +++ b/docs/build/html/common_2copy_8h.js @@ -5,5 +5,6 @@ var common_2copy_8h = [ "mlx::core::CopyType::Vector", "namespacemlx_1_1core.html#abd84ff6c5245e4e170b2ef5247594337a57dea6f5039281b7fee517fc43bf3110", null ], [ "mlx::core::CopyType::General", "namespacemlx_1_1core.html#abd84ff6c5245e4e170b2ef5247594337a0db377921f4ce762c62526131097968f", null ], [ "mlx::core::CopyType::GeneralGeneral", "namespacemlx_1_1core.html#abd84ff6c5245e4e170b2ef5247594337a6fe62e8ce1fae1e70cb9eeaa67d29dab", null ] - ] ] + ] ], + [ "mlx::core::set_copy_output_data", "namespacemlx_1_1core.html#a3892b68a2e828270caa1c7accf44f038", null ] ]; \ No newline at end of file diff --git a/docs/build/html/common_2copy_8h_source.html b/docs/build/html/common_2copy_8h_source.html index 56d818476..0aedf96f3 100644 --- a/docs/build/html/common_2copy_8h_source.html +++ b/docs/build/html/common_2copy_8h_source.html @@ -131,9 +131,43 @@ $(function(){initNavTree('common_2copy_8h_source.html',''); initResizable(true);
23};
24
-
25} // namespace mlx::core
+
+
25inline bool set_copy_output_data(const array& in, array& out, CopyType ctype) {
+
26 if (ctype == CopyType::Vector) {
+
27 // If the input is donateable, we are doing a vector copy and the types
+
28 // have the same size, then the input buffer can hold the output.
+
29 if (in.is_donatable() && in.itemsize() == out.itemsize()) {
+
30 out.copy_shared_buffer(in);
+
31 return true;
+
32 } else {
+
33 out.set_data(
+
34 allocator::malloc_or_wait(in.data_size() * out.itemsize()),
+
35 in.data_size(),
+
36 in.strides(),
+
37 in.flags());
+
38 return false;
+
39 }
+
40 } else {
+
41 out.set_data(allocator::malloc_or_wait(out.nbytes()));
+
42 return false;
+
43 }
+
44}
+
+
45
+
46} // namespace mlx::core
+
mlx::core::array
Definition array.h:24
+
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:313
+
mlx::core::array::strides
const Strides & strides() const
The strides of the array.
Definition array.h:117
+
mlx::core::array::nbytes
size_t nbytes() const
The number of bytes in the array.
Definition array.h:93
+
mlx::core::array::is_donatable
bool is_donatable() const
True indicates the arrays buffer is safe to reuse.
Definition array.h:278
+
mlx::core::array::copy_shared_buffer
void copy_shared_buffer(const array &other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
+
mlx::core::array::itemsize
size_t itemsize() const
The size of the array's datatype in bytes.
Definition array.h:83
+
mlx::core::array::set_data
void set_data(allocator::Buffer buffer, Deleter d=allocator::free)
+
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:327
+
mlx::core::allocator::malloc_or_wait
Buffer malloc_or_wait(size_t size)
mlx::core
Definition allocator.h:7
+
mlx::core::set_copy_output_data
bool set_copy_output_data(const array &in, array &out, CopyType ctype)
Definition copy.h:25
mlx::core::BinaryOpType::General
@ General
Definition binary.h:16
mlx::core::CopyType
CopyType
Definition copy.h:9
mlx::core::CopyType::Vector
@ Vector
Definition copy.h:15
diff --git a/docs/build/html/common_2hadamard_8h_source.html b/docs/build/html/common_2hadamard_8h_source.html index 5c70f5ba9..65b322690 100644 --- a/docs/build/html/common_2hadamard_8h_source.html +++ b/docs/build/html/common_2hadamard_8h_source.html @@ -220,7 +220,7 @@ $(function(){initNavTree('common_2hadamard_8h_source.html',''); initResizable(tr
mlx::core::hadamard_matrices
const std::map< int, std::string_view > hadamard_matrices()
Definition hadamard.h:81
mlx::core::h20
constexpr std::string_view h20
Definition hadamard.h:27
mlx::core::h28
constexpr std::string_view h28
Definition hadamard.h:50
-
mlx::core::is_power_of_2
bool is_power_of_2(int n)
Definition utils.h:105
+
mlx::core::is_power_of_2
bool is_power_of_2(int n)
Definition utils.h:106
diff --git a/docs/build/html/common_2ternary_8h.html b/docs/build/html/common_2ternary_8h.html index 37bcfbb36..b05f23d46 100644 --- a/docs/build/html/common_2ternary_8h.html +++ b/docs/build/html/common_2ternary_8h.html @@ -134,8 +134,8 @@ Enumerations Functions TernaryOpType mlx::core::get_ternary_op_type (const array &a, const array &b, const array &c)   -void mlx::core::set_ternary_op_output_data (const array &a, const array &b, const array &c, array &out, TernaryOpType topt, bool donate_with_move=false) -  +void mlx::core::set_ternary_op_output_data (const array &a, const array &b, const array &c, array &out, TernaryOpType topt) +  diff --git a/docs/build/html/common_2ternary_8h.js b/docs/build/html/common_2ternary_8h.js index 5f139d48d..72e022e81 100644 --- a/docs/build/html/common_2ternary_8h.js +++ b/docs/build/html/common_2ternary_8h.js @@ -6,5 +6,5 @@ var common_2ternary_8h = [ "mlx::core::TernaryOpType::General", "namespacemlx_1_1core.html#ac2b8997537c7f25dd2b244d4c0a865a1a0db377921f4ce762c62526131097968f", null ] ] ], [ "mlx::core::get_ternary_op_type", "namespacemlx_1_1core.html#a548b6f4a39e639c18896e50b1702c830", null ], - [ "mlx::core::set_ternary_op_output_data", "namespacemlx_1_1core.html#a6f4528d0d338ea5e1f19d345875c26a2", null ] + [ "mlx::core::set_ternary_op_output_data", "namespacemlx_1_1core.html#ae159e1f9193c12eff9a56dfceb1502ef", null ] ]; \ No newline at end of file diff --git a/docs/build/html/common_2ternary_8h_source.html b/docs/build/html/common_2ternary_8h_source.html index eabc69f86..d4c89f7ec 100644 --- a/docs/build/html/common_2ternary_8h_source.html +++ b/docs/build/html/common_2ternary_8h_source.html @@ -143,76 +143,70 @@ $(function(){initNavTree('common_2ternary_8h_source.html',''); initResizable(tru
33
-
34inline void set_ternary_op_output_data(
+
34inline void set_ternary_op_output_data(
35 const array& a,
36 const array& b,
37 const array& c,
38 array& out,
-
39 TernaryOpType topt,
-
40 bool donate_with_move = false) {
-
41 auto maybe_donate = [&out, donate_with_move](const array& x) {
-
42 if (is_donatable(x, out)) {
-
43 if (donate_with_move) {
-
44 out.move_shared_buffer(x);
-
45 } else {
-
46 out.copy_shared_buffer(x);
-
47 }
-
48 return true;
-
49 }
-
50 return false;
-
51 };
-
52
-
53 switch (topt) {
-
54 case TernaryOpType::ScalarScalarScalar:
-
55 out.set_data(
-
56 allocator::malloc_or_wait(out.itemsize()), 1, b.strides(), b.flags());
-
57 break;
-
58 case TernaryOpType::VectorVectorVector:
-
59 if (!(maybe_donate(a) || maybe_donate(b) || maybe_donate(c))) {
-
60 out.set_data(
-
61 allocator::malloc_or_wait(out.itemsize() * b.data_size()),
-
62 b.data_size(),
-
63 b.strides(),
-
64 b.flags());
-
65 }
-
66 break;
-
67 case TernaryOpType::General:
-
68 // Try to donate an input which is row_contiguous
-
69 if (!((a.flags().row_contiguous && maybe_donate(a)) ||
-
70 (b.flags().row_contiguous && maybe_donate(b)) ||
-
71 (c.flags().row_contiguous && maybe_donate(c)))) {
-
72 out.set_data(allocator::malloc_or_wait(out.nbytes()));
-
73 }
-
74 break;
-
75 }
-
76}
+
39 TernaryOpType topt) {
+
40 auto maybe_donate = [&out](const array& x) {
+
41 if (is_donatable(x, out)) {
+
42 out.copy_shared_buffer(x);
+
43 return true;
+
44 }
+
45 return false;
+
46 };
+
47
+
48 switch (topt) {
+
49 case TernaryOpType::ScalarScalarScalar:
+
50 out.set_data(
+
51 allocator::malloc_or_wait(out.itemsize()), 1, b.strides(), b.flags());
+
52 break;
+
53 case TernaryOpType::VectorVectorVector:
+
54 if (!(maybe_donate(a) || maybe_donate(b) || maybe_donate(c))) {
+
55 out.set_data(
+
56 allocator::malloc_or_wait(out.itemsize() * b.data_size()),
+
57 b.data_size(),
+
58 b.strides(),
+
59 b.flags());
+
60 }
+
61 break;
+
62 case TernaryOpType::General:
+
63 // Try to donate an input which is row_contiguous
+
64 if (!((a.flags().row_contiguous && maybe_donate(a)) ||
+
65 (b.flags().row_contiguous && maybe_donate(b)) ||
+
66 (c.flags().row_contiguous && maybe_donate(c)))) {
+
67 out.set_data(allocator::malloc_or_wait(out.nbytes()));
+
68 }
+
69 break;
+
70 }
+
71}
-
77
-
78} // namespace mlx::core
+
72
+
73} // namespace mlx::core
mlx::core::array
Definition array.h:24
-
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:318
+
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:313
mlx::core::array::strides
const Strides & strides() const
The strides of the array.
Definition array.h:117
mlx::core::array::nbytes
size_t nbytes() const
The number of bytes in the array.
Definition array.h:93
mlx::core::array::copy_shared_buffer
void copy_shared_buffer(const array &other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
-
mlx::core::array::move_shared_buffer
void move_shared_buffer(array other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
mlx::core::array::itemsize
size_t itemsize() const
The size of the array's datatype in bytes.
Definition array.h:83
mlx::core::array::set_data
void set_data(allocator::Buffer buffer, Deleter d=allocator::free)
-
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:332
+
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:327
mlx::core::allocator::malloc_or_wait
Buffer malloc_or_wait(size_t size)
mlx::core
Definition allocator.h:7
mlx::core::BinaryOpType::General
@ General
Definition binary.h:16
mlx::core::get_ternary_op_type
TernaryOpType get_ternary_op_type(const array &a, const array &b, const array &c)
Definition ternary.h:18
-
mlx::core::set_ternary_op_output_data
void set_ternary_op_output_data(const array &a, const array &b, const array &c, array &out, TernaryOpType topt, bool donate_with_move=false)
Definition ternary.h:34
mlx::core::TernaryOpType
TernaryOpType
Definition ternary.h:11
mlx::core::TernaryOpType::ScalarScalarScalar
@ ScalarScalarScalar
Definition ternary.h:12
mlx::core::TernaryOpType::General
@ General
Definition ternary.h:14
mlx::core::TernaryOpType::VectorVectorVector
@ VectorVectorVector
Definition ternary.h:13
+
mlx::core::set_ternary_op_output_data
void set_ternary_op_output_data(const array &a, const array &b, const array &c, array &out, TernaryOpType topt)
Definition ternary.h:34
mlx::core::is_donatable
bool is_donatable(const array &in, const array &out)
Definition utils.h:155
-
mlx::core::array::Flags::row_contiguous
bool row_contiguous
Definition array.h:237
-
mlx::core::array::Flags::col_contiguous
bool col_contiguous
Definition array.h:243
+
mlx::core::array::Flags::row_contiguous
bool row_contiguous
Definition array.h:244
+
mlx::core::array::Flags::col_contiguous
bool col_contiguous
Definition array.h:250
diff --git a/docs/build/html/compiled_8h.html b/docs/build/html/compiled_8h.html index 7ed7d39bf..fa35e7fec 100644 --- a/docs/build/html/compiled_8h.html +++ b/docs/build/html/compiled_8h.html @@ -146,8 +146,8 @@ Functions   bool mlx::core::compiled_check_contiguity (const std::vector< array > &inputs, const Shape &shape)   -void mlx::core::compiled_allocate_outputs (const std::vector< array > &inputs, std::vector< array > &outputs, const std::vector< array > &inputs_, const std::unordered_set< uintptr_t > &constant_ids_, bool contiguous, bool move_buffers=false) -  +void mlx::core::compiled_allocate_outputs (const std::vector< array > &inputs, std::vector< array > &outputs, const std::vector< array > &inputs_, const std::unordered_set< uintptr_t > &constant_ids_, bool contiguous) +  diff --git a/docs/build/html/compiled_8h.js b/docs/build/html/compiled_8h.js index b878f272f..a2f8d3417 100644 --- a/docs/build/html/compiled_8h.js +++ b/docs/build/html/compiled_8h.js @@ -1,7 +1,7 @@ var compiled_8h = [ [ "mlx::core::build_lib_name", "namespacemlx_1_1core.html#a3ef23f334cb9f68a2c50524bc67c913b", null ], - [ "mlx::core::compiled_allocate_outputs", "namespacemlx_1_1core.html#ab8c3c4fc05745f586de922c8266f4fce", null ], + [ "mlx::core::compiled_allocate_outputs", "namespacemlx_1_1core.html#a8ed5ff0d69f6c7d2e092fe811e40d564", null ], [ "mlx::core::compiled_check_contiguity", "namespacemlx_1_1core.html#a562040f4a03f2c0a5d50eb9c8f14a8be", null ], [ "mlx::core::get_type_string", "namespacemlx_1_1core.html#af776fd91dd60594dcfebbafd17f19068", null ], [ "mlx::core::is_scalar", "namespacemlx_1_1core.html#a985c60929757190e0b4ec51f57c767d0", null ], diff --git a/docs/build/html/compiled_8h_source.html b/docs/build/html/compiled_8h_source.html index e279c1183..0631cec5d 100644 --- a/docs/build/html/compiled_8h_source.html +++ b/docs/build/html/compiled_8h_source.html @@ -174,22 +174,21 @@ $(function(){initNavTree('compiled_8h_source.html',''); initResizable(true); });
57 const Shape& shape);
58
59// Allocate space for the outputs possibly with input donation
-
60void compiled_allocate_outputs(
+
60void compiled_allocate_outputs(
61 const std::vector<array>& inputs,
62 std::vector<array>& outputs,
63 const std::vector<array>& inputs_,
64 const std::unordered_set<uintptr_t>& constant_ids_,
-
65 bool contiguous,
-
66 bool move_buffers = false);
-
67
-
68} // namespace mlx::core
+
65 bool contiguous);
+
66
+
67} // namespace mlx::core
mlx::core::AsType
Definition primitives.h:392
mlx::core::Broadcast
Definition primitives.h:541
mlx::core::Primitive
Definition primitives.h:48
mlx::core::array
Definition array.h:24
mlx::core::array::ndim
size_t ndim() const
The number of dimensions of the array.
Definition array.h:98
-
mlx::core::array::item
T item()
Get the value from a scalar array.
Definition array.h:551
+
mlx::core::array::item
T item()
Get the value from a scalar array.
Definition array.h:536
mlx::core::array::dtype
Dtype dtype() const
Get the arrays data type.
Definition array.h:131
mlx::core::contiguous
array contiguous(const array &a, bool allow_col_major=false, StreamOrDevice s={})
mlx::core
Definition allocator.h:7
@@ -198,10 +197,10 @@ $(function(){initNavTree('compiled_8h_source.html',''); initResizable(true); });
mlx::core::compiled_check_contiguity
bool compiled_check_contiguity(const std::vector< array > &inputs, const Shape &shape)
mlx::core::Shape
std::vector< ShapeElem > Shape
Definition array.h:21
mlx::core::print_constant
void print_constant(std::ostream &os, const array &x)
+
mlx::core::compiled_allocate_outputs
void compiled_allocate_outputs(const std::vector< array > &inputs, std::vector< array > &outputs, const std::vector< array > &inputs_, const std::unordered_set< uintptr_t > &constant_ids_, bool contiguous)
mlx::core::print_float_constant
void print_float_constant(std::ostream &os, const array &x)
Definition compiled.h:26
mlx::core::print_int_constant
void print_int_constant(std::ostream &os, const array &x)
Definition compiled.h:33
mlx::core::is_scalar
bool is_scalar(const array &x)
Definition compiled.h:50
-
mlx::core::compiled_allocate_outputs
void compiled_allocate_outputs(const std::vector< array > &inputs, std::vector< array > &outputs, const std::vector< array > &inputs_, const std::unordered_set< uintptr_t > &constant_ids_, bool contiguous, bool move_buffers=false)
mlx::core::get_type_string
std::string get_type_string(Dtype d)
mlx::core::is_static_cast
bool is_static_cast(const Primitive &p)
Definition compiled.h:13
diff --git a/docs/build/html/cpp/ops.html b/docs/build/html/cpp/ops.html index 194fc30a9..6ca15ab83 100644 --- a/docs/build/html/cpp/ops.html +++ b/docs/build/html/cpp/ops.html @@ -8,7 +8,7 @@ - Operations — MLX 0.23.2 documentation + Operations — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/cpu_2arange_8h.html b/docs/build/html/cpu_2arange_8h.html index 1da9dd3a2..69ec6ad7b 100644 --- a/docs/build/html/cpu_2arange_8h.html +++ b/docs/build/html/cpu_2arange_8h.html @@ -103,13 +103,12 @@ $(function(){initNavTree('cpu_2arange_8h.html',''); initResizable(true); });
-Namespaces | -Functions
+Namespaces
arange.h File Reference
-
#include "mlx/allocator.h"
-#include "mlx/array.h"
+
#include "mlx/array.h"
+#include "mlx/backend/cpu/encoder.h"

Go to the source code of this file.

@@ -119,11 +118,6 @@ Namespaces -
 
namespace  mlx::core
 
- - -

-Functions

void mlx::core::arange (const std::vector< array > &inputs, array &out, double start, double step)
 
diff --git a/docs/build/html/cpu_2arange_8h.js b/docs/build/html/cpu_2arange_8h.js deleted file mode 100644 index b5d9ef600..000000000 --- a/docs/build/html/cpu_2arange_8h.js +++ /dev/null @@ -1,4 +0,0 @@ -var cpu_2arange_8h = -[ - [ "mlx::core::arange", "namespacemlx_1_1core.html#a369aa886219b83cf219e7a7862ce260b", null ] -]; \ No newline at end of file diff --git a/docs/build/html/cpu_2arange_8h_source.html b/docs/build/html/cpu_2arange_8h_source.html index 827c5d9eb..88f480d6e 100644 --- a/docs/build/html/cpu_2arange_8h_source.html +++ b/docs/build/html/cpu_2arange_8h_source.html @@ -109,105 +109,38 @@ $(function(){initNavTree('cpu_2arange_8h_source.html',''); initResizable(true);
2
3#pragma once
4
-
5#include "mlx/allocator.h"
-
6#include "mlx/array.h"
+
5#include "mlx/array.h"
+
6#include "mlx/backend/cpu/encoder.h"
7
8namespace mlx::core {
9
10namespace {
11
12template <typename T>
-
13void arange(T start, T next, array& out, size_t size) {
-
14 auto ptr = out.data<T>();
+
13void arange(T start, T next, array& out, size_t size, Stream stream) {
+
14 auto ptr = out.data<T>();
15 auto step_size = next - start;
-
16 for (int i = 0; i < size; ++i) {
-
17 ptr[i] = start;
-
18 start += step_size;
-
19 }
-
20}
-
21
-
22} // namespace
-
23
-
-
24void arange(
-
25 const std::vector<array>& inputs,
-
26 array& out,
-
27 double start,
-
28 double step) {
-
29 assert(inputs.size() == 0);
-
30 out.set_data(allocator::malloc_or_wait(out.nbytes()));
-
31 switch (out.dtype()) {
-
32 case bool_:
-
33 throw std::runtime_error("Bool type unsupported for arange.");
-
34 break;
-
35 case uint8:
-
36 arange<uint8_t>(start, start + step, out, out.size());
-
37 break;
-
38 case uint16:
-
39 arange<uint16_t>(start, start + step, out, out.size());
-
40 break;
-
41 case uint32:
-
42 arange<uint32_t>(start, start + step, out, out.size());
-
43 break;
-
44 case uint64:
-
45 arange<uint64_t>(start, start + step, out, out.size());
-
46 break;
-
47 case int8:
-
48 arange<int8_t>(start, start + step, out, out.size());
-
49 break;
-
50 case int16:
-
51 arange<int16_t>(start, start + step, out, out.size());
-
52 break;
-
53 case int32:
-
54 arange<int32_t>(start, start + step, out, out.size());
-
55 break;
-
56 case int64:
-
57 arange<int64_t>(start, start + step, out, out.size());
-
58 break;
-
59 case float16:
-
60 arange<float16_t>(start, start + step, out, out.size());
-
61 break;
-
62 case float32:
-
63 arange<float>(start, start + step, out, out.size());
-
64 break;
-
65 case float64:
-
66 arange<double>(start, start + step, out, out.size());
-
67 break;
-
68 case bfloat16:
-
69 arange<bfloat16_t>(start, start + step, out, out.size());
-
70 break;
-
71 case complex64:
-
72 arange<complex64_t>(start, start + step, out, out.size());
-
73 break;
-
74 }
-
75}
-
-
76
-
77} // namespace mlx::core
- +
16 auto& encoder = cpu::get_command_encoder(stream);
+
17 encoder.set_output_array(out);
+
18 encoder.dispatch([ptr, start, step_size, size]() mutable {
+
19 for (int i = 0; i < size; ++i) {
+
20 ptr[i] = start;
+
21 start += step_size;
+
22 }
+
23 });
+
24}
+
25
+
26} // namespace
+
27
+
28} // namespace mlx::core
mlx::core::array
Definition array.h:24
-
mlx::core::array::nbytes
size_t nbytes() const
The number of bytes in the array.
Definition array.h:93
-
mlx::core::array::size
size_t size() const
The number of elements in the array.
Definition array.h:88
-
mlx::core::array::dtype
Dtype dtype() const
Get the arrays data type.
Definition array.h:131
-
mlx::core::array::set_data
void set_data(allocator::Buffer buffer, Deleter d=allocator::free)
-
mlx::core::allocator::malloc_or_wait
Buffer malloc_or_wait(size_t size)
+
mlx::core::array::data
T * data()
Definition array.h:349
+ +
mlx::core::arange
array arange(double start, double stop, double step, Dtype dtype, StreamOrDevice s={})
A 1D array of numbers starting at start (optional), stopping at stop, stepping by step (optional).
+
mlx::core::cpu::get_command_encoder
CommandEncoder & get_command_encoder(Stream stream)
mlx::core
Definition allocator.h:7
-
mlx::core::bool_
constexpr Dtype bool_
Definition dtype.h:68
-
mlx::core::uint64
constexpr Dtype uint64
Definition dtype.h:73
-
mlx::core::uint16
constexpr Dtype uint16
Definition dtype.h:71
-
mlx::core::arange
void arange(const std::vector< array > &inputs, array &out, double start, double step)
Definition arange.h:24
-
mlx::core::float64
constexpr Dtype float64
Definition dtype.h:82
-
mlx::core::bfloat16
constexpr Dtype bfloat16
Definition dtype.h:83
-
mlx::core::int32
constexpr Dtype int32
Definition dtype.h:77
-
mlx::core::float32
constexpr Dtype float32
Definition dtype.h:81
-
mlx::core::int16
constexpr Dtype int16
Definition dtype.h:76
-
mlx::core::int8
constexpr Dtype int8
Definition dtype.h:75
-
mlx::core::int64
constexpr Dtype int64
Definition dtype.h:78
-
mlx::core::uint8
constexpr Dtype uint8
Definition dtype.h:70
-
mlx::core::float16
constexpr Dtype float16
Definition dtype.h:80
-
mlx::core::uint32
constexpr Dtype uint32
Definition dtype.h:72
-
mlx::core::complex64
constexpr Dtype complex64
Definition dtype.h:84
+
mlx::core::Stream
Definition stream.h:9
diff --git a/docs/build/html/cpu_2binary_8h.html b/docs/build/html/cpu_2binary_8h.html index d10115299..4a9585413 100644 --- a/docs/build/html/cpu_2binary_8h.html +++ b/docs/build/html/cpu_2binary_8h.html @@ -110,7 +110,6 @@ $(function(){initNavTree('cpu_2binary_8h.html',''); initResizable(true); });
#include <cassert>
-#include "mlx/allocator.h"
#include "mlx/array.h"
#include "mlx/backend/common/binary.h"
#include "mlx/backend/common/utils.h"
@@ -136,21 +135,18 @@ Namespaces - - - - - - - - - - - - - - - + + + + + + + + + + + +

Functions

template<typename T, typename U, typename Op, int D, bool Strided>
void mlx::core::binary_op_dims (const T *a, const T *b, U *out, Op op, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides, int axis)
 
template<typename T, typename U, bool Strided, typename Op>
void mlx::core::binary_op_dispatch_dims (const array &a, const array &b, array &out, Op op, int dim, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides)
 
template<typename T, typename U, typename Op>
void mlx::core::binary_op (const array &a, const array &b, array &out, Op op)
 
template<typename T, typename Op>
void mlx::core::binary_op (const array &a, const array &b, array &out, Op op)
 
template<typename Op>
void mlx::core::binary (const array &a, const array &b, array &out, Op op)
 
template<typename T, typename U, typename Op, int D, bool Strided>
void mlx::core::binary_op_dims (const T *a, const T *b, U *out, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides, int axis)
 
template<typename T, typename U, bool Strided, typename Op>
void mlx::core::binary_op_dispatch_dims (const T *a, const T *b, U *out, int dim, int size, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides)
 
template<typename T, typename U, typename Op>
void mlx::core::binary_op (const array &a, const array &b, array &out, BinaryOpType bopt)
 
template<typename T, typename Op>
void mlx::core::binary_op (const array &a, const array &b, array &out, BinaryOpType bopt)
 
diff --git a/docs/build/html/cpu_2binary_8h.js b/docs/build/html/cpu_2binary_8h.js index 3c8896aa8..715265408 100644 --- a/docs/build/html/cpu_2binary_8h.js +++ b/docs/build/html/cpu_2binary_8h.js @@ -3,9 +3,8 @@ var cpu_2binary_8h = [ "mlx::core::VectorScalar< Op >", "structmlx_1_1core_1_1_vector_scalar.html", "structmlx_1_1core_1_1_vector_scalar" ], [ "mlx::core::ScalarVector< Op >", "structmlx_1_1core_1_1_scalar_vector.html", "structmlx_1_1core_1_1_scalar_vector" ], [ "mlx::core::VectorVector< Op >", "structmlx_1_1core_1_1_vector_vector.html", "structmlx_1_1core_1_1_vector_vector" ], - [ "mlx::core::binary", "namespacemlx_1_1core.html#ae374861abd45cf019c3e6be2026f3798", null ], - [ "mlx::core::binary_op", "namespacemlx_1_1core.html#a9c1c1fdf9a0840a16a4d10a8f74f761d", null ], - [ "mlx::core::binary_op", "namespacemlx_1_1core.html#a2aca3458c56605a74d07ec39876549bc", null ], - [ "mlx::core::binary_op_dims", "namespacemlx_1_1core.html#a7ca09ebf776fe32db580f9038587ec31", null ], - [ "mlx::core::binary_op_dispatch_dims", "namespacemlx_1_1core.html#a66c9ee5018168b9101de52e0122d9755", null ] + [ "mlx::core::binary_op", "namespacemlx_1_1core.html#ae0c47c0bd95bb8c44339159e04c0f604", null ], + [ "mlx::core::binary_op", "namespacemlx_1_1core.html#a5160ef5819f58cf040c9613ecce548f1", null ], + [ "mlx::core::binary_op_dims", "namespacemlx_1_1core.html#aeac6fa9529eedba76b27de9d098de963", null ], + [ "mlx::core::binary_op_dispatch_dims", "namespacemlx_1_1core.html#ad1229ffbba21bdb81f63482a4651bc5a", null ] ]; \ No newline at end of file diff --git a/docs/build/html/cpu_2binary_8h_source.html b/docs/build/html/cpu_2binary_8h_source.html index 762cbc7e3..a88304321 100644 --- a/docs/build/html/cpu_2binary_8h_source.html +++ b/docs/build/html/cpu_2binary_8h_source.html @@ -110,454 +110,348 @@ $(function(){initNavTree('cpu_2binary_8h_source.html',''); initResizable(true);
3#pragma once
4#include <cassert>
5
-
6#include "mlx/allocator.h"
-
7#include "mlx/array.h"
-
8#include "mlx/backend/common/binary.h"
-
9#include "mlx/backend/common/utils.h"
-
10
-
11#include "mlx/backend/cpu/simd/simd.h"
-
12
-
13namespace mlx::core {
-
14
-
15template <typename Op>
-
-
16struct VectorScalar {
-
17 Op op;
-
18
-
19 VectorScalar(Op op_) : op(op_) {}
-
20
-
21 template <typename T, typename U>
-
-
22 void operator()(const T* a, const T* b, U* dst, int size) {
-
23 T scalar = *b;
-
24 constexpr int N = simd::max_size<T>;
-
25 while (size >= N) {
-
26 simd::store(dst, op(simd::load<T, N>(a), simd::Simd<T, N>(scalar)));
-
27 dst += N;
-
28 a += N;
-
29 size -= N;
+
6#include "mlx/array.h"
+
7#include "mlx/backend/common/binary.h"
+
8#include "mlx/backend/common/utils.h"
+
9
+
10#include "mlx/backend/cpu/simd/simd.h"
+
11
+
12namespace mlx::core {
+
13
+
14template <typename Op>
+
+
15struct VectorScalar {
+
16 template <typename T, typename U>
+
+
17 void operator()(const T* a, const T* b, U* dst, int size) {
+
18 T scalar = *b;
+
19 constexpr int N = simd::max_size<T>;
+
20 while (size >= N) {
+
21 simd::store(dst, Op{}(simd::load<T, N>(a), simd::Simd<T, N>(scalar)));
+
22 dst += N;
+
23 a += N;
+
24 size -= N;
+
25 }
+
26 while (size-- > 0) {
+
27 *dst = Op{}(*a, scalar);
+
28 dst++;
+
29 a++;
30 }
-
31 while (size-- > 0) {
-
32 *dst = op(*a, scalar);
-
33 dst++;
-
34 a++;
-
35 }
-
36 }
+
31 }
-
37};
+
32};
-
38
-
39template <typename Op>
-
-
40struct ScalarVector {
-
41 Op op;
-
42
-
43 ScalarVector(Op op_) : op(op_) {}
-
44
-
45 template <typename T, typename U>
-
-
46 void operator()(const T* a, const T* b, U* dst, int size) {
-
47 T scalar = *a;
-
48 constexpr int N = simd::max_size<T>;
-
49 while (size >= N) {
-
50 simd::store(dst, op(simd::Simd<T, N>(scalar), simd::load<T, N>(b)));
-
51 dst += N;
-
52 b += N;
-
53 size -= N;
-
54 }
-
55 while (size-- > 0) {
-
56 *dst = op(scalar, *b);
-
57 dst++;
-
58 b++;
-
59 }
-
60 }
+
33
+
34template <typename Op>
+
+
35struct ScalarVector {
+
36 template <typename T, typename U>
+
+
37 void operator()(const T* a, const T* b, U* dst, int size) {
+
38 T scalar = *a;
+
39 constexpr int N = simd::max_size<T>;
+
40 while (size >= N) {
+
41 simd::store(dst, Op{}(simd::Simd<T, N>(scalar), simd::load<T, N>(b)));
+
42 dst += N;
+
43 b += N;
+
44 size -= N;
+
45 }
+
46 while (size-- > 0) {
+
47 *dst = Op{}(scalar, *b);
+
48 dst++;
+
49 b++;
+
50 }
+
51 }
-
61};
+
52};
-
62
-
63template <typename Op>
-
-
64struct VectorVector {
-
65 Op op;
-
66
-
67 VectorVector(Op op_) : op(op_) {}
-
68
-
69 template <typename T, typename U>
-
-
70 void operator()(const T* a, const T* b, U* dst, int size) {
-
71 constexpr int N = simd::max_size<T>;
-
72 while (size >= N) {
-
73 simd::store(dst, op(simd::load<T, N>(a), simd::load<T, N>(b)));
-
74 dst += N;
-
75 a += N;
-
76 b += N;
-
77 size -= N;
-
78 }
-
79 while (size-- > 0) {
-
80 *dst = op(*a, *b);
-
81 dst++;
-
82 a++;
-
83 b++;
-
84 }
-
85 }
+
53
+
54template <typename Op>
+
+
55struct VectorVector {
+
56 template <typename T, typename U>
+
+
57 void operator()(const T* a, const T* b, U* dst, int size) {
+
58 constexpr int N = simd::max_size<T>;
+
59 while (size >= N) {
+
60 simd::store(dst, Op{}(simd::load<T, N>(a), simd::load<T, N>(b)));
+
61 dst += N;
+
62 a += N;
+
63 b += N;
+
64 size -= N;
+
65 }
+
66 while (size-- > 0) {
+
67 *dst = Op{}(*a, *b);
+
68 dst++;
+
69 a++;
+
70 b++;
+
71 }
+
72 }
-
86};
+
73};
-
87
-
88template <typename T, typename U, typename Op, int D, bool Strided>
-
-
89void binary_op_dims(
-
90 const T* a,
-
91 const T* b,
-
92 U* out,
-
93 Op op,
-
94 const Shape& shape,
-
95 const Strides& a_strides,
-
96 const Strides& b_strides,
-
97 const Strides& out_strides,
-
98 int axis) {
-
99 auto stride_a = a_strides[axis];
-
100 auto stride_b = b_strides[axis];
-
101 auto stride_out = out_strides[axis];
-
102 auto N = shape[axis];
-
103
-
104 for (int i = 0; i < N; i++) {
-
105 if constexpr (D > 1) {
-
106 binary_op_dims<T, U, Op, D - 1, Strided>(
-
107 a, b, out, op, shape, a_strides, b_strides, out_strides, axis + 1);
-
108 } else {
-
109 if constexpr (Strided) {
-
110 op(a, b, out, stride_out);
-
111 } else {
-
112 *out = op(*a, *b);
-
113 }
-
114 }
-
115 out += stride_out;
-
116 a += stride_a;
-
117 b += stride_b;
-
118 }
-
119}
+
74
+
75template <typename T, typename U, typename Op, int D, bool Strided>
+
+
76void binary_op_dims(
+
77 const T* a,
+
78 const T* b,
+
79 U* out,
+
80 const Shape& shape,
+
81 const Strides& a_strides,
+
82 const Strides& b_strides,
+
83 const Strides& out_strides,
+
84 int axis) {
+
85 auto stride_a = a_strides[axis];
+
86 auto stride_b = b_strides[axis];
+
87 auto stride_out = out_strides[axis];
+
88 auto N = shape[axis];
+
89
+
90 for (int i = 0; i < N; i++) {
+
91 if constexpr (D > 1) {
+
92 binary_op_dims<T, U, Op, D - 1, Strided>(
+
93 a, b, out, shape, a_strides, b_strides, out_strides, axis + 1);
+
94 } else {
+
95 if constexpr (Strided) {
+
96 Op{}(a, b, out, stride_out);
+
97 } else {
+
98 *out = Op{}(*a, *b);
+
99 }
+
100 }
+
101 out += stride_out;
+
102 a += stride_a;
+
103 b += stride_b;
+
104 }
+
105}
-
120
-
121template <typename T, typename U, bool Strided, typename Op>
-
-
122void binary_op_dispatch_dims(
-
123 const array& a,
-
124 const array& b,
-
125 array& out,
-
126 Op op,
-
127 int dim,
-
128 const Shape& shape,
-
129 const Strides& a_strides,
-
130 const Strides& b_strides,
-
131 const Strides& out_strides) {
-
132 const T* a_ptr = a.data<T>();
-
133 const T* b_ptr = b.data<T>();
-
134 U* out_ptr = out.data<U>();
-
135 switch (dim) {
-
136 case 1:
-
137 binary_op_dims<T, U, Op, 1, Strided>(
-
138 a_ptr,
-
139 b_ptr,
-
140 out_ptr,
-
141 op,
-
142 shape,
-
143 a_strides,
-
144 b_strides,
-
145 out_strides,
-
146 0);
-
147 return;
-
148 case 2:
-
149 binary_op_dims<T, U, Op, 2, Strided>(
-
150 a_ptr,
-
151 b_ptr,
-
152 out_ptr,
-
153 op,
-
154 shape,
-
155 a_strides,
-
156 b_strides,
-
157 out_strides,
-
158 0);
-
159 return;
-
160 case 3:
-
161 binary_op_dims<T, U, Op, 3, Strided>(
-
162 a_ptr,
-
163 b_ptr,
-
164 out_ptr,
-
165 op,
-
166 shape,
-
167 a_strides,
-
168 b_strides,
-
169 out_strides,
-
170 0);
-
171 return;
-
172 }
-
173
-
174 ContiguousIterator a_it(shape, a_strides, dim - 3);
-
175 ContiguousIterator b_it(shape, b_strides, dim - 3);
-
176 auto stride = out_strides[dim - 4];
-
177 for (int64_t elem = 0; elem < a.size(); elem += stride) {
-
178 binary_op_dims<T, U, Op, 3, Strided>(
-
179 a_ptr + a_it.loc,
-
180 b_ptr + b_it.loc,
-
181 out_ptr + elem,
-
182 op,
-
183 shape,
-
184 a_strides,
-
185 b_strides,
-
186 out_strides,
-
187 dim - 3);
-
188 a_it.step();
-
189 b_it.step();
-
190 }
-
191}
+
106
+
107template <typename T, typename U, bool Strided, typename Op>
+
+
108void binary_op_dispatch_dims(
+
109 const T* a,
+
110 const T* b,
+
111 U* out,
+
112 int dim,
+
113 int size,
+
114 const Shape& shape,
+
115 const Strides& a_strides,
+
116 const Strides& b_strides,
+
117 const Strides& out_strides) {
+
118 switch (dim) {
+
119 case 1:
+
120 binary_op_dims<T, U, Op, 1, Strided>(
+
121 a, b, out, shape, a_strides, b_strides, out_strides, 0);
+
122 return;
+
123 case 2:
+
124 binary_op_dims<T, U, Op, 2, Strided>(
+
125 a, b, out, shape, a_strides, b_strides, out_strides, 0);
+
126 return;
+
127 case 3:
+
128 binary_op_dims<T, U, Op, 3, Strided>(
+
129 a, b, out, shape, a_strides, b_strides, out_strides, 0);
+
130 return;
+
131 }
+
132
+
133 ContiguousIterator a_it(shape, a_strides, dim - 3);
+
134 ContiguousIterator b_it(shape, b_strides, dim - 3);
+
135 auto stride = out_strides[dim - 4];
+
136 for (int64_t elem = 0; elem < size; elem += stride) {
+
137 binary_op_dims<T, U, Op, 3, Strided>(
+
138 a + a_it.loc,
+
139 b + b_it.loc,
+
140 out + elem,
+
141 shape,
+
142 a_strides,
+
143 b_strides,
+
144 out_strides,
+
145 dim - 3);
+
146 a_it.step();
+
147 b_it.step();
+
148 }
+
149}
-
192
-
193template <typename T, typename U, typename Op>
-
-
194void binary_op(const array& a, const array& b, array& out, Op op) {
-
195 auto bopt = get_binary_op_type(a, b);
-
196 set_binary_op_output_data(a, b, out, bopt);
+
150
+
151template <typename T, typename U, typename Op>
+
+
152void binary_op(const array& a, const array& b, array& out, BinaryOpType bopt) {
+
153 // The full computation is scalar scalar so call the base op once
+
154 auto a_ptr = a.data<T>();
+
155 auto b_ptr = b.data<T>();
+
156
+
157 auto out_ptr = out.data<U>();
+
158 if (bopt == BinaryOpType::ScalarScalar) {
+
159 *out_ptr = Op{}(*a_ptr, *b_ptr);
+
160 return;
+
161 }
+
162
+
163 // The full computation is scalar vector so delegate to the op
+
164 if (bopt == BinaryOpType::ScalarVector) {
+
165 ScalarVector<Op>{}(a_ptr, b_ptr, out_ptr, b.data_size());
+
166 return;
+
167 }
+
168
+
169 // The full computation is vector scalar so delegate to the op
+
170 if (bopt == BinaryOpType::VectorScalar) {
+
171 VectorScalar<Op>{}(a_ptr, b_ptr, out_ptr, a.data_size());
+
172 return;
+
173 }
+
174
+
175 // The full computation is vector vector so delegate to the op
+
176 if (bopt == BinaryOpType::VectorVector) {
+
177 VectorVector<Op>{}(a_ptr, b_ptr, out_ptr, a.size());
+
178 return;
+
179 }
+
180
+
181 // General computation so let's try to optimize
+
182 auto [new_shape, new_strides] = collapse_contiguous_dims(
+
183 a.shape(), {a.strides(), b.strides(), out.strides()});
+
184 auto& a_strides = new_strides[0];
+
185 auto& b_strides = new_strides[1];
+
186 auto& strides = new_strides[2];
+
187
+
188 // Get the left-most dim such that the array is row contiguous after
+
189 auto leftmost_rc_dim = [&strides](const auto& arr_strides) {
+
190 int d = arr_strides.size() - 1;
+
191 for (; d >= 0 && arr_strides[d] == strides[d]; d--) {
+
192 }
+
193 return d + 1;
+
194 };
+
195 auto a_rc_dim = leftmost_rc_dim(a_strides);
+
196 auto b_rc_dim = leftmost_rc_dim(b_strides);
197
-
198 // The full computation is scalar scalar so call the base op once
-
199 if (bopt == BinaryOpType::ScalarScalar) {
-
200 *(out.data<U>()) = op(*a.data<T>(), *b.data<T>());
-
201 return;
-
202 }
-
203
-
204 // The full computation is scalar vector so delegate to the op
-
205 if (bopt == BinaryOpType::ScalarVector) {
-
206 ScalarVector{op}(a.data<T>(), b.data<T>(), out.data<U>(), b.data_size());
-
207 return;
-
208 }
+
198 // Get the left-most dim such that the array is a broadcasted "scalar" after
+
199 auto leftmost_s_dim = [](const auto& arr_strides) {
+
200 int d = arr_strides.size() - 1;
+
201 for (; d >= 0 && arr_strides[d] == 0; d--) {
+
202 }
+
203 return d + 1;
+
204 };
+
205 auto a_s_dim = leftmost_s_dim(a_strides);
+
206 auto b_s_dim = leftmost_s_dim(b_strides);
+
207
+
208 auto ndim = new_shape.size();
209
-
210 // The full computation is vector scalar so delegate to the op
-
211 if (bopt == BinaryOpType::VectorScalar) {
-
212 VectorScalar{op}(a.data<T>(), b.data<T>(), out.data<U>(), a.data_size());
-
213 return;
-
214 }
-
215
-
216 // The full computation is vector vector so delegate to the op
-
217 if (bopt == BinaryOpType::VectorVector) {
-
218 VectorVector{op}(a.data<T>(), b.data<T>(), out.data<U>(), out.size());
-
219 return;
-
220 }
-
221
-
222 // General computation so let's try to optimize
-
223 auto [new_shape, new_strides] = collapse_contiguous_dims(
-
224 a.shape(), {a.strides(), b.strides(), out.strides()});
-
225 const auto& a_strides = new_strides[0];
-
226 const auto& b_strides = new_strides[1];
-
227 const auto& strides = new_strides[2];
-
228
-
229 // Get the left-most dim such that the array is row contiguous after
-
230 auto leftmost_rc_dim = [&strides](const auto& arr_strides) {
-
231 int d = arr_strides.size() - 1;
-
232 for (; d >= 0 && arr_strides[d] == strides[d]; d--) {
-
233 }
-
234 return d + 1;
-
235 };
-
236 auto a_rc_dim = leftmost_rc_dim(a_strides);
-
237 auto b_rc_dim = leftmost_rc_dim(b_strides);
-
238
-
239 // Get the left-most dim such that the array is a broadcasted "scalar" after
-
240 auto leftmost_s_dim = [](const auto& arr_strides) {
-
241 int d = arr_strides.size() - 1;
-
242 for (; d >= 0 && arr_strides[d] == 0; d--) {
-
243 }
-
244 return d + 1;
-
245 };
-
246 auto a_s_dim = leftmost_s_dim(a_strides);
-
247 auto b_s_dim = leftmost_s_dim(b_strides);
-
248
-
249 auto ndim = new_shape.size();
-
250
-
251 // Case 1: LxM and FxM where L and F are broadcastable and M is row contiguous
-
252 int dim = ndim;
-
253 if (int d = std::max(a_rc_dim, b_rc_dim); d < ndim) {
-
254 bopt = BinaryOpType::VectorVector;
-
255 dim = d;
-
256 // Case 2: LxM and Fx1 where L and F are broadcastable and M is row
-
257 // contiguous
-
258 } else if (int d = std::max(a_rc_dim, b_s_dim); d < ndim) {
-
259 bopt = BinaryOpType::VectorScalar;
-
260 dim = d;
-
261 // Case 3: Lx1 and FxM where L and F are broadcastable and M is row
-
262 // contiguous
-
263 } else if (int d = std::max(a_s_dim, b_rc_dim); d < ndim) {
-
264 bopt = BinaryOpType::ScalarVector;
-
265 dim = d;
-
266 }
-
267
-
268 // Can be sure dim > 0 since otherwise we would have used one of the fully
-
269 // contiguous methods above. Except for the case that the flags do not
-
270 // correspond to the underlying contiguity.
-
271 if (dim == 0 || strides[dim - 1] < 16) {
-
272 bopt = BinaryOpType::General;
-
273 dim = ndim;
-
274 }
-
275
-
276 switch (bopt) {
-
277 case BinaryOpType::VectorVector:
-
278 binary_op_dispatch_dims<T, U, true>(
-
279 a,
-
280 b,
-
281 out,
-
282 VectorVector{op},
-
283 dim,
-
284 new_shape,
-
285 a_strides,
-
286 b_strides,
-
287 strides);
-
288 break;
-
289 case BinaryOpType::VectorScalar:
-
290 binary_op_dispatch_dims<T, U, true>(
-
291 a,
-
292 b,
-
293 out,
-
294 VectorScalar{op},
-
295 dim,
-
296 new_shape,
-
297 a_strides,
-
298 b_strides,
-
299 strides);
-
300 break;
-
301 case BinaryOpType::ScalarVector:
-
302 binary_op_dispatch_dims<T, U, true>(
-
303 a,
-
304 b,
-
305 out,
-
306 ScalarVector{op},
-
307 dim,
-
308 new_shape,
-
309 a_strides,
-
310 b_strides,
-
311 strides);
-
312 break;
-
313 default:
-
314 binary_op_dispatch_dims<T, U, false>(
-
315 a, b, out, op, dim, new_shape, a_strides, b_strides, strides);
-
316 break;
-
317 }
-
318}
+
210 // Case 1: LxM and FxM where L and F are broadcastable and M is row
+
211 // contiguous
+
212 int dim = ndim;
+
213 if (int d = std::max(a_rc_dim, b_rc_dim); d < ndim) {
+
214 bopt = BinaryOpType::VectorVector;
+
215 dim = d;
+
216 // Case 2: LxM and Fx1 where L and F are broadcastable and M is row
+
217 // contiguous
+
218 } else if (int d = std::max(a_rc_dim, b_s_dim); d < ndim) {
+
219 bopt = BinaryOpType::VectorScalar;
+
220 dim = d;
+
221 // Case 3: Lx1 and FxM where L and F are broadcastable and M is row
+
222 // contiguous
+
223 } else if (int d = std::max(a_s_dim, b_rc_dim); d < ndim) {
+
224 bopt = BinaryOpType::ScalarVector;
+
225 dim = d;
+
226 }
+
227
+
228 // Can be sure dim > 0 since otherwise we would have used one of the fully
+
229 // contiguous methods above. Except for the case that the flags do not
+
230 // correspond to the underlying contiguity.
+
231 if (dim == 0 || strides[dim - 1] < 16) {
+
232 bopt = BinaryOpType::General;
+
233 dim = ndim;
+
234 }
+
235
+
236 switch (bopt) {
+
237 case BinaryOpType::VectorVector:
+
238 binary_op_dispatch_dims<T, U, true, VectorVector<Op>>(
+
239 a_ptr,
+
240 b_ptr,
+
241 out_ptr,
+
242 dim,
+
243 a.size(),
+
244 new_shape,
+
245 a_strides,
+
246 b_strides,
+
247 strides);
+
248 break;
+
249 case BinaryOpType::VectorScalar:
+
250 binary_op_dispatch_dims<T, U, true, VectorScalar<Op>>(
+
251 a_ptr,
+
252 b_ptr,
+
253 out_ptr,
+
254 dim,
+
255 a.size(),
+
256 new_shape,
+
257 a_strides,
+
258 b_strides,
+
259 strides);
+
260 break;
+
261 case BinaryOpType::ScalarVector:
+
262 binary_op_dispatch_dims<T, U, true, ScalarVector<Op>>(
+
263 a_ptr,
+
264 b_ptr,
+
265 out_ptr,
+
266 dim,
+
267 a.size(),
+
268 new_shape,
+
269 a_strides,
+
270 b_strides,
+
271 strides);
+
272 break;
+
273 default:
+
274 binary_op_dispatch_dims<T, U, false, Op>(
+
275 a_ptr,
+
276 b_ptr,
+
277 out_ptr,
+
278 dim,
+
279 a.size(),
+
280 new_shape,
+
281 a_strides,
+
282 b_strides,
+
283 strides);
+
284 break;
+
285 }
+
286}
-
319
-
320template <typename T, typename Op>
-
-
321void binary_op(const array& a, const array& b, array& out, Op op) {
-
322 binary_op<T, T>(a, b, out, op);
-
323}
+
287
+
288template <typename T, typename Op>
+
+
289void binary_op(const array& a, const array& b, array& out, BinaryOpType bopt) {
+
290 binary_op<T, T, Op>(a, b, out, bopt);
+
291}
-
324
-
325template <typename Op>
-
-
326void binary(const array& a, const array& b, array& out, Op op) {
-
327 switch (out.dtype()) {
-
328 case bool_:
-
329 binary_op<bool>(a, b, out, op);
-
330 break;
-
331 case uint8:
-
332 binary_op<uint8_t>(a, b, out, op);
-
333 break;
-
334 case uint16:
-
335 binary_op<uint16_t>(a, b, out, op);
-
336 break;
-
337 case uint32:
-
338 binary_op<uint32_t>(a, b, out, op);
-
339 break;
-
340 case uint64:
-
341 binary_op<uint64_t>(a, b, out, op);
-
342 break;
-
343 case int8:
-
344 binary_op<int8_t>(a, b, out, op);
-
345 break;
-
346 case int16:
-
347 binary_op<int16_t>(a, b, out, op);
-
348 break;
-
349 case int32:
-
350 binary_op<int32_t>(a, b, out, op);
-
351 break;
-
352 case int64:
-
353 binary_op<int64_t>(a, b, out, op);
-
354 break;
-
355 case float16:
-
356 binary_op<float16_t>(a, b, out, op);
-
357 break;
-
358 case float32:
-
359 binary_op<float>(a, b, out, op);
-
360 break;
-
361 case float64:
-
362 binary_op<double>(a, b, out, op);
-
363 break;
-
364 case bfloat16:
-
365 binary_op<bfloat16_t>(a, b, out, op);
-
366 break;
-
367 case complex64:
-
368 binary_op<complex64_t>(a, b, out, op);
-
369 break;
-
370 }
-
371}
-
-
372
-
373} // namespace mlx::core
- +
292
+
293} // namespace mlx::core
mlx::core::array
Definition array.h:24
mlx::core::array::shape
const Shape & shape() const
The shape of the array as a vector of integers.
Definition array.h:103
mlx::core::array::size
size_t size() const
The number of elements in the array.
Definition array.h:88
-
mlx::core::array::data
T * data()
Definition array.h:354
-
mlx::core::array::dtype
Dtype dtype() const
Get the arrays data type.
Definition array.h:131
-
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:332
+
mlx::core::array::data
T * data()
Definition array.h:349
+
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:327
mlx::core::simd::load
Simd< T, N > load(const T *x)
Definition base_simd.h:28
mlx::core::simd::max_size
static constexpr int max_size
Definition base_simd.h:14
mlx::core::simd::store
void store(T *dst, Simd< T, N > x)
Definition base_simd.h:33
mlx::core
Definition allocator.h:7
-
mlx::core::bool_
constexpr Dtype bool_
Definition dtype.h:68
-
mlx::core::uint64
constexpr Dtype uint64
Definition dtype.h:73
-
mlx::core::get_binary_op_type
BinaryOpType get_binary_op_type(const array &a, const array &b)
Definition binary.h:19
-
mlx::core::uint16
constexpr Dtype uint16
Definition dtype.h:71
-
mlx::core::float64
constexpr Dtype float64
Definition dtype.h:82
mlx::core::collapse_contiguous_dims
std::tuple< Shape, std::vector< Strides > > collapse_contiguous_dims(const Shape &shape, const std::vector< Strides > &strides, int64_t size_cap=std::numeric_limits< int32_t >::max())
-
mlx::core::bfloat16
constexpr Dtype bfloat16
Definition dtype.h:83
+
mlx::core::BinaryOpType
BinaryOpType
Definition binary.h:11
mlx::core::BinaryOpType::General
@ General
Definition binary.h:16
mlx::core::BinaryOpType::VectorVector
@ VectorVector
Definition binary.h:15
mlx::core::BinaryOpType::ScalarScalar
@ ScalarScalar
Definition binary.h:12
mlx::core::BinaryOpType::VectorScalar
@ VectorScalar
Definition binary.h:14
mlx::core::BinaryOpType::ScalarVector
@ ScalarVector
Definition binary.h:13
-
mlx::core::int32
constexpr Dtype int32
Definition dtype.h:77
-
mlx::core::binary_op_dispatch_dims
void binary_op_dispatch_dims(const array &a, const array &b, array &out, Op op, int dim, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides)
Definition binary.h:122
-
mlx::core::float32
constexpr Dtype float32
Definition dtype.h:81
mlx::core::Shape
std::vector< ShapeElem > Shape
Definition array.h:21
-
mlx::core::set_binary_op_output_data
void set_binary_op_output_data(const array &a, const array &b, array &out, BinaryOpType bopt, bool donate_with_move=false)
Definition binary.h:37
-
mlx::core::int16
constexpr Dtype int16
Definition dtype.h:76
mlx::core::Strides
std::vector< int64_t > Strides
Definition array.h:22
-
mlx::core::binary_op_dims
void binary_op_dims(const T *a, const T *b, U *out, Op op, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides, int axis)
Definition binary.h:89
-
mlx::core::int8
constexpr Dtype int8
Definition dtype.h:75
-
mlx::core::int64
constexpr Dtype int64
Definition dtype.h:78
-
mlx::core::uint8
constexpr Dtype uint8
Definition dtype.h:70
-
mlx::core::binary_op
void binary_op(const array &a, const array &b, array &out, Op op)
Definition binary.h:194
-
mlx::core::float16
constexpr Dtype float16
Definition dtype.h:80
-
mlx::core::uint32
constexpr Dtype uint32
Definition dtype.h:72
-
mlx::core::binary
void binary(const array &a, const array &b, array &out, Op op)
Definition binary.h:326
-
mlx::core::complex64
constexpr Dtype complex64
Definition dtype.h:84
+
mlx::core::binary_op_dispatch_dims
void binary_op_dispatch_dims(const T *a, const T *b, U *out, int dim, int size, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides)
Definition binary.h:108
+
mlx::core::binary_op
void binary_op(const array &a, const array &b, array &out, BinaryOpType bopt)
Definition binary.h:152
+
mlx::core::binary_op_dims
void binary_op_dims(const T *a, const T *b, U *out, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides, int axis)
Definition binary.h:76
mlx::core::ContiguousIterator
Definition utils.h:73
mlx::core::ContiguousIterator::loc
int64_t loc
Definition utils.h:126
mlx::core::ContiguousIterator::step
void step()
Definition utils.h:74
-
mlx::core::ScalarVector
Definition binary.h:40
-
mlx::core::ScalarVector::ScalarVector
ScalarVector(Op op_)
Definition binary.h:43
-
mlx::core::ScalarVector::operator()
void operator()(const T *a, const T *b, U *dst, int size)
Definition binary.h:46
-
mlx::core::ScalarVector::op
Op op
Definition binary.h:41
-
mlx::core::VectorScalar
Definition binary.h:16
-
mlx::core::VectorScalar::operator()
void operator()(const T *a, const T *b, U *dst, int size)
Definition binary.h:22
-
mlx::core::VectorScalar::op
Op op
Definition binary.h:17
-
mlx::core::VectorScalar::VectorScalar
VectorScalar(Op op_)
Definition binary.h:19
-
mlx::core::VectorVector
Definition binary.h:64
-
mlx::core::VectorVector::VectorVector
VectorVector(Op op_)
Definition binary.h:67
-
mlx::core::VectorVector::op
Op op
Definition binary.h:65
-
mlx::core::VectorVector::operator()
void operator()(const T *a, const T *b, U *dst, int size)
Definition binary.h:70
+
mlx::core::ScalarVector
Definition binary.h:35
+
mlx::core::ScalarVector::operator()
void operator()(const T *a, const T *b, U *dst, int size)
Definition binary.h:37
+
mlx::core::VectorScalar
Definition binary.h:15
+
mlx::core::VectorScalar::operator()
void operator()(const T *a, const T *b, U *dst, int size)
Definition binary.h:17
+
mlx::core::VectorVector
Definition binary.h:55
+
mlx::core::VectorVector::operator()
void operator()(const T *a, const T *b, U *dst, int size)
Definition binary.h:57
mlx::core::simd::Simd
Definition accelerate_simd.h:55
diff --git a/docs/build/html/cpu_2binary__two_8h_source.html b/docs/build/html/cpu_2binary__two_8h_source.html index f3ddd5360..84522374e 100644 --- a/docs/build/html/cpu_2binary__two_8h_source.html +++ b/docs/build/html/cpu_2binary__two_8h_source.html @@ -117,7 +117,7 @@ $(function(){initNavTree('cpu_2binary__two_8h_source.html',''); initResizable(tr
10namespace {
11
12template <typename T, typename U, typename Op, int D>
-
13void binary_op_dims(
+
13void binary_op_dims(
14 const T* a,
15 const T* b,
16 U* out_a,
@@ -135,7 +135,7 @@ $(function(){initNavTree('cpu_2binary__two_8h_source.html',''); initResizable(tr
28
29 for (int i = 0; i < N; i++) {
30 if constexpr (D > 1) {
-
31 binary_op_dims<T, U, Op, D - 1>(
+
31 binary_op_dims<T, U, Op, D - 1>(
32 a,
33 b,
34 out_a,
@@ -157,7 +157,7 @@ $(function(){initNavTree('cpu_2binary__two_8h_source.html',''); initResizable(tr
50}
51
52template <typename T, typename U, typename Op>
-
53void binary_op_dispatch_dims(
+
53void binary_op_dispatch_dims(
54 const array& a,
55 const array& b,
56 array& out_a,
@@ -165,18 +165,18 @@ $(function(){initNavTree('cpu_2binary__two_8h_source.html',''); initResizable(tr
58 Op op) {
59 auto [shape, strides] = collapse_contiguous_dims(
60 a.shape(), {a.strides(), b.strides(), out_a.strides()});
-
61 const auto& a_strides = strides[0];
-
62 const auto& b_strides = strides[1];
-
63 const auto& out_strides = strides[2];
-
64 const T* a_ptr = a.data<T>();
-
65 const T* b_ptr = b.data<T>();
-
66 U* out_a_ptr = out_a.data<U>();
-
67 U* out_b_ptr = out_b.data<U>();
-
68
+
61 const T* a_ptr = a.data<T>();
+
62 const T* b_ptr = b.data<T>();
+
63 U* out_a_ptr = out_a.data<U>();
+
64 U* out_b_ptr = out_b.data<U>();
+
65
+
66 const auto& a_strides = strides[0];
+
67 const auto& b_strides = strides[1];
+
68 const auto& out_strides = strides[2];
69 int ndim = shape.size();
70 switch (ndim) {
71 case 1:
-
72 binary_op_dims<T, U, Op, 1>(
+
72 binary_op_dims<T, U, Op, 1>(
73 a_ptr,
74 b_ptr,
75 out_a_ptr,
@@ -189,7 +189,7 @@ $(function(){initNavTree('cpu_2binary__two_8h_source.html',''); initResizable(tr
82 0);
83 return;
84 case 2:
-
85 binary_op_dims<T, U, Op, 2>(
+
85 binary_op_dims<T, U, Op, 2>(
86 a_ptr,
87 b_ptr,
88 out_a_ptr,
@@ -207,7 +207,7 @@ $(function(){initNavTree('cpu_2binary__two_8h_source.html',''); initResizable(tr
100 ContiguousIterator b_it(shape, b_strides, ndim - 2);
101 auto stride = out_strides[ndim - 3];
102 for (size_t elem = 0; elem < a.size(); elem += stride) {
-
103 binary_op_dims<T, U, Op, 2>(
+
103 binary_op_dims<T, U, Op, 2>(
104 a_ptr + a_it.loc,
105 b_ptr + b_it.loc,
106 out_a_ptr + elem,
@@ -224,141 +224,69 @@ $(function(){initNavTree('cpu_2binary__two_8h_source.html',''); initResizable(tr
117}
118
119template <typename T, typename U = T, typename Op>
-
120void binary_op(
+
120void binary_op(
121 const array& a,
122 const array& b,
-
123 std::vector<array>& outputs,
-
124 Op op) {
-
125 auto bopt = get_binary_op_type(a, b);
-
126 auto& out_a = outputs[0];
-
127 auto& out_b = outputs[1];
-
128 set_binary_op_output_data(a, b, out_a, bopt);
-
129 set_binary_op_output_data(a, b, out_b, bopt);
-
130
-
131 // The full computation is scalar scalar so call the base op once
-
132 if (bopt == BinaryOpType::General) {
-
133 binary_op_dispatch_dims<T, U, Op>(a, b, out_a, out_b, op);
-
134 return;
-
135 }
-
136
-
137 auto a_ptr = a.data<T>();
-
138 auto b_ptr = b.data<T>();
-
139 auto out_a_ptr = out_a.data<U>();
-
140 auto out_b_ptr = out_b.data<U>();
-
141 if (bopt == BinaryOpType::ScalarScalar) {
-
142 std::tie(*out_a_ptr, *out_b_ptr) = op(*a_ptr, *b_ptr);
-
143 } else if (bopt == BinaryOpType::ScalarVector) {
-
144 for (size_t i = 0; i < b.size(); ++i) {
-
145 std::tie(*out_a_ptr, *out_b_ptr) = op(*a_ptr, *b_ptr);
-
146 out_a_ptr++;
-
147 out_b_ptr++;
-
148 b_ptr++;
-
149 }
-
150 } else if (bopt == BinaryOpType::VectorScalar) {
-
151 for (size_t i = 0; i < a.size(); ++i) {
-
152 std::tie(*out_a_ptr, *out_b_ptr) = op(*a_ptr, *b_ptr);
-
153 out_a_ptr++;
-
154 out_b_ptr++;
-
155 a_ptr++;
-
156 }
-
157 } else { // VectorVector
-
158 for (size_t i = 0; i < a.size(); ++i) {
-
159 std::tie(*out_a_ptr, *out_b_ptr) = op(*a_ptr, *b_ptr);
-
160 out_a_ptr++;
-
161 out_b_ptr++;
-
162 a_ptr++;
-
163 b_ptr++;
-
164 }
-
165 }
-
166}
-
167
-
168template <typename Op>
-
169void binary(
-
170 const array& a,
-
171 const array& b,
-
172 std::vector<array>& outputs,
-
173 Op op) {
-
174 switch (outputs[0].dtype()) {
-
175 case bool_:
-
176 binary_op<bool>(a, b, outputs, op);
-
177 break;
-
178 case uint8:
-
179 binary_op<uint8_t>(a, b, outputs, op);
-
180 break;
-
181 case uint16:
-
182 binary_op<uint16_t>(a, b, outputs, op);
-
183 break;
-
184 case uint32:
-
185 binary_op<uint32_t>(a, b, outputs, op);
-
186 break;
-
187 case uint64:
-
188 binary_op<uint64_t>(a, b, outputs, op);
-
189 break;
-
190 case int8:
-
191 binary_op<int8_t>(a, b, outputs, op);
-
192 break;
-
193 case int16:
-
194 binary_op<int16_t>(a, b, outputs, op);
-
195 break;
-
196 case int32:
-
197 binary_op<int32_t>(a, b, outputs, op);
-
198 break;
-
199 case int64:
-
200 binary_op<int64_t>(a, b, outputs, op);
-
201 break;
-
202 case float16:
-
203 binary_op<float16_t>(a, b, outputs, op);
-
204 break;
-
205 case float32:
-
206 binary_op<float>(a, b, outputs, op);
-
207 break;
-
208 case float64:
-
209 binary_op<double>(a, b, outputs, op);
-
210 break;
-
211 case bfloat16:
-
212 binary_op<bfloat16_t>(a, b, outputs, op);
-
213 break;
-
214 case complex64:
-
215 binary_op<complex64_t>(a, b, outputs, op);
-
216 break;
-
217 }
-
218}
-
219
-
220} // namespace
-
221
-
222} // namespace mlx::core
+
123 array& out_a,
+
124 array& out_b,
+
125 Op op,
+
126 BinaryOpType bopt) {
+
127 // The full computation is scalar scalar so call the base op once
+
128 if (bopt == BinaryOpType::General) {
+
129 binary_op_dispatch_dims<T, U, Op>(a, b, out_a, out_b, op);
+
130 return;
+
131 }
+
132
+
133 auto a_ptr = a.data<T>();
+
134 auto b_ptr = b.data<T>();
+
135 auto out_a_ptr = out_a.data<U>();
+
136 auto out_b_ptr = out_b.data<U>();
+
137 if (bopt == BinaryOpType::ScalarScalar) {
+
138 std::tie(*out_a_ptr, *out_b_ptr) = op(*a_ptr, *b_ptr);
+
139 } else if (bopt == BinaryOpType::ScalarVector) {
+
140 for (size_t i = 0; i < b.data_size(); ++i) {
+
141 std::tie(*out_a_ptr, *out_b_ptr) = op(*a_ptr, *b_ptr);
+
142 out_a_ptr++;
+
143 out_b_ptr++;
+
144 b_ptr++;
+
145 }
+
146 } else if (bopt == BinaryOpType::VectorScalar) {
+
147 for (size_t i = 0; i < a.data_size(); ++i) {
+
148 std::tie(*out_a_ptr, *out_b_ptr) = op(*a_ptr, *b_ptr);
+
149 out_a_ptr++;
+
150 out_b_ptr++;
+
151 a_ptr++;
+
152 }
+
153 } else { // VectorVector
+
154 for (size_t i = 0; i < a.size(); ++i) {
+
155 std::tie(*out_a_ptr, *out_b_ptr) = op(*a_ptr, *b_ptr);
+
156 out_a_ptr++;
+
157 out_b_ptr++;
+
158 a_ptr++;
+
159 b_ptr++;
+
160 }
+
161 }
+
162}
+
163
+
164} // namespace
+
165
+
166} // namespace mlx::core
mlx::core::array
Definition array.h:24
mlx::core::simd::N
constexpr int N
Definition neon_fp16_simd.h:9
mlx::core
Definition allocator.h:7
-
mlx::core::bool_
constexpr Dtype bool_
Definition dtype.h:68
-
mlx::core::uint64
constexpr Dtype uint64
Definition dtype.h:73
-
mlx::core::get_binary_op_type
BinaryOpType get_binary_op_type(const array &a, const array &b)
Definition binary.h:19
-
mlx::core::uint16
constexpr Dtype uint16
Definition dtype.h:71
-
mlx::core::float64
constexpr Dtype float64
Definition dtype.h:82
mlx::core::collapse_contiguous_dims
std::tuple< Shape, std::vector< Strides > > collapse_contiguous_dims(const Shape &shape, const std::vector< Strides > &strides, int64_t size_cap=std::numeric_limits< int32_t >::max())
-
mlx::core::bfloat16
constexpr Dtype bfloat16
Definition dtype.h:83
+
mlx::core::BinaryOpType
BinaryOpType
Definition binary.h:11
mlx::core::BinaryOpType::General
@ General
Definition binary.h:16
mlx::core::BinaryOpType::ScalarScalar
@ ScalarScalar
Definition binary.h:12
mlx::core::BinaryOpType::VectorScalar
@ VectorScalar
Definition binary.h:14
mlx::core::BinaryOpType::ScalarVector
@ ScalarVector
Definition binary.h:13
-
mlx::core::int32
constexpr Dtype int32
Definition dtype.h:77
-
mlx::core::binary_op_dispatch_dims
void binary_op_dispatch_dims(const array &a, const array &b, array &out, Op op, int dim, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides)
Definition binary.h:122
-
mlx::core::float32
constexpr Dtype float32
Definition dtype.h:81
mlx::core::Shape
std::vector< ShapeElem > Shape
Definition array.h:21
-
mlx::core::set_binary_op_output_data
void set_binary_op_output_data(const array &a, const array &b, array &out, BinaryOpType bopt, bool donate_with_move=false)
Definition binary.h:37
-
mlx::core::int16
constexpr Dtype int16
Definition dtype.h:76
mlx::core::Strides
std::vector< int64_t > Strides
Definition array.h:22
-
mlx::core::binary_op_dims
void binary_op_dims(const T *a, const T *b, U *out, Op op, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides, int axis)
Definition binary.h:89
-
mlx::core::int8
constexpr Dtype int8
Definition dtype.h:75
-
mlx::core::int64
constexpr Dtype int64
Definition dtype.h:78
-
mlx::core::uint8
constexpr Dtype uint8
Definition dtype.h:70
-
mlx::core::binary_op
void binary_op(const array &a, const array &b, array &out, Op op)
Definition binary.h:194
-
mlx::core::float16
constexpr Dtype float16
Definition dtype.h:80
-
mlx::core::uint32
constexpr Dtype uint32
Definition dtype.h:72
-
mlx::core::binary
void binary(const array &a, const array &b, array &out, Op op)
Definition binary.h:326
-
mlx::core::complex64
constexpr Dtype complex64
Definition dtype.h:84
+
mlx::core::binary_op_dispatch_dims
void binary_op_dispatch_dims(const T *a, const T *b, U *out, int dim, int size, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides)
Definition binary.h:108
+
mlx::core::binary_op
void binary_op(const array &a, const array &b, array &out, BinaryOpType bopt)
Definition binary.h:152
+
mlx::core::binary_op_dims
void binary_op_dims(const T *a, const T *b, U *out, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides, int axis)
Definition binary.h:76
mlx::core::ContiguousIterator
Definition utils.h:73
diff --git a/docs/build/html/cpu_2copy_8h.html b/docs/build/html/cpu_2copy_8h.html index de69b295f..d938473b0 100644 --- a/docs/build/html/cpu_2copy_8h.html +++ b/docs/build/html/cpu_2copy_8h.html @@ -108,7 +108,8 @@ $(function(){initNavTree('cpu_2copy_8h.html',''); initResizable(true); });
copy.h File Reference
-
#include "mlx/array.h"
+
#include <optional>
+#include "mlx/array.h"
#include "mlx/backend/common/copy.h"
#include "mlx/backend/common/utils.h"
@@ -123,12 +124,12 @@ Namespaces - - - - - - + + + + + +

Functions

void mlx::core::copy (const array &src, array &dst, CopyType ctype)
 
void mlx::core::copy_inplace (const array &src, array &dst, CopyType ctype)
 
void mlx::core::copy_inplace (const array &src, array &dst, const Shape &data_shape, const Strides &i_strides, const Strides &o_strides, int64_t i_offset, int64_t o_offset, CopyType ctype)
 
void mlx::core::copy (const array &src, array &dst, CopyType ctype, Stream stream)
 
void mlx::core::copy_inplace (const array &src, array &dst, CopyType ctype, Stream stream)
 
void mlx::core::copy_inplace (const array &src, array &dst, const Shape &data_shape, const Strides &i_strides, const Strides &o_strides, int64_t i_offset, int64_t o_offset, CopyType ctype, Stream stream, const std::optional< array > &dynamic_i_offset=std::nullopt, const std::optional< array > &dynamic_o_offset=std::nullopt)
 
diff --git a/docs/build/html/cpu_2copy_8h.js b/docs/build/html/cpu_2copy_8h.js index c9361c23b..a0339a06a 100644 --- a/docs/build/html/cpu_2copy_8h.js +++ b/docs/build/html/cpu_2copy_8h.js @@ -1,6 +1,6 @@ var cpu_2copy_8h = [ - [ "mlx::core::copy", "namespacemlx_1_1core.html#a479648542a2bea151b947b18f0e79dd2", null ], - [ "mlx::core::copy_inplace", "namespacemlx_1_1core.html#ae85bafda5ab0b4b2289591260cf07685", null ], - [ "mlx::core::copy_inplace", "namespacemlx_1_1core.html#a98495894a796b2cc6d022e7a03432c64", null ] + [ "mlx::core::copy", "namespacemlx_1_1core.html#a017bd8bd743e26f1ff971c8749b55daf", null ], + [ "mlx::core::copy_inplace", "namespacemlx_1_1core.html#a1e4381d42877a5c6050c20e77d13c990", null ], + [ "mlx::core::copy_inplace", "namespacemlx_1_1core.html#ab30708325761c91e7dde245827e9dd91", null ] ]; \ No newline at end of file diff --git a/docs/build/html/cpu_2copy_8h_source.html b/docs/build/html/cpu_2copy_8h_source.html index f2839828e..0a2c78ac3 100644 --- a/docs/build/html/cpu_2copy_8h_source.html +++ b/docs/build/html/cpu_2copy_8h_source.html @@ -109,36 +109,42 @@ $(function(){initNavTree('cpu_2copy_8h_source.html',''); initResizable(true); })
2
3#pragma once
4
-
5#include "mlx/array.h"
-
6#include "mlx/backend/common/copy.h"
-
7#include "mlx/backend/common/utils.h"
-
8
-
9namespace mlx::core {
+
5#include <optional>
+
6
+
7#include "mlx/array.h"
+
8#include "mlx/backend/common/copy.h"
+
9#include "mlx/backend/common/utils.h"
10
-
11void copy(const array& src, array& dst, CopyType ctype);
-
12void copy_inplace(const array& src, array& dst, CopyType ctype);
-
13
-
14void copy_inplace(
-
15 const array& src,
-
16 array& dst,
-
17 const Shape& data_shape,
-
18 const Strides& i_strides,
-
19 const Strides& o_strides,
-
20 int64_t i_offset,
-
21 int64_t o_offset,
-
22 CopyType ctype);
-
23
-
24} // namespace mlx::core
+
11namespace mlx::core {
+
12
+
13void copy(const array& src, array& dst, CopyType ctype, Stream stream);
+
14void copy_inplace(const array& src, array& dst, CopyType ctype, Stream stream);
+
15
+
16void copy_inplace(
+
17 const array& src,
+
18 array& dst,
+
19 const Shape& data_shape,
+
20 const Strides& i_strides,
+
21 const Strides& o_strides,
+
22 int64_t i_offset,
+
23 int64_t o_offset,
+
24 CopyType ctype,
+
25 Stream stream,
+
26 const std::optional<array>& dynamic_i_offset = std::nullopt,
+
27 const std::optional<array>& dynamic_o_offset = std::nullopt);
+
28
+
29} // namespace mlx::core
mlx::core::array
Definition array.h:24
mlx::core
Definition allocator.h:7
-
mlx::core::copy
void copy(const array &src, array &dst, CopyType ctype)
+
mlx::core::copy
void copy(const array &src, array &dst, CopyType ctype, Stream stream)
mlx::core::Shape
std::vector< ShapeElem > Shape
Definition array.h:21
mlx::core::Strides
std::vector< int64_t > Strides
Definition array.h:22
-
mlx::core::copy_inplace
void copy_inplace(const array &src, array &dst, CopyType ctype)
+
mlx::core::copy_inplace
void copy_inplace(const array &src, array &dst, CopyType ctype, Stream stream)
mlx::core::CopyType
CopyType
Definition copy.h:9
+
mlx::core::Stream
Definition stream.h:9
diff --git a/docs/build/html/cpu_2gemm_8h.html b/docs/build/html/cpu_2gemm_8h.html index 6a41765ea..7a5fc6c1b 100644 --- a/docs/build/html/cpu_2gemm_8h.html +++ b/docs/build/html/cpu_2gemm_8h.html @@ -121,9 +121,9 @@ Namespaces - - - + + +

Functions

template<typename T>
void mlx::core::matmul (const array &a, const array &b, array &out, bool a_transposed, bool b_transposed, size_t lda, size_t ldb, float alpha, float beta)
 
template<typename T>
void mlx::core::matmul (const T *a, const T *b, T *out, bool a_transposed, bool b_transposed, size_t lda, size_t ldb, size_t ldc, float alpha, float beta, size_t batch_size, const Shape &a_shape, const Strides &a_strides, const Shape &b_shape, const Strides &b_strides)
 
diff --git a/docs/build/html/cpu_2gemm_8h.js b/docs/build/html/cpu_2gemm_8h.js index 4b39c7431..5ac1cb352 100644 --- a/docs/build/html/cpu_2gemm_8h.js +++ b/docs/build/html/cpu_2gemm_8h.js @@ -1,4 +1,4 @@ var cpu_2gemm_8h = [ - [ "mlx::core::matmul", "namespacemlx_1_1core.html#aaacf0afe13d77a5c49ce96f1e833eb2d", null ] + [ "mlx::core::matmul", "namespacemlx_1_1core.html#afd07258882634dcda1e6f18f10dc28d5", null ] ]; \ No newline at end of file diff --git a/docs/build/html/cpu_2gemm_8h_source.html b/docs/build/html/cpu_2gemm_8h_source.html index 6ccfed1c7..a320b421f 100644 --- a/docs/build/html/cpu_2gemm_8h_source.html +++ b/docs/build/html/cpu_2gemm_8h_source.html @@ -113,22 +113,29 @@ $(function(){initNavTree('cpu_2gemm_8h_source.html',''); initResizable(true); })
6namespace mlx::core {
7
8template <typename T>
-
9void matmul(
-
10 const array& a,
-
11 const array& b,
-
12 array& out,
+
9void matmul(
+
10 const T* a,
+
11 const T* b,
+
12 T* out,
13 bool a_transposed,
14 bool b_transposed,
15 size_t lda,
16 size_t ldb,
-
17 float alpha,
-
18 float beta);
-
19
-
20} // namespace mlx::core
+
17 size_t ldc,
+
18 float alpha,
+
19 float beta,
+
20 size_t batch_size,
+
21 const Shape& a_shape,
+
22 const Strides& a_strides,
+
23 const Shape& b_shape,
+
24 const Strides& b_strides);
+
25
+
26} // namespace mlx::core
-
mlx::core::array
Definition array.h:24
mlx::core
Definition allocator.h:7
-
mlx::core::matmul
void matmul(const array &a, const array &b, array &out, bool a_transposed, bool b_transposed, size_t lda, size_t ldb, float alpha, float beta)
+
mlx::core::Shape
std::vector< ShapeElem > Shape
Definition array.h:21
+
mlx::core::Strides
std::vector< int64_t > Strides
Definition array.h:22
+
mlx::core::matmul
void matmul(const T *a, const T *b, T *out, bool a_transposed, bool b_transposed, size_t lda, size_t ldb, size_t ldc, float alpha, float beta, size_t batch_size, const Shape &a_shape, const Strides &a_strides, const Shape &b_shape, const Strides &b_strides)
diff --git a/docs/build/html/cpu_2ternary_8h.html b/docs/build/html/cpu_2ternary_8h.html index 4214ae3c0..2f68c2531 100644 --- a/docs/build/html/cpu_2ternary_8h.html +++ b/docs/build/html/cpu_2ternary_8h.html @@ -108,10 +108,10 @@ $(function(){initNavTree('cpu_2ternary_8h.html',''); initResizable(true); });
ternary.h File Reference
-
#include "mlx/allocator.h"
-#include "mlx/array.h"
+
#include "mlx/array.h"
#include "mlx/backend/common/ternary.h"
#include "mlx/backend/common/utils.h"
+#include "mlx/backend/cpu/encoder.h"

Go to the source code of this file.

@@ -127,12 +127,12 @@ Functions - - - - - - + + + + + +
template<typename T1, typename T2, typename T3, typename U, typename Op, int D>
void mlx::core::ternary_op_dims (const T1 *a, const T2 *b, const T3 *c, U *out, Op op, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &c_strides, const Strides &out_strides, int axis)
 
template<typename T1, typename T2, typename T3, typename U, typename Op>
void mlx::core::ternary_op_dispatch_dims (const array &a, const array &b, const array &c, array &out, Op op)
 
template<typename T1, typename T2, typename T3, typename U, typename Op>
void mlx::core::ternary_op (const array &a, const array &b, const array &c, array &out, Op op)
 
template<typename T1, typename T2, typename T3, typename U, typename Op>
void mlx::core::ternary_op_dispatch_dims (const T1 *a_ptr, const T2 *b_ptr, const T3 *c_ptr, U *out_ptr, Op op, size_t size, Shape &shape, std::vector< Strides > &strides)
 
template<typename T1, typename T2, typename T3, typename U, typename Op>
void mlx::core::ternary_op (const array &a, const array &b, const array &c, array &out, Op op, TernaryOpType topt)
 
diff --git a/docs/build/html/cpu_2ternary_8h.js b/docs/build/html/cpu_2ternary_8h.js index 8a6129550..b80a4728c 100644 --- a/docs/build/html/cpu_2ternary_8h.js +++ b/docs/build/html/cpu_2ternary_8h.js @@ -1,6 +1,6 @@ var cpu_2ternary_8h = [ - [ "mlx::core::ternary_op", "namespacemlx_1_1core.html#a9dcc3018702ee31c21c8652bdc2182b1", null ], + [ "mlx::core::ternary_op", "namespacemlx_1_1core.html#a48fbbd43d2165ab7f42bac3f228bbda3", null ], [ "mlx::core::ternary_op_dims", "namespacemlx_1_1core.html#a8096c7a688ac3f09cca69a3a85f7f157", null ], - [ "mlx::core::ternary_op_dispatch_dims", "namespacemlx_1_1core.html#ac1c085e305954247d042f5d8803cd85b", null ] + [ "mlx::core::ternary_op_dispatch_dims", "namespacemlx_1_1core.html#a9abcc6efafd9ab5df1293b1793a734d2", null ] ]; \ No newline at end of file diff --git a/docs/build/html/cpu_2ternary_8h_source.html b/docs/build/html/cpu_2ternary_8h_source.html index 40361d521..b168d3e8e 100644 --- a/docs/build/html/cpu_2ternary_8h_source.html +++ b/docs/build/html/cpu_2ternary_8h_source.html @@ -108,10 +108,10 @@ $(function(){initNavTree('cpu_2ternary_8h_source.html',''); initResizable(true); Go to the documentation of this file.
1// Copyright © 2023 Apple Inc.
2
3#pragma once
-
4#include "mlx/allocator.h"
-
5#include "mlx/array.h"
-
6#include "mlx/backend/common/ternary.h"
-
7#include "mlx/backend/common/utils.h"
+
4#include "mlx/array.h"
+
5#include "mlx/backend/common/ternary.h"
+
6#include "mlx/backend/common/utils.h"
+
7#include "mlx/backend/cpu/encoder.h"
8
9namespace mlx::core {
10
@@ -162,129 +162,124 @@ $(function(){initNavTree('cpu_2ternary_8h_source.html',''); initResizable(true);
53
54template <typename T1, typename T2, typename T3, typename U, typename Op>
-
55void ternary_op_dispatch_dims(
-
56 const array& a,
-
57 const array& b,
-
58 const array& c,
-
59 array& out,
-
60 Op op) {
-
61 auto [shape, strides] = collapse_contiguous_dims(
-
62 a.shape(), {a.strides(), b.strides(), c.strides(), out.strides()});
-
63 const auto& a_strides = strides[0];
-
64 const auto& b_strides = strides[1];
-
65 const auto& c_strides = strides[2];
-
66 const auto& out_strides = strides[3];
-
67
-
68 const T1* a_ptr = a.data<T1>();
-
69 const T2* b_ptr = b.data<T2>();
-
70 const T3* c_ptr = c.data<T3>();
-
71 U* out_ptr = out.data<T3>();
-
72 int ndim = shape.size();
-
73 switch (ndim) {
-
74 case 1:
-
75 ternary_op_dims<T1, T2, T3, U, Op, 1>(
-
76 a_ptr,
-
77 b_ptr,
-
78 c_ptr,
-
79 out_ptr,
-
80 op,
-
81 shape,
-
82 a_strides,
-
83 b_strides,
-
84 c_strides,
-
85 out_strides,
-
86 0);
-
87 return;
-
88 case 2:
-
89 ternary_op_dims<T1, T2, T3, U, Op, 2>(
-
90 a_ptr,
-
91 b_ptr,
-
92 c_ptr,
-
93 out_ptr,
-
94 op,
-
95 shape,
-
96 a_strides,
-
97 b_strides,
-
98 c_strides,
-
99 out_strides,
-
100 0);
-
101 return;
-
102 }
-
103
-
104 ContiguousIterator a_it(shape, a_strides, ndim - 2);
-
105 ContiguousIterator b_it(shape, b_strides, ndim - 2);
-
106 ContiguousIterator c_it(shape, c_strides, ndim - 2);
-
107 auto stride = out_strides[ndim - 3];
-
108 for (size_t elem = 0; elem < a.size(); elem += stride) {
-
109 ternary_op_dims<T1, T2, T3, U, Op, 2>(
-
110 a_ptr + a_it.loc,
-
111 b_ptr + b_it.loc,
-
112 c_ptr + c_it.loc,
-
113 out_ptr + elem,
-
114 op,
-
115 shape,
-
116 a_strides,
-
117 b_strides,
-
118 c_strides,
-
119 out_strides,
-
120 ndim - 2);
-
121 a_it.step();
-
122 b_it.step();
-
123 c_it.step();
-
124 }
-
125}
+
55void ternary_op_dispatch_dims(
+
56 const T1* a_ptr,
+
57 const T2* b_ptr,
+
58 const T3* c_ptr,
+
59 U* out_ptr,
+
60 Op op,
+
61 size_t size,
+
62 Shape& shape,
+
63 std::vector<Strides>& strides) {
+
64 const auto& a_strides = strides[0];
+
65 const auto& b_strides = strides[1];
+
66 const auto& c_strides = strides[2];
+
67 const auto& out_strides = strides[3];
+
68 int ndim = shape.size();
+
69 switch (ndim) {
+
70 case 1:
+
71 ternary_op_dims<T1, T2, T3, U, Op, 1>(
+
72 a_ptr,
+
73 b_ptr,
+
74 c_ptr,
+
75 out_ptr,
+
76 op,
+
77 shape,
+
78 a_strides,
+
79 b_strides,
+
80 c_strides,
+
81 out_strides,
+
82 0);
+
83 return;
+
84 case 2:
+
85 ternary_op_dims<T1, T2, T3, U, Op, 2>(
+
86 a_ptr,
+
87 b_ptr,
+
88 c_ptr,
+
89 out_ptr,
+
90 op,
+
91 shape,
+
92 a_strides,
+
93 b_strides,
+
94 c_strides,
+
95 out_strides,
+
96 0);
+
97 return;
+
98 }
+
99
+
100 ContiguousIterator a_it(shape, a_strides, ndim - 2);
+
101 ContiguousIterator b_it(shape, b_strides, ndim - 2);
+
102 ContiguousIterator c_it(shape, c_strides, ndim - 2);
+
103 auto stride = out_strides[ndim - 3];
+
104 for (size_t elem = 0; elem < size; elem += stride) {
+
105 ternary_op_dims<T1, T2, T3, U, Op, 2>(
+
106 a_ptr + a_it.loc,
+
107 b_ptr + b_it.loc,
+
108 c_ptr + c_it.loc,
+
109 out_ptr + elem,
+
110 op,
+
111 shape,
+
112 a_strides,
+
113 b_strides,
+
114 c_strides,
+
115 out_strides,
+
116 ndim - 2);
+
117 a_it.step();
+
118 b_it.step();
+
119 c_it.step();
+
120 }
+
121}
-
126
-
127template <typename T1, typename T2, typename T3, typename U, typename Op>
-
-
128void ternary_op(
-
129 const array& a,
-
130 const array& b,
-
131 const array& c,
-
132 array& out,
-
133 Op op) {
-
134 TernaryOpType topt = get_ternary_op_type(a, b, c);
-
135 set_ternary_op_output_data(a, b, c, out, topt);
-
136
-
137 // The full computation is scalar-scalar-scalar so we call the base op once.
-
138 if (topt == TernaryOpType::ScalarScalarScalar) {
-
139 *(out.data<U>()) = op(*a.data<T1>(), *b.data<T2>(), *c.data<T3>());
-
140 } else if (topt == TernaryOpType::VectorVectorVector) {
-
141 const T1* a_ptr = a.data<T1>();
-
142 const T2* b_ptr = b.data<T2>();
-
143 const T3* c_ptr = c.data<T3>();
-
144 U* out_ptr = out.data<U>();
-
145 for (size_t i = 0; i < out.size(); ++i) {
-
146 *out_ptr = op(*a_ptr, *b_ptr, *c_ptr);
-
147 a_ptr++;
-
148 b_ptr++;
-
149 c_ptr++;
-
150 out_ptr++;
-
151 }
-
152 } else {
-
153 ternary_op_dispatch_dims<T1, T2, T3, U>(a, b, c, out, op);
-
154 }
-
155}
+
122
+
123template <typename T1, typename T2, typename T3, typename U, typename Op>
+
+
124void ternary_op(
+
125 const array& a,
+
126 const array& b,
+
127 const array& c,
+
128 array& out,
+
129 Op op,
+
130 TernaryOpType topt) {
+
131 const T1* a_ptr = a.data<T1>();
+
132 const T2* b_ptr = b.data<T2>();
+
133 const T3* c_ptr = c.data<T3>();
+
134 U* out_ptr = out.data<U>();
+
135
+
136 if (topt == TernaryOpType::ScalarScalarScalar) {
+
137 *out_ptr = op(*a_ptr, *b_ptr, *c_ptr);
+
138 } else if (topt == TernaryOpType::VectorVectorVector) {
+
139 for (size_t i = 0; i < out.size(); ++i) {
+
140 *out_ptr = op(*a_ptr, *b_ptr, *c_ptr);
+
141 a_ptr++;
+
142 b_ptr++;
+
143 c_ptr++;
+
144 out_ptr++;
+
145 }
+
146 } else {
+
147 auto [shape, strides] = collapse_contiguous_dims(
+
148 a.shape(), {a.strides(), b.strides(), c.strides(), out.strides()});
+
149 ternary_op_dispatch_dims<T1, T2, T3, U>(
+
150 a_ptr, b_ptr, c_ptr, out_ptr, op, out.size(), shape, strides);
+
151 }
+
152}
-
156
-
157} // namespace mlx::core
- +
153
+
154} // namespace mlx::core
mlx::core::array
Definition array.h:24
mlx::core::array::shape
const Shape & shape() const
The shape of the array as a vector of integers.
Definition array.h:103
mlx::core::array::size
size_t size() const
The number of elements in the array.
Definition array.h:88
-
mlx::core::array::data
T * data()
Definition array.h:354
+
mlx::core::array::data
T * data()
Definition array.h:349
+
mlx::core
Definition allocator.h:7
+
mlx::core::ternary_op
void ternary_op(const array &a, const array &b, const array &c, array &out, Op op, TernaryOpType topt)
Definition ternary.h:124
mlx::core::collapse_contiguous_dims
std::tuple< Shape, std::vector< Strides > > collapse_contiguous_dims(const Shape &shape, const std::vector< Strides > &strides, int64_t size_cap=std::numeric_limits< int32_t >::max())
-
mlx::core::get_ternary_op_type
TernaryOpType get_ternary_op_type(const array &a, const array &b, const array &c)
Definition ternary.h:18
mlx::core::Shape
std::vector< ShapeElem > Shape
Definition array.h:21
-
mlx::core::set_ternary_op_output_data
void set_ternary_op_output_data(const array &a, const array &b, const array &c, array &out, TernaryOpType topt, bool donate_with_move=false)
Definition ternary.h:34
mlx::core::Strides
std::vector< int64_t > Strides
Definition array.h:22
mlx::core::ternary_op_dims
void ternary_op_dims(const T1 *a, const T2 *b, const T3 *c, U *out, Op op, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &c_strides, const Strides &out_strides, int axis)
Definition ternary.h:12
-
mlx::core::ternary_op
void ternary_op(const array &a, const array &b, const array &c, array &out, Op op)
Definition ternary.h:128
-
mlx::core::ternary_op_dispatch_dims
void ternary_op_dispatch_dims(const array &a, const array &b, const array &c, array &out, Op op)
Definition ternary.h:55
+
mlx::core::ternary_op_dispatch_dims
void ternary_op_dispatch_dims(const T1 *a_ptr, const T2 *b_ptr, const T3 *c_ptr, U *out_ptr, Op op, size_t size, Shape &shape, std::vector< Strides > &strides)
Definition ternary.h:55
mlx::core::TernaryOpType
TernaryOpType
Definition ternary.h:11
mlx::core::TernaryOpType::ScalarScalarScalar
@ ScalarScalarScalar
Definition ternary.h:12
mlx::core::TernaryOpType::VectorVectorVector
@ VectorVectorVector
Definition ternary.h:13
diff --git a/docs/build/html/cpu_2unary_8h.html b/docs/build/html/cpu_2unary_8h.html index d797ec193..039444896 100644 --- a/docs/build/html/cpu_2unary_8h.html +++ b/docs/build/html/cpu_2unary_8h.html @@ -111,6 +111,7 @@ $(function(){initNavTree('cpu_2unary_8h.html',''); initResizable(true); });
#include "mlx/allocator.h"
#include "mlx/array.h"
#include "mlx/backend/common/utils.h"
+#include "mlx/backend/cpu/encoder.h"
#include "mlx/backend/cpu/simd/simd.h"
#include "mlx/utils.h"
@@ -127,21 +128,33 @@ Namespaces Functions void mlx::core::set_unary_output_data (const array &in, array &out)   -template<typename T, typename U = T, typename Op> -void mlx::core::unary_op (const T *a, U *out, Op op, size_t shape, size_t stride) -  -template<typename T, typename U = T, typename Op> -void mlx::core::unary_op (const array &a, array &out, Op op) -  -template<typename Op> -void mlx::core::unary (const array &a, array &out, Op op) -  -template<typename Op> -void mlx::core::unary_fp (const array &a, array &out, Op op) -  -template<typename Op> -void mlx::core::unary_int (const array &a, array &out, Op op) -  +template<typename T, typename U = T, typename Op> +void mlx::core::unary_op (const T *a, U *out, size_t shape, size_t stride) +  +template<typename T, typename U = T, typename Op> +void mlx::core::unary_op (const array &a, array &out, Op) +  +template<typename Op> +void mlx::core::unary (const array &a, array &out, Op op, Stream stream) +  +template<typename Op> +void mlx::core::unary_real_fp (const array &a, array &out, Op op, Stream stream) +  +template<typename Op> +void mlx::core::unary_fp (const array &a, array &out, Op op, Stream stream) +  +template<typename Op> +void mlx::core::unary_signed (const array &a, array &out, Op op, Stream stream) +  +template<typename Op> +void mlx::core::unary_complex (const array &a, array &out, Op op, Stream stream) +  +template<typename Op> +void mlx::core::unary_complex_to_float (const array &a, array &out, Op op, Stream stream) +  +template<typename Op> +void mlx::core::unary_int (const array &a, array &out, Op op, Stream stream) + 
diff --git a/docs/build/html/cpu_2unary_8h.js b/docs/build/html/cpu_2unary_8h.js index fdc54690d..577a7afd9 100644 --- a/docs/build/html/cpu_2unary_8h.js +++ b/docs/build/html/cpu_2unary_8h.js @@ -1,9 +1,13 @@ var cpu_2unary_8h = [ [ "mlx::core::set_unary_output_data", "namespacemlx_1_1core.html#a4c6a4241bfcdd7bbf30d0e521b79e5a3", null ], - [ "mlx::core::unary", "namespacemlx_1_1core.html#a6c8fdd03ef891d7f47804bf02e9a8507", null ], - [ "mlx::core::unary_fp", "namespacemlx_1_1core.html#a76a2cb4634f5fd6970a8c3b3753d7a4a", null ], - [ "mlx::core::unary_int", "namespacemlx_1_1core.html#a078859db0d66ff77f97af6dc9764e8eb", null ], - [ "mlx::core::unary_op", "namespacemlx_1_1core.html#ae20f207ad1ed3badc17cecf08f118b5e", null ], - [ "mlx::core::unary_op", "namespacemlx_1_1core.html#a27f00519f9756896734fd4d47fec0625", null ] + [ "mlx::core::unary", "namespacemlx_1_1core.html#a0f3ff0f676d28840c210ef6277caa546", null ], + [ "mlx::core::unary_complex", "namespacemlx_1_1core.html#a9af588b2e7f4e5249cd8b7722ad829c0", null ], + [ "mlx::core::unary_complex_to_float", "namespacemlx_1_1core.html#a0640d1f5bcd9a4f5cdaea9f197a53515", null ], + [ "mlx::core::unary_fp", "namespacemlx_1_1core.html#a6c1b92aea938457e44f93a7955d22823", null ], + [ "mlx::core::unary_int", "namespacemlx_1_1core.html#a50536365b8bcfec55e7d023ae9a6395c", null ], + [ "mlx::core::unary_op", "namespacemlx_1_1core.html#ab9812785763451ceb86486032d614048", null ], + [ "mlx::core::unary_op", "namespacemlx_1_1core.html#aa6b3dfc27a21d26b3fda96022aa60e32", null ], + [ "mlx::core::unary_real_fp", "namespacemlx_1_1core.html#a940f998c7469d14f5234f78dcaecd48b", null ], + [ "mlx::core::unary_signed", "namespacemlx_1_1core.html#aed2b5550f8424094ef10bdadfe92ec0f", null ] ]; \ No newline at end of file diff --git a/docs/build/html/cpu_2unary_8h_source.html b/docs/build/html/cpu_2unary_8h_source.html index c7dcf23fb..c403d250e 100644 --- a/docs/build/html/cpu_2unary_8h_source.html +++ b/docs/build/html/cpu_2unary_8h_source.html @@ -112,235 +112,371 @@ $(function(){initNavTree('cpu_2unary_8h_source.html',''); initResizable(true); }
5#include "mlx/allocator.h"
6#include "mlx/array.h"
7#include "mlx/backend/common/utils.h"
-
8#include "mlx/backend/cpu/simd/simd.h"
-
9#include "mlx/utils.h"
-
10
-
11namespace mlx::core {
-
12
-
-
13void set_unary_output_data(const array& in, array& out) {
-
14 if (is_donatable(in, out)) {
-
15 out.copy_shared_buffer(in);
-
16 } else {
-
17 auto size = in.data_size();
-
18 out.set_data(
-
19 allocator::malloc_or_wait(size * out.itemsize()),
-
20 size,
-
21 in.strides(),
-
22 in.flags());
-
23 }
-
24}
+
8#include "mlx/backend/cpu/encoder.h"
+
9#include "mlx/backend/cpu/simd/simd.h"
+
10#include "mlx/utils.h"
+
11
+
12namespace mlx::core {
+
13
+
+
14void set_unary_output_data(const array& in, array& out) {
+
15 if (in.flags().contiguous) {
+
16 if (is_donatable(in, out)) {
+
17 out.copy_shared_buffer(in);
+
18 } else {
+
19 auto size = in.data_size();
+
20 out.set_data(
+
21 allocator::malloc_or_wait(size * out.itemsize()),
+
22 size,
+
23 in.strides(),
+
24 in.flags());
+
25 }
+
26 } else {
+
27 out.set_data(allocator::malloc_or_wait(out.nbytes()));
+
28 }
+
29}
-
25
-
26template <typename T, typename U = T, typename Op>
-
-
27void unary_op(const T* a, U* out, Op op, size_t shape, size_t stride) {
-
28 for (size_t i = 0; i < shape; i += 1) {
-
29 out[i] = op(*a);
-
30 a += stride;
-
31 }
-
32}
+
30
+
31template <typename T, typename U = T, typename Op>
+
+
32void unary_op(const T* a, U* out, size_t shape, size_t stride) {
+
33 for (size_t i = 0; i < shape; i += 1) {
+
34 out[i] = Op{}(*a);
+
35 a += stride;
+
36 }
+
37}
-
33
-
34template <typename T, typename U = T, typename Op>
-
-
35void unary_op(const array& a, array& out, Op op) {
-
36 const T* a_ptr = a.data<T>();
-
37 if (a.flags().contiguous) {
-
38 set_unary_output_data(a, out);
-
39 U* dst = out.data<U>();
-
40 constexpr int N = simd::max_size<T>;
-
41 size_t size = a.data_size();
-
42 while (size >= N) {
-
43 simd::store(dst, op(simd::load<T, N>(a_ptr)));
-
44 size -= N;
-
45 a_ptr += N;
-
46 dst += N;
-
47 }
-
48 while (size > 0) {
-
49 *dst = op(*a_ptr);
-
50 size--;
-
51 dst++;
-
52 a_ptr++;
-
53 }
-
54 } else {
-
55 out.set_data(allocator::malloc_or_wait(out.nbytes()));
-
56 U* dst = out.data<U>();
-
57 size_t shape = a.ndim() > 0 ? a.shape(-1) : 1;
-
58 size_t stride = a.ndim() > 0 ? a.strides(-1) : 1;
-
59 if (a.ndim() <= 1) {
-
60 unary_op(a_ptr, dst, op, shape, stride);
-
61 return;
-
62 }
-
63 ContiguousIterator it(a.shape(), a.strides(), a.ndim() - 1);
-
64 for (size_t elem = 0; elem < a.size(); elem += shape) {
-
65 unary_op(a_ptr + it.loc, dst + elem, op, shape, stride);
-
66 it.step();
-
67 }
-
68 }
-
69}
+
38
+
39template <typename T, typename U = T, typename Op>
+
+
40void unary_op(const array& a, array& out, Op) {
+
41 const T* src = a.data<T>();
+
42 U* dst = out.data<U>();
+
43 auto ndim = a.ndim();
+
44 if (a.flags().contiguous) {
+
45 auto size = a.data_size();
+
46 constexpr int N = simd::max_size<T>;
+
47 while (size >= N) {
+
48 simd::store(dst, Op{}(simd::load<T, N>(src)));
+
49 size -= N;
+
50 src += N;
+
51 dst += N;
+
52 }
+
53 while (size > 0) {
+
54 *dst = Op{}(*src);
+
55 size--;
+
56 dst++;
+
57 src++;
+
58 }
+
59 } else {
+
60 size_t shape = ndim > 0 ? a.shape().back() : 1;
+
61 size_t stride = ndim > 0 ? a.strides().back() : 1;
+
62 if (ndim <= 1) {
+
63 unary_op<T, U, Op>(src, dst, shape, stride);
+
64 return;
+
65 }
+
66 auto it = ContiguousIterator(a.shape(), a.strides(), ndim - 1);
+
67 for (size_t elem = 0; elem < a.size(); elem += shape) {
+
68 unary_op<T, U, Op>(src + it.loc, dst + elem, shape, stride);
+
69 it.step();
+
70 }
+
71 }
+
72}
-
70
-
71template <typename Op>
-
-
72void unary(const array& a, array& out, Op op) {
-
73 switch (out.dtype()) {
-
74 case bool_:
-
75 unary_op<bool>(a, out, op);
-
76 break;
-
77 case uint8:
-
78 unary_op<uint8_t>(a, out, op);
-
79 break;
-
80 case uint16:
-
81 unary_op<uint16_t>(a, out, op);
-
82 break;
-
83 case uint32:
-
84 unary_op<uint32_t>(a, out, op);
-
85 break;
-
86 case uint64:
-
87 unary_op<uint64_t>(a, out, op);
-
88 break;
-
89 case int8:
-
90 unary_op<int8_t>(a, out, op);
-
91 break;
-
92 case int16:
-
93 unary_op<int16_t>(a, out, op);
-
94 break;
-
95 case int32:
-
96 unary_op<int32_t>(a, out, op);
-
97 break;
-
98 case int64:
-
99 unary_op<int64_t>(a, out, op);
-
100 break;
-
101 case float16:
-
102 unary_op<float16_t>(a, out, op);
-
103 break;
-
104 case float32:
-
105 unary_op<float>(a, out, op);
-
106 break;
-
107 case float64:
-
108 unary_op<double>(a, out, op);
-
109 break;
-
110 case bfloat16:
-
111 unary_op<bfloat16_t>(a, out, op);
-
112 break;
-
113 case complex64:
-
114 unary_op<complex64_t>(a, out, op);
-
115 break;
-
116 }
-
117}
+
73
+
74template <typename Op>
+
+
75void unary(const array& a, array& out, Op op, Stream stream) {
+
76 set_unary_output_data(a, out);
+
77 auto& encoder = cpu::get_command_encoder(stream);
+
78 encoder.set_input_array(a);
+
79 encoder.set_output_array(out);
+
80 encoder.dispatch([a = array::unsafe_weak_copy(a),
+
81 out = array::unsafe_weak_copy(out),
+
82 op = op]() mutable {
+
83 switch (out.dtype()) {
+
84 case bool_:
+
85 unary_op<bool>(a, out, op);
+
86 break;
+
87 case uint8:
+
88 unary_op<uint8_t>(a, out, op);
+
89 break;
+
90 case uint16:
+
91 unary_op<uint16_t>(a, out, op);
+
92 break;
+
93 case uint32:
+
94 unary_op<uint32_t>(a, out, op);
+
95 break;
+
96 case uint64:
+
97 unary_op<uint64_t>(a, out, op);
+
98 break;
+
99 case int8:
+
100 unary_op<int8_t>(a, out, op);
+
101 break;
+
102 case int16:
+
103 unary_op<int16_t>(a, out, op);
+
104 break;
+
105 case int32:
+
106 unary_op<int32_t>(a, out, op);
+
107 break;
+
108 case int64:
+
109 unary_op<int64_t>(a, out, op);
+
110 break;
+
111 case float16:
+
112 unary_op<float16_t>(a, out, op);
+
113 break;
+
114 case float32:
+
115 unary_op<float>(a, out, op);
+
116 break;
+
117 case float64:
+
118 unary_op<double>(a, out, op);
+
119 break;
+
120 case bfloat16:
+
121 unary_op<bfloat16_t>(a, out, op);
+
122 break;
+
123 case complex64:
+
124 unary_op<complex64_t>(a, out, op);
+
125 break;
+
126 }
+
127 });
+
128}
-
118
-
119template <typename Op>
-
-
120void unary_fp(const array& a, array& out, Op op) {
-
121 switch (out.dtype()) {
-
122 case bfloat16:
-
123 unary_op<bfloat16_t>(a, out, op);
-
124 break;
-
125 case float16:
-
126 unary_op<float16_t>(a, out, op);
-
127 break;
-
128 case float32:
-
129 unary_op<float>(a, out, op);
-
130 break;
-
131 case float64:
-
132 unary_op<double>(a, out, op);
-
133 break;
-
134 case complex64:
-
135 unary_op<complex64_t>(a, out, op);
-
136 break;
-
137 default:
-
138 std::ostringstream err;
-
139 err << "[unary_fp] Does not support " << out.dtype();
-
140 throw std::runtime_error(err.str());
-
141 }
-
142}
+
129
+
130template <typename Op>
+
+
131void unary_real_fp(const array& a, array& out, Op op, Stream stream) {
+
132 set_unary_output_data(a, out);
+
133 auto& encoder = cpu::get_command_encoder(stream);
+
134 encoder.set_input_array(a);
+
135 encoder.set_output_array(out);
+
136 encoder.dispatch([a = array::unsafe_weak_copy(a),
+
137 out = array::unsafe_weak_copy(out),
+
138 op = op]() mutable {
+
139 switch (out.dtype()) {
+
140 case bfloat16:
+
141 unary_op<bfloat16_t>(a, out, op);
+
142 break;
+
143 case float16:
+
144 unary_op<float16_t>(a, out, op);
+
145 break;
+
146 case float32:
+
147 unary_op<float>(a, out, op);
+
148 break;
+
149 case float64:
+
150 unary_op<double>(a, out, op);
+
151 break;
+
152 default:
+
153 std::ostringstream err;
+
154 err << "[unary_real] Does not support " << out.dtype();
+
155 throw std::runtime_error(err.str());
+
156 }
+
157 });
+
158}
-
143
-
144template <typename Op>
-
-
145void unary_int(const array& a, array& out, Op op) {
-
146 switch (out.dtype()) {
-
147 case uint8:
-
148 unary_op<uint8_t>(a, out, op);
-
149 break;
-
150 case uint16:
-
151 unary_op<uint16_t>(a, out, op);
-
152 break;
-
153 case uint32:
-
154 unary_op<uint32_t>(a, out, op);
-
155 break;
-
156 case uint64:
-
157 unary_op<uint64_t>(a, out, op);
-
158 break;
-
159 case int8:
-
160 unary_op<int8_t>(a, out, op);
-
161 break;
-
162 case int16:
-
163 unary_op<int16_t>(a, out, op);
-
164 break;
-
165 case int32:
-
166 unary_op<int32_t>(a, out, op);
-
167 break;
-
168 case int64:
-
169 unary_op<int64_t>(a, out, op);
-
170 break;
-
171 default:
-
172 std::ostringstream err;
-
173 err << "[unary_int] Does not support " << out.dtype();
-
174 throw std::runtime_error(err.str());
-
175 }
-
176}
+
159template <typename Op>
+
+
160void unary_fp(const array& a, array& out, Op op, Stream stream) {
+
161 set_unary_output_data(a, out);
+
162 auto& encoder = cpu::get_command_encoder(stream);
+
163 encoder.set_input_array(a);
+
164 encoder.set_output_array(out);
+
165 encoder.dispatch([a = array::unsafe_weak_copy(a),
+
166 out = array::unsafe_weak_copy(out),
+
167 op = op]() mutable {
+
168 switch (out.dtype()) {
+
169 case bfloat16:
+
170 unary_op<bfloat16_t>(a, out, op);
+
171 break;
+
172 case float16:
+
173 unary_op<float16_t>(a, out, op);
+
174 break;
+
175 case float32:
+
176 unary_op<float>(a, out, op);
+
177 break;
+
178 case float64:
+
179 unary_op<double>(a, out, op);
+
180 break;
+
181 case complex64:
+
182 unary_op<complex64_t>(a, out, op);
+
183 break;
+
184 default:
+
185 std::ostringstream err;
+
186 err << "[unary_fp] Does not support " << out.dtype();
+
187 throw std::runtime_error(err.str());
+
188 }
+
189 });
+
190}
-
177
-
178} // namespace mlx::core
+
191
+
192template <typename Op>
+
+
193void unary_signed(const array& a, array& out, Op op, Stream stream) {
+
194 set_unary_output_data(a, out);
+
195 auto& encoder = cpu::get_command_encoder(stream);
+
196 encoder.set_input_array(a);
+
197 encoder.set_output_array(out);
+
198 encoder.dispatch([a = array::unsafe_weak_copy(a),
+
199 out = array::unsafe_weak_copy(out),
+
200 op = op]() mutable {
+
201 switch (out.dtype()) {
+
202 case int8:
+
203 unary_op<int8_t>(a, out, op);
+
204 break;
+
205 case int16:
+
206 unary_op<int16_t>(a, out, op);
+
207 break;
+
208 case int32:
+
209 unary_op<int32_t>(a, out, op);
+
210 break;
+
211 case int64:
+
212 unary_op<int64_t>(a, out, op);
+
213 break;
+
214 case float16:
+
215 unary_op<float16_t>(a, out, op);
+
216 break;
+
217 case float32:
+
218 unary_op<float>(a, out, op);
+
219 break;
+
220 case float64:
+
221 unary_op<double>(a, out, op);
+
222 break;
+
223 case bfloat16:
+
224 unary_op<bfloat16_t>(a, out, op);
+
225 break;
+
226 case complex64:
+
227 unary_op<complex64_t>(a, out, op);
+
228 break;
+
229 default:
+
230 throw std::runtime_error("[Abs] Called on unsigned type");
+
231 }
+
232 });
+
233}
+
+
234
+
235template <typename Op>
+
+
236void unary_complex(const array& a, array& out, Op op, Stream stream) {
+
237 set_unary_output_data(a, out);
+
238 auto& encoder = cpu::get_command_encoder(stream);
+
239 encoder.set_input_array(a);
+
240 encoder.set_output_array(out);
+
241 encoder.dispatch([a = array::unsafe_weak_copy(a),
+
242 out = array::unsafe_weak_copy(out),
+
243 op = op]() mutable { unary_op<complex64_t>(a, out, op); });
+
244}
+
+
245
+
246template <typename Op>
+
+
247void unary_complex_to_float(const array& a, array& out, Op op, Stream stream) {
+
248 set_unary_output_data(a, out);
+
249 auto& encoder = cpu::get_command_encoder(stream);
+
250 encoder.set_input_array(a);
+
251 encoder.set_output_array(out);
+
252 encoder.dispatch(
+
253 [a = array::unsafe_weak_copy(a),
+
254 out = array::unsafe_weak_copy(out),
+
255 op = op]() mutable { unary_op<complex64_t, float>(a, out, op); });
+
256}
+
+
257
+
258template <typename Op>
+
+
259void unary_int(const array& a, array& out, Op op, Stream stream) {
+
260 set_unary_output_data(a, out);
+
261 auto& encoder = cpu::get_command_encoder(stream);
+
262 encoder.set_input_array(a);
+
263 encoder.set_output_array(out);
+
264 encoder.dispatch([a = array::unsafe_weak_copy(a),
+
265 out = array::unsafe_weak_copy(out),
+
266 op = op]() mutable {
+
267 switch (out.dtype()) {
+
268 case uint8:
+
269 unary_op<uint8_t>(a, out, op);
+
270 break;
+
271 case uint16:
+
272 unary_op<uint16_t>(a, out, op);
+
273 break;
+
274 case uint32:
+
275 unary_op<uint32_t>(a, out, op);
+
276 break;
+
277 case uint64:
+
278 unary_op<uint64_t>(a, out, op);
+
279 break;
+
280 case int8:
+
281 unary_op<int8_t>(a, out, op);
+
282 break;
+
283 case int16:
+
284 unary_op<int16_t>(a, out, op);
+
285 break;
+
286 case int32:
+
287 unary_op<int32_t>(a, out, op);
+
288 break;
+
289 case int64:
+
290 unary_op<int64_t>(a, out, op);
+
291 break;
+
292 default:
+
293 std::ostringstream err;
+
294 err << "[unary_int] Does not support " << out.dtype();
+
295 throw std::runtime_error(err.str());
+
296 }
+
297 });
+
298}
+
+
299
+
300} // namespace mlx::core
mlx::core::array
Definition array.h:24
-
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:318
+
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:313
mlx::core::array::shape
const Shape & shape() const
The shape of the array as a vector of integers.
Definition array.h:103
mlx::core::array::strides
const Strides & strides() const
The strides of the array.
Definition array.h:117
mlx::core::array::nbytes
size_t nbytes() const
The number of bytes in the array.
Definition array.h:93
mlx::core::array::ndim
size_t ndim() const
The number of dimensions of the array.
Definition array.h:98
mlx::core::array::size
size_t size() const
The number of elements in the array.
Definition array.h:88
-
mlx::core::array::data
T * data()
Definition array.h:354
+
mlx::core::array::data
T * data()
Definition array.h:349
+
mlx::core::array::unsafe_weak_copy
static array unsafe_weak_copy(const array &other)
Get a new array that refers to the same data as the input but with a non-owning pointer to it.
mlx::core::array::copy_shared_buffer
void copy_shared_buffer(const array &other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
mlx::core::array::dtype
Dtype dtype() const
Get the arrays data type.
Definition array.h:131
mlx::core::array::itemsize
size_t itemsize() const
The size of the array's datatype in bytes.
Definition array.h:83
mlx::core::array::set_data
void set_data(allocator::Buffer buffer, Deleter d=allocator::free)
-
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:332
+
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:327
+
mlx::core::allocator::malloc_or_wait
Buffer malloc_or_wait(size_t size)
+
mlx::core::cpu::get_command_encoder
CommandEncoder & get_command_encoder(Stream stream)
mlx::core::simd::load
Simd< T, N > load(const T *x)
Definition base_simd.h:28
mlx::core::simd::max_size
static constexpr int max_size
Definition base_simd.h:14
mlx::core::simd::store
void store(T *dst, Simd< T, N > x)
Definition base_simd.h:33
mlx::core
Definition allocator.h:7
-
mlx::core::unary_int
void unary_int(const array &a, array &out, Op op)
Definition unary.h:145
+
mlx::core::unary_complex_to_float
void unary_complex_to_float(const array &a, array &out, Op op, Stream stream)
Definition unary.h:247
+
mlx::core::unary
void unary(const array &a, array &out, Op op, Stream stream)
Definition unary.h:75
mlx::core::bool_
constexpr Dtype bool_
Definition dtype.h:68
mlx::core::uint64
constexpr Dtype uint64
Definition dtype.h:73
-
mlx::core::unary_op
void unary_op(const T *a, U *out, Op op, size_t shape, size_t stride)
Definition unary.h:27
mlx::core::uint16
constexpr Dtype uint16
Definition dtype.h:71
mlx::core::float64
constexpr Dtype float64
Definition dtype.h:82
-
mlx::core::set_unary_output_data
void set_unary_output_data(const array &in, array &out)
Definition unary.h:13
+
mlx::core::set_unary_output_data
void set_unary_output_data(const array &in, array &out)
Definition unary.h:14
+
mlx::core::unary_int
void unary_int(const array &a, array &out, Op op, Stream stream)
Definition unary.h:259
mlx::core::bfloat16
constexpr Dtype bfloat16
Definition dtype.h:83
mlx::core::int32
constexpr Dtype int32
Definition dtype.h:77
mlx::core::float32
constexpr Dtype float32
Definition dtype.h:81
-
mlx::core::unary
void unary(const array &a, array &out, Op op)
Definition unary.h:72
+
mlx::core::unary_fp
void unary_fp(const array &a, array &out, Op op, Stream stream)
Definition unary.h:160
mlx::core::int16
constexpr Dtype int16
Definition dtype.h:76
-
mlx::core::unary_fp
void unary_fp(const array &a, array &out, Op op)
Definition unary.h:120
mlx::core::int8
constexpr Dtype int8
Definition dtype.h:75
mlx::core::int64
constexpr Dtype int64
Definition dtype.h:78
+
mlx::core::unary_real_fp
void unary_real_fp(const array &a, array &out, Op op, Stream stream)
Definition unary.h:131
mlx::core::uint8
constexpr Dtype uint8
Definition dtype.h:70
+
mlx::core::unary_complex
void unary_complex(const array &a, array &out, Op op, Stream stream)
Definition unary.h:236
+
mlx::core::unary_op
void unary_op(const T *a, U *out, size_t shape, size_t stride)
Definition unary.h:32
mlx::core::float16
constexpr Dtype float16
Definition dtype.h:80
mlx::core::uint32
constexpr Dtype uint32
Definition dtype.h:72
+
mlx::core::unary_signed
void unary_signed(const array &a, array &out, Op op, Stream stream)
Definition unary.h:193
mlx::core::is_donatable
bool is_donatable(const array &in, const array &out)
Definition utils.h:155
mlx::core::complex64
constexpr Dtype complex64
Definition dtype.h:84
mlx::core::ContiguousIterator
Definition utils.h:73
-
mlx::core::ContiguousIterator::loc
int64_t loc
Definition utils.h:126
-
mlx::core::ContiguousIterator::step
void step()
Definition utils.h:74
-
mlx::core::array::Flags::contiguous
bool contiguous
Definition array.h:231
+
mlx::core::Stream
Definition stream.h:9
+
mlx::core::array::Flags::contiguous
bool contiguous
Definition array.h:238
diff --git a/docs/build/html/dev/custom_metal_kernels.html b/docs/build/html/dev/custom_metal_kernels.html index e013dedef..9cab19a24 100644 --- a/docs/build/html/dev/custom_metal_kernels.html +++ b/docs/build/html/dev/custom_metal_kernels.html @@ -8,7 +8,7 @@ - Custom Metal Kernels — MLX 0.23.2 documentation + Custom Metal Kernels — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
diff --git a/docs/build/html/dev/extensions.html b/docs/build/html/dev/extensions.html index 1e97e01bf..fbf885283 100644 --- a/docs/build/html/dev/extensions.html +++ b/docs/build/html/dev/extensions.html @@ -8,7 +8,7 @@ - Custom Extensions in MLX — MLX 0.23.2 documentation + Custom Extensions in MLX — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
@@ -942,12 +942,12 @@ You can do that in MLX directly:

This function performs that operation while leaving the implementation and function transformations to MLX.

-

However you may need to customize the underlying implementation, perhaps to -make it faster or for custom differentiation. In this tutorial we will go -through adding custom extensions. It will cover:

+

However, you may want to customize the underlying implementation, perhaps to +make it faster. In this tutorial we will go through adding custom extensions. +It will cover:

  • The structure of the MLX library.

    • -

  • Implementing a CPU operation that redirects to Accelerate when appropriate.

    • +

  • Implementing a CPU operation.

  • Implementing a GPU operation using metal.

  • Adding the vjp and jvp function transformation.

  • Building a custom extension and binding it to python.

    • @@ -962,14 +962,14 @@ more detail.

    Operations#

    Operations are the front-end functions that operate on arrays. They are defined in the C++ API (Operations), and the Python API (Operations) binds them.

    -

    We would like an operation, axpby() that takes in two arrays x and +

    We would like an operation axpby() that takes in two arrays, x and y, and two scalars, alpha and beta. This is how to define it in C++:

    /**
 *  Scale and sum two vectors element-wise
 *  z = alpha * x + beta * y
 *
-*  Follow numpy style broadcasting between x and y
+*  Use NumPy-style broadcasting between x and y
 *  Inputs are upcasted to floats if needed
 **/
 array axpby(
@@ -981,7 +981,7 @@ C++:
    
 );
    -

    The simplest way to this operation is in terms of existing operations:

    +

    The simplest way to implement this is with existing operations:

    array axpby(
     const array& x, // Input array x
     const array& y, // Input array y
@@ -1062,9 +1062,6 @@ more concrete:
    
   private:
     float alpha_;
     float beta_;
-
-    /** Fall back implementation for evaluation on CPU */
-    void eval(const std::vector<array>& inputs, array& out);
 };
    @@ -1093,7 +1090,7 @@ inputs that are passed to the primitive.

    auto promoted_dtype = promote_types(x.dtype(), y.dtype()); // Upcast to float32 for non-floating point inputs x and y - auto out_dtype = is_floating_point(promoted_dtype) + auto out_dtype = issubdtype(promoted_dtype, float32) ? promoted_dtype : promote_types(promoted_dtype, float32); @@ -1139,153 +1136,87 @@ of these functions to allocate memory as needed.

    Implementing the CPU Back-end#

    -

    Let’s start by implementing a naive and generic version of -Axpby::eval_cpu(). We declared this as a private member function of -Axpby earlier called Axpby::eval().

    -

    Our naive method will go over each element of the output array, find the +

    Let’s start by implementing Axpby::eval_cpu().

    +

    The method will go over each element of the output array, find the corresponding input elements of x and y and perform the operation point-wise. This is captured in the templated function axpby_impl().

    template <typename T>
 void axpby_impl(
-        const array& x,
-        const array& y,
-        array& out,
-        float alpha_,
-        float beta_) {
-    // We only allocate memory when we are ready to fill the output
-    // malloc_or_wait synchronously allocates available memory
-    // There may be a wait executed here if the allocation is requested
-    // under memory-pressured conditions
-    out.set_data(allocator::malloc_or_wait(out.nbytes()));
+    const mx::array& x,
+    const mx::array& y,
+    mx::array& out,
+    float alpha_,
+    float beta_,
+    mx::Stream stream) {
+  // Allocate the output with `malloc_or_wait` which synchronously allocates
+  // memory, potentially waiting if the system is under memory pressure
+  out.set_data(mx::allocator::malloc_or_wait(out.nbytes()));
 
-    // Collect input and output data pointers
-    const T* x_ptr = x.data<T>();
-    const T* y_ptr = y.data<T>();
-    T* out_ptr = out.data<T>();
+  // Get the CPU command encoder and register input and output arrays
+  auto& encoder = mx::cpu::get_command_encoder(stream);
+  encoder.set_input_array(x);
+  encoder.set_input_array(y);
+  encoder.set_output_array(out);
+
+  // Launch the CPU kernel
+  encoder.dispatch([x_ptr = x.data<T>(),
+                    y_ptr = y.data<T>(),
+                    out_ptr = out.data<T>(),
+                    size = out.size(),
+                    shape = out.shape(),
+                    x_strides = x.strides(),
+                    y_strides = y.strides(),
+                    alpha_,
+                    beta_]() {
 
     // Cast alpha and beta to the relevant types
     T alpha = static_cast<T>(alpha_);
     T beta = static_cast<T>(beta_);
 
     // Do the element-wise operation for each output
-    for (size_t out_idx = 0; out_idx < out.size(); out_idx++) {
-        // Map linear indices to offsets in x and y
-        auto x_offset = elem_to_loc(out_idx, x.shape(), x.strides());
-        auto y_offset = elem_to_loc(out_idx, y.shape(), y.strides());
+    for (size_t out_idx = 0; out_idx < size; out_idx++) {
+      // Map linear indices to offsets in x and y
+      auto x_offset = mx::elem_to_loc(out_idx, shape, x_strides);
+      auto y_offset = mx::elem_to_loc(out_idx, shape, y_strides);
 
-        // We allocate the output to be contiguous and regularly strided
-        // (defaults to row major) and hence it doesn't need additional mapping
-        out_ptr[out_idx] = alpha * x_ptr[x_offset] + beta * y_ptr[y_offset];
+      // We allocate the output to be contiguous and regularly strided
+      // (defaults to row major) and hence it doesn't need additional mapping
+      out_ptr[out_idx] = alpha * x_ptr[x_offset] + beta * y_ptr[y_offset];
     }
+  });
 }

    Our implementation should work for all incoming floating point arrays. Accordingly, we add dispatches for float32, float16, bfloat16 and complex64. We throw an error if we encounter an unexpected type.

    -
    /** Fall back implementation for evaluation on CPU */
-void Axpby::eval(
-  const std::vector<array>& inputs,
-  const std::vector<array>& outputs) {
-    auto& x = inputs[0];
-    auto& y = inputs[1];
-    auto& out = outputs[0];
+
    void Axpby::eval_cpu(
+    const std::vector<mx::array>& inputs,
+    std::vector<mx::array>& outputs) {
+  auto& x = inputs[0];
+  auto& y = inputs[1];
+  auto& out = outputs[0];
 
-    // Dispatch to the correct dtype
-    if (out.dtype() == float32) {
-        return axpby_impl<float>(x, y, out, alpha_, beta_);
-    } else if (out.dtype() == float16) {
-        return axpby_impl<float16_t>(x, y, out, alpha_, beta_);
-    } else if (out.dtype() == bfloat16) {
-        return axpby_impl<bfloat16_t>(x, y, out, alpha_, beta_);
-    } else if (out.dtype() == complex64) {
-        return axpby_impl<complex64_t>(x, y, out, alpha_, beta_);
-    } else {
-        throw std::runtime_error(
-            "[Axpby] Only supports floating point types.");
-    }
-}
-
    
-
    
-
    This is good as a fallback implementation. We can use the axpby routine
-provided by the Accelerate framework for a faster implementation in certain
-cases:
    
-
      
-
    1. Accelerate does not provide implementations of axpby for half precision
-floats. We can only use it for float32 types.
      2. 
-
    2. Accelerate assumes the inputs x and y are contiguous and all
-elements have fixed strides between them. We only direct to Accelerate
-if both x and y are row contiguous or column contiguous.
      3. 
-
    3. Accelerate performs the routine Y = (alpha * X) + (beta * Y) in-place.
-MLX expects to write the output to a new array. We must copy the elements
-of y into the output and use that as an input to axpby.
      4. 
-
    
-
    Let’s write an implementation that uses Accelerate in the right conditions.
-It allocates data for the output, copies y into it, and then calls the
-catlas_saxpby() from accelerate.
    
-
    template <typename T>
-void axpby_impl_accelerate(
-        const array& x,
-        const array& y,
-        array& out,
-        float alpha_,
-        float beta_) {
-    // Accelerate library provides catlas_saxpby which does
-    // Y = (alpha * X) + (beta * Y) in place
-    // To use it, we first copy the data in y over to the output array
-    out.set_data(allocator::malloc_or_wait(out.nbytes()));
-
-    // We then copy over the elements using the contiguous vector specialization
-    copy_inplace(y, out, CopyType::Vector);
-
-    // Get x and y pointers for catlas_saxpby
-    const T* x_ptr = x.data<T>();
-    T* y_ptr = out.data<T>();
-
-    T alpha = static_cast<T>(alpha_);
-    T beta = static_cast<T>(beta_);
-
-    // Call the inplace accelerate operator
-    catlas_saxpby(
-        /* N = */ out.size(),
-        /* ALPHA = */ alpha,
-        /* X = */ x_ptr,
-        /* INCX = */ 1,
-        /* BETA = */ beta,
-        /* Y = */ y_ptr,
-        /* INCY = */ 1);
-}
-
    
-
    
-
    For inputs that do not fit the criteria for accelerate, we fall back to
-Axpby::eval(). With this in mind, let’s finish our
-Axpby::eval_cpu().
    
-
    /** Evaluate primitive on CPU using accelerate specializations */
-void Axpby::eval_cpu(
-  const std::vector<array>& inputs,
-  const std::vector<array>& outputs) {
-    assert(inputs.size() == 2);
-    auto& x = inputs[0];
-    auto& y = inputs[1];
-    auto& out = outputs[0];
-
-    // Accelerate specialization for contiguous single precision float arrays
-    if (out.dtype() == float32 &&
-        ((x.flags().row_contiguous && y.flags().row_contiguous) ||
-        (x.flags().col_contiguous && y.flags().col_contiguous))) {
-        axpby_impl_accelerate<float>(x, y, out, alpha_, beta_);
-        return;
-    }
-
-    // Fall back to common back-end if specializations are not available
-    eval(inputs, outputs);
+  // Dispatch to the correct dtype
+  if (out.dtype() == mx::float32) {
+    return axpby_impl<float>(x, y, out, alpha_, beta_, stream());
+  } else if (out.dtype() == mx::float16) {
+    return axpby_impl<mx::float16_t>(x, y, out, alpha_, beta_, stream());
+  } else if (out.dtype() == mx::bfloat16) {
+    return axpby_impl<mx::bfloat16_t>(x, y, out, alpha_, beta_, stream());
+  } else if (out.dtype() == mx::complex64) {
+    return axpby_impl<mx::complex64_t>(x, y, out, alpha_, beta_, stream());
+  } else {
+    throw std::runtime_error(
+        "Axpby is only supported for floating point types.");
+  }
 }
 
    
 
    
 
    Just this much is enough to run the operation axpby() on a CPU stream! If
 you do not plan on running the operation on the GPU or using transforms on
 computation graphs that contain Axpby, you can stop implementing the
-primitive here and enjoy the speed-ups you get from the Accelerate library.
    
+primitive here.

    Implementing the GPU Back-end#

    @@ -1688,18 +1619,16 @@ import the Python package and play with it as you would any other MLX operation.

    Results#

    Let’s run a quick benchmark and see how our new axpby operation compares -with the naive simple_axpby() we first defined on the CPU.

    +with the naive simple_axpby() we first defined.

    import mlx.core as mx
 from mlx_sample_extensions import axpby
 import time
 
-mx.set_default_device(mx.cpu)
-
 def simple_axpby(x: mx.array, y: mx.array, alpha: float, beta: float) -> mx.array:
     return alpha * x + beta * y
 
-M = 256
-N = 512
+M = 4096
+N = 4096
 
 x = mx.random.normal((M, N))
 y = mx.random.normal((M, N))
@@ -1710,25 +1639,25 @@ with the naive def bench(f):
     # Warm up
-    for i in range(100):
+    for i in range(5):
         z = f(x, y, alpha, beta)
         mx.eval(z)
 
     # Timed run
     s = time.time()
-    for i in range(5000):
+    for i in range(100):
         z = f(x, y, alpha, beta)
         mx.eval(z)
     e = time.time()
-    return e - s
+    return 1000 * (e - s) / 100
 
 simple_time = bench(simple_axpby)
 custom_time = bench(axpby)
 
-print(f"Simple axpby: {simple_time:.3f} s | Custom axpby: {custom_time:.3f} s")
+print(f"Simple axpby: {simple_time:.3f} ms | Custom axpby: {custom_time:.3f} ms")
    -

    The results are Simple axpby: 0.114 s | Custom axpby: 0.109 s. We see +

    The results are Simple axpby: 1.559 ms | Custom axpby: 0.774 ms. We see modest improvements right away!

    This operation is now good to be used to build other operations, in mlx.nn.Module calls, and also as a part of graph transformations like diff --git a/docs/build/html/dev/metal_debugger.html b/docs/build/html/dev/metal_debugger.html index 3b3d42f9d..739273dd1 100644 --- a/docs/build/html/dev/metal_debugger.html +++ b/docs/build/html/dev/metal_debugger.html @@ -8,7 +8,7 @@ - Metal Debugger — MLX 0.23.2 documentation + Metal Debugger — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/dev/mlx_in_cpp.html b/docs/build/html/dev/mlx_in_cpp.html index b228f9ea4..ff769656e 100644 --- a/docs/build/html/dev/mlx_in_cpp.html +++ b/docs/build/html/dev/mlx_in_cpp.html @@ -8,7 +8,7 @@ - Using MLX in C++ — MLX 0.23.2 documentation + Using MLX in C++ — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -136,8 +136,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/dir_2193406f5b2eae6fc53753d8a9a80df3.html b/docs/build/html/dir_2193406f5b2eae6fc53753d8a9a80df3.html index 88969db9d..093a0a384 100644 --- a/docs/build/html/dir_2193406f5b2eae6fc53753d8a9a80df3.html +++ b/docs/build/html/dir_2193406f5b2eae6fc53753d8a9a80df3.html @@ -110,7 +110,7 @@ $(function(){initNavTree('dir_2193406f5b2eae6fc53753d8a9a80df3.html',''); initRe Files  gguf.h   - load.h + load.h   diff --git a/docs/build/html/dir_2193406f5b2eae6fc53753d8a9a80df3.js b/docs/build/html/dir_2193406f5b2eae6fc53753d8a9a80df3.js index 5da693cd2..1da920a25 100644 --- a/docs/build/html/dir_2193406f5b2eae6fc53753d8a9a80df3.js +++ b/docs/build/html/dir_2193406f5b2eae6fc53753d8a9a80df3.js @@ -1,5 +1,5 @@ var dir_2193406f5b2eae6fc53753d8a9a80df3 = [ [ "gguf.h", "gguf_8h.html", "gguf_8h" ], - [ "load.h", "io_2load_8h.html", "io_2load_8h" ] + [ "load.h", "load_8h.html", "load_8h" ] ]; \ No newline at end of file diff --git a/docs/build/html/dir_48c8bf40aae7e42226b4fe31ea48af19.html b/docs/build/html/dir_48c8bf40aae7e42226b4fe31ea48af19.html index 57f14e96b..dac418785 100644 --- a/docs/build/html/dir_48c8bf40aae7e42226b4fe31ea48af19.html +++ b/docs/build/html/dir_48c8bf40aae7e42226b4fe31ea48af19.html @@ -125,6 +125,10 @@ Files    copy.h   + encoder.h +  + eval.h +   gemm.h    jit_compiler.h diff --git a/docs/build/html/dir_48c8bf40aae7e42226b4fe31ea48af19.js b/docs/build/html/dir_48c8bf40aae7e42226b4fe31ea48af19.js index 1adc2785b..763c9783c 100644 --- a/docs/build/html/dir_48c8bf40aae7e42226b4fe31ea48af19.js +++ b/docs/build/html/dir_48c8bf40aae7e42226b4fe31ea48af19.js @@ -1,12 +1,14 @@ var dir_48c8bf40aae7e42226b4fe31ea48af19 = [ [ "simd", "dir_777905fddc177f731a39846ae16b0314.html", "dir_777905fddc177f731a39846ae16b0314" ], - [ "arange.h", "cpu_2arange_8h.html", "cpu_2arange_8h" ], + [ "arange.h", "cpu_2arange_8h.html", null ], [ "binary.h", "cpu_2binary_8h.html", "cpu_2binary_8h" ], [ "binary_ops.h", "cpu_2binary__ops_8h.html", "cpu_2binary__ops_8h" ], [ "binary_two.h", "cpu_2binary__two_8h.html", null ], [ "compiled_preamble.h", "compiled__preamble_8h.html", "compiled__preamble_8h" ], [ "copy.h", "cpu_2copy_8h.html", "cpu_2copy_8h" ], + [ "encoder.h", "encoder_8h.html", "encoder_8h" ], + [ "eval.h", "eval_8h.html", "eval_8h" ], [ "gemm.h", "cpu_2gemm_8h.html", "cpu_2gemm_8h" ], [ "jit_compiler.h", "jit__compiler_8h.html", "jit__compiler_8h" ], [ "lapack.h", "lapack_8h.html", "lapack_8h" ], diff --git a/docs/build/html/dir_938ab0ecf10b8b860ff766c820f665fd.html b/docs/build/html/dir_938ab0ecf10b8b860ff766c820f665fd.html index d1e1c6b34..34a3222d6 100644 --- a/docs/build/html/dir_938ab0ecf10b8b860ff766c820f665fd.html +++ b/docs/build/html/dir_938ab0ecf10b8b860ff766c820f665fd.html @@ -145,6 +145,8 @@ Files    fast_primitives.h   + fence.h +   fft.h    graph_utils.h diff --git a/docs/build/html/dir_938ab0ecf10b8b860ff766c820f665fd.js b/docs/build/html/dir_938ab0ecf10b8b860ff766c820f665fd.js index 913bb651b..d7750fe46 100644 --- a/docs/build/html/dir_938ab0ecf10b8b860ff766c820f665fd.js +++ b/docs/build/html/dir_938ab0ecf10b8b860ff766c820f665fd.js @@ -17,6 +17,7 @@ var dir_938ab0ecf10b8b860ff766c820f665fd = [ "export_impl.h", "export__impl_8h.html", "export__impl_8h" ], [ "fast.h", "fast_8h.html", "fast_8h" ], [ "fast_primitives.h", "fast__primitives_8h.html", "fast__primitives_8h" ], + [ "fence.h", "fence_8h.html", "fence_8h" ], [ "fft.h", "fft_8h.html", "fft_8h" ], [ "graph_utils.h", "graph__utils_8h.html", "graph__utils_8h" ], [ "io.h", "io_8h.html", "io_8h" ], diff --git a/docs/build/html/dir_d0c977ea65824390717cdb7efc36c157.html b/docs/build/html/dir_d0c977ea65824390717cdb7efc36c157.html index f62038ee1..df4127fa9 100644 --- a/docs/build/html/dir_d0c977ea65824390717cdb7efc36c157.html +++ b/docs/build/html/dir_d0c977ea65824390717cdb7efc36c157.html @@ -123,10 +123,6 @@ Files    device.h   - event.h -  - fence.h -   kernels.h    matmul.h diff --git a/docs/build/html/dir_d0c977ea65824390717cdb7efc36c157.js b/docs/build/html/dir_d0c977ea65824390717cdb7efc36c157.js index 8ba6eebd1..c47037736 100644 --- a/docs/build/html/dir_d0c977ea65824390717cdb7efc36c157.js +++ b/docs/build/html/dir_d0c977ea65824390717cdb7efc36c157.js @@ -6,8 +6,6 @@ var dir_d0c977ea65824390717cdb7efc36c157 = [ "binary.h", "metal_2binary_8h.html", "metal_2binary_8h" ], [ "copy.h", "metal_2copy_8h.html", "metal_2copy_8h" ], [ "device.h", "backend_2metal_2device_8h.html", "backend_2metal_2device_8h" ], - [ "event.h", "backend_2metal_2event_8h.html", "backend_2metal_2event_8h" ], - [ "fence.h", "fence_8h.html", "fence_8h" ], [ "kernels.h", "kernels_8h.html", "kernels_8h" ], [ "matmul.h", "matmul_8h.html", "matmul_8h" ], [ "metal.h", "metal_8h.html", "metal_8h" ], diff --git a/docs/build/html/dir_f149b24a1b5be11cd70151abe517e3f8.html b/docs/build/html/dir_f149b24a1b5be11cd70151abe517e3f8.html index 990508c9d..8ea693ec0 100644 --- a/docs/build/html/dir_f149b24a1b5be11cd70151abe517e3f8.html +++ b/docs/build/html/dir_f149b24a1b5be11cd70151abe517e3f8.html @@ -116,8 +116,6 @@ Files    hadamard.h   - load.h -   reduce.h    slicing.h diff --git a/docs/build/html/dir_f149b24a1b5be11cd70151abe517e3f8.js b/docs/build/html/dir_f149b24a1b5be11cd70151abe517e3f8.js index d1816b07c..b6dc8775e 100644 --- a/docs/build/html/dir_f149b24a1b5be11cd70151abe517e3f8.js +++ b/docs/build/html/dir_f149b24a1b5be11cd70151abe517e3f8.js @@ -4,7 +4,6 @@ var dir_f149b24a1b5be11cd70151abe517e3f8 = [ "compiled.h", "compiled_8h.html", "compiled_8h" ], [ "copy.h", "common_2copy_8h.html", "common_2copy_8h" ], [ "hadamard.h", "common_2hadamard_8h.html", "common_2hadamard_8h" ], - [ "load.h", "backend_2common_2load_8h.html", "backend_2common_2load_8h" ], [ "reduce.h", "common_2reduce_8h.html", "common_2reduce_8h" ], [ "slicing.h", "common_2slicing_8h.html", "common_2slicing_8h" ], [ "ternary.h", "common_2ternary_8h.html", "common_2ternary_8h" ], diff --git a/docs/build/html/distributed__impl_8h.html b/docs/build/html/distributed__impl_8h.html index 2f0b67d1b..11af52aa7 100644 --- a/docs/build/html/distributed__impl_8h.html +++ b/docs/build/html/distributed__impl_8h.html @@ -132,18 +132,16 @@ Namespaces - - - - - - - - - - - - + + + + + + + + + +

    Functions

    Stream mlx::core::distributed::detail::communication_stream ()
     
    void mlx::core::distributed::detail::all_sum (Group group, const array &input, array &output)
     
    void mlx::core::distributed::detail::all_gather (Group group, const array &input, array &output)
     
    void mlx::core::distributed::detail::send (Group group, const array &input, int dst)
     Send an array to the dst rank.
     
    void mlx::core::distributed::detail::recv (Group group, array &out, int src)
     Recv an array from the src rank.
     
    void mlx::core::distributed::detail::all_sum (Group group, const array &input, array &output, Stream stream)
     
    void mlx::core::distributed::detail::all_gather (Group group, const array &input, array &output, Stream stream)
     
    void mlx::core::distributed::detail::send (Group group, const array &input, int dst, Stream stream)
     Send an array to the dst rank.
     
    void mlx::core::distributed::detail::recv (Group group, array &out, int src, Stream stream)
     Recv an array from the src rank.
     
    diff --git a/docs/build/html/distributed__impl_8h.js b/docs/build/html/distributed__impl_8h.js index 8481f0f38..5fb3c41e7 100644 --- a/docs/build/html/distributed__impl_8h.js +++ b/docs/build/html/distributed__impl_8h.js @@ -1,9 +1,8 @@ var distributed__impl_8h = [ [ "mlx::core::distributed::detail::GroupImpl", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl" ], - [ "mlx::core::distributed::detail::all_gather", "namespacemlx_1_1core_1_1distributed_1_1detail.html#aeb5a1726358213bc75756506f7b54d04", null ], - [ "mlx::core::distributed::detail::all_sum", "namespacemlx_1_1core_1_1distributed_1_1detail.html#aa1d225b25f7b6426c48c5e35860ee960", null ], - [ "mlx::core::distributed::detail::communication_stream", "namespacemlx_1_1core_1_1distributed_1_1detail.html#ac3612edf0e0e18c1e4ba0ce7c6e35cd6", null ], - [ "mlx::core::distributed::detail::recv", "namespacemlx_1_1core_1_1distributed_1_1detail.html#a003de04deb00ecbb19179b3f557df548", null ], - [ "mlx::core::distributed::detail::send", "namespacemlx_1_1core_1_1distributed_1_1detail.html#abf33511660ac71df5fc92f2aad6c6e08", null ] + [ "mlx::core::distributed::detail::all_gather", "namespacemlx_1_1core_1_1distributed_1_1detail.html#ab3dc0367476257f13fe15d4db946edf5", null ], + [ "mlx::core::distributed::detail::all_sum", "namespacemlx_1_1core_1_1distributed_1_1detail.html#a042be875217168ccfc267fba19a627cb", null ], + [ "mlx::core::distributed::detail::recv", "namespacemlx_1_1core_1_1distributed_1_1detail.html#a79bb934225482f2104e8ff270b0530c3", null ], + [ "mlx::core::distributed::detail::send", "namespacemlx_1_1core_1_1distributed_1_1detail.html#a23c5cf992d4f2b2ce9dfa51593a4876d", null ] ]; \ No newline at end of file diff --git a/docs/build/html/distributed__impl_8h_source.html b/docs/build/html/distributed__impl_8h_source.html index 269f53d17..856f546da 100644 --- a/docs/build/html/distributed__impl_8h_source.html +++ b/docs/build/html/distributed__impl_8h_source.html @@ -122,44 +122,40 @@ $(function(){initNavTree('distributed__impl_8h_source.html',''); initResizable(t

    17 virtual int size() = 0;
    18 virtual std::shared_ptr<GroupImpl> split(int color, int key = -1) = 0;
    19
    -
    20 virtual void all_sum(const array& input, array& output) = 0;
    -
    21 virtual void all_gather(const array& input, array& output) = 0;
    -
    22 virtual void send(const array& input, int dst) = 0;
    -
    23 virtual void recv(array& out, int src) = 0;
    +
    20 virtual void all_sum(const array& input, array& output, Stream stream) = 0;
    +
    21 virtual void all_gather(const array& input, array& output, Stream stream) = 0;
    +
    22 virtual void send(const array& input, int dst, Stream stream) = 0;
    +
    23 virtual void recv(array& out, int src, Stream stream) = 0;
    24};
    25
    -
    26/* Return the communication stream. */
    -
    27Stream communication_stream();
    +
    26/* Perform an all reduce sum operation */
    +
    27void all_sum(Group group, const array& input, array& output, Stream stream);
    28
    -
    29/* Perform an all reduce sum operation */
    -
    30void all_sum(Group group, const array& input, array& output);
    -
    31
    -
    32/* Perform an all gather operation */
    -
    33void all_gather(Group group, const array& input, array& output);
    +
    29/* Perform an all gather operation */
    +
    30void all_gather(Group group, const array& input, array& output, Stream stream);
    +
    31
    +
    33void send(Group group, const array& input, int dst, Stream stream);
    34
    -
    36void send(Group group, const array& input, int dst);
    -
    37
    -
    39void recv(Group group, array& out, int src);
    -
    40
    -
    41} // namespace mlx::core::distributed::detail
    +
    36void recv(Group group, array& out, int src, Stream stream);
    +
    37
    +
    38} // namespace mlx::core::distributed::detail
    mlx::core::array
    Definition array.h:24
    mlx::core::distributed::detail::GroupImpl
    Abstract base class of a distributed group implementation.
    Definition distributed_impl.h:12
    -
    mlx::core::distributed::detail::GroupImpl::all_gather
    virtual void all_gather(const array &input, array &output)=0
    +
    mlx::core::distributed::detail::GroupImpl::all_sum
    virtual void all_sum(const array &input, array &output, Stream stream)=0
    +
    mlx::core::distributed::detail::GroupImpl::all_gather
    virtual void all_gather(const array &input, array &output, Stream stream)=0
    +
    mlx::core::distributed::detail::GroupImpl::send
    virtual void send(const array &input, int dst, Stream stream)=0
    +
    mlx::core::distributed::detail::GroupImpl::recv
    virtual void recv(array &out, int src, Stream stream)=0
    mlx::core::distributed::detail::GroupImpl::~GroupImpl
    virtual ~GroupImpl()
    Definition distributed_impl.h:14
    mlx::core::distributed::detail::GroupImpl::split
    virtual std::shared_ptr< GroupImpl > split(int color, int key=-1)=0
    -
    mlx::core::distributed::detail::GroupImpl::recv
    virtual void recv(array &out, int src)=0
    -
    mlx::core::distributed::detail::GroupImpl::send
    virtual void send(const array &input, int dst)=0
    -
    mlx::core::distributed::detail::GroupImpl::all_sum
    virtual void all_sum(const array &input, array &output)=0
    mlx::core::distributed::detail
    Definition distributed.h:12
    -
    mlx::core::distributed::detail::recv
    void recv(Group group, array &out, int src)
    Recv an array from the src rank.
    -
    mlx::core::distributed::detail::all_sum
    void all_sum(Group group, const array &input, array &output)
    -
    mlx::core::distributed::detail::send
    void send(Group group, const array &input, int dst)
    Send an array to the dst rank.
    - -
    mlx::core::distributed::detail::all_gather
    void all_gather(Group group, const array &input, array &output)
    +
    mlx::core::distributed::detail::all_sum
    void all_sum(Group group, const array &input, array &output, Stream stream)
    +
    mlx::core::distributed::detail::send
    void send(Group group, const array &input, int dst, Stream stream)
    Send an array to the dst rank.
    +
    mlx::core::distributed::detail::recv
    void recv(Group group, array &out, int src, Stream stream)
    Recv an array from the src rank.
    +
    mlx::core::distributed::detail::all_gather
    void all_gather(Group group, const array &input, array &output, Stream stream)
    mlx::core::Stream
    Definition stream.h:9
    mlx::core::distributed::Group
    A distributed::Group represents a group of independent mlx processes that can communicate.
    Definition distributed.h:24
    diff --git a/docs/build/html/doxygen_crawl.html b/docs/build/html/doxygen_crawl.html index 892a167c8..8217fa0f4 100644 --- a/docs/build/html/doxygen_crawl.html +++ b/docs/build/html/doxygen_crawl.html @@ -46,16 +46,12 @@ - - - - @@ -988,14 +984,15 @@ - - + + - + + @@ -1043,11 +1040,10 @@ - - - - - + + + + @@ -1830,9 +1826,7 @@ - - @@ -1840,7 +1834,6 @@ - @@ -1863,6 +1856,7 @@ + @@ -1874,6 +1868,7 @@ + @@ -1886,7 +1881,6 @@ - @@ -1940,14 +1934,14 @@ - + + + + - - - @@ -2009,10 +2003,10 @@ + - @@ -2365,10 +2359,14 @@ + + + + @@ -2873,9 +2871,6 @@ - - - @@ -2913,6 +2908,9 @@ + + + @@ -3262,6 +3260,7 @@ + @@ -3276,11 +3275,11 @@ + - @@ -3297,6 +3296,7 @@ + @@ -3330,6 +3330,7 @@ + @@ -3349,17 +3350,14 @@ - - - @@ -3384,17 +3382,16 @@ - - + @@ -3427,9 +3424,9 @@ - + @@ -3448,12 +3445,14 @@ + + @@ -3512,7 +3511,6 @@ - @@ -3520,16 +3518,13 @@ - - + - - @@ -3549,7 +3544,6 @@ - @@ -3565,7 +3559,6 @@ - @@ -3582,7 +3575,6 @@ - @@ -3613,6 +3605,7 @@ + @@ -3622,11 +3615,11 @@ + - @@ -3638,21 +3631,21 @@ - + + + - - + - @@ -3661,9 +3654,9 @@ + - @@ -3683,6 +3676,7 @@ + @@ -3695,7 +3689,7 @@ - + @@ -3726,7 +3720,6 @@ - @@ -3765,6 +3758,7 @@ + @@ -3807,15 +3801,15 @@ + + - - @@ -3823,18 +3817,19 @@ - + + @@ -3886,6 +3881,7 @@ + @@ -3896,6 +3892,10 @@ + + + + @@ -3921,11 +3921,10 @@ - - - - - + + + + @@ -3944,7 +3943,7 @@ - + @@ -4020,17 +4019,18 @@ - + + @@ -4043,12 +4043,12 @@ - + @@ -4607,10 +4607,10 @@ + + - - @@ -4631,8 +4631,10 @@ - + + + @@ -4836,32 +4838,32 @@ - - - - - - - - - - - - - + + + + + + + + + + + + + - - - - - - - - - - - + + + + + + + + + + + @@ -5309,6 +5311,7 @@ + @@ -5324,7 +5327,6 @@ - @@ -5438,9 +5440,7 @@ - - @@ -5456,12 +5456,8 @@ - - - - @@ -5502,6 +5498,19 @@ + + + + + + + + + + + + + @@ -5775,6 +5784,7 @@ + @@ -5790,7 +5800,6 @@ - @@ -5833,14 +5842,13 @@ + - - @@ -5892,10 +5900,14 @@ + + + + @@ -5903,11 +5915,13 @@ + + diff --git a/docs/build/html/backend_2metal_2event_8h.html b/docs/build/html/encoder_8h.html similarity index 66% rename from docs/build/html/backend_2metal_2event_8h.html rename to docs/build/html/encoder_8h.html index 08cc96a23..0d0eda40c 100644 --- a/docs/build/html/backend_2metal_2event_8h.html +++ b/docs/build/html/encoder_8h.html @@ -5,7 +5,7 @@ -MLX: mlx/backend/metal/event.h File Reference +MLX: mlx/backend/cpu/encoder.h File Reference @@ -76,7 +76,7 @@ $(function() { codefold.init(0); });
    @@ -103,34 +103,49 @@ $(function(){initNavTree('backend_2metal_2event_8h.html',''); initResizable(true
    +Classes | Namespaces | -Functions
    -
    event.h File Reference
    +Functions | +Variables
    +
    encoder.h File Reference
    - -

    Go to the source code of this file.

    +
    #include <unordered_map>
    +#include "mlx/array.h"
    +#include "mlx/scheduler.h"
    +
    +

    Go to the source code of this file.

    + + + +

    +Classes

    struct  mlx::core::cpu::CommandEncoder
     
    + +

    Namespaces

    namespace  mlx
     
    namespace  mlx::core
     
    namespace  mlx::core::cpu
     
    - - - - + + +

    Functions

    void mlx::core::encode_wait (Event e)
     
    void mlx::core::encode_signal (Event e)
     
    CommandEncoder & mlx::core::cpu::get_command_encoder (Stream stream)
     
    + + +

    +Variables

    constexpr int mlx::core::cpu::DISPATCHES_PER_TASK = 10
     
    diff --git a/docs/build/html/encoder_8h.js b/docs/build/html/encoder_8h.js new file mode 100644 index 000000000..d810eec5b --- /dev/null +++ b/docs/build/html/encoder_8h.js @@ -0,0 +1,6 @@ +var encoder_8h = +[ + [ "mlx::core::cpu::CommandEncoder", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html", "structmlx_1_1core_1_1cpu_1_1_command_encoder" ], + [ "mlx::core::cpu::get_command_encoder", "namespacemlx_1_1core_1_1cpu.html#a65b1789c4b339a108e64fda5f102d933", null ], + [ "mlx::core::cpu::DISPATCHES_PER_TASK", "namespacemlx_1_1core_1_1cpu.html#a1fc5871c94ccee8536c6d43f8f6d5557", null ] +]; \ No newline at end of file diff --git a/docs/build/html/encoder_8h_source.html b/docs/build/html/encoder_8h_source.html new file mode 100644 index 000000000..bd57da650 --- /dev/null +++ b/docs/build/html/encoder_8h_source.html @@ -0,0 +1,220 @@ + + + + + + + +MLX: mlx/backend/cpu/encoder.h Source File + + + + + + + + + + + + + + + + +
    +
    + + + + + + + +
    +
    MLX +
    +
    + +   + + + + +
    +
    +
    + + + + +
    +
    + +
    +
    +
    + +
    + +
    +
    + + +
    +
    +
    +
    +
    +
    Loading...
    +
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    +
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    +
    +
    +
    +
    + +
    +
    encoder.h
    +
    +
    +Go to the documentation of this file.
    1// Copyright © 2025 Apple Inc.
    +
    2
    +
    3#pragma once
    +
    4
    +
    5#include <unordered_map>
    +
    6
    +
    7#include "mlx/array.h"
    +
    8#include "mlx/scheduler.h"
    +
    9
    +
    +
    10namespace mlx::core::cpu {
    +
    11
    +
    12// Number of dispatches per scheduler task
    +
    13constexpr int DISPATCHES_PER_TASK = 10;
    +
    14
    +
    +
    15struct CommandEncoder {
    +
    16 CommandEncoder(Stream stream) : stream_(stream) {}
    +
    17
    +
    18 CommandEncoder(const CommandEncoder&) = delete;
    +
    19 CommandEncoder& operator=(const CommandEncoder&) = delete;
    +
    20 CommandEncoder(CommandEncoder&&) = delete;
    +
    21 CommandEncoder& operator=(CommandEncoder&&) = delete;
    +
    22
    +
    23 void set_input_array(const array& a) {}
    +
    24 void set_output_array(array& a) {}
    +
    25
    +
    26 // Hold onto a temporary until any already scheduled tasks which use it as
    +
    27 // an input are complete.
    +
    +
    28 void add_temporary(array arr) {
    +
    29 temporaries_.push_back(std::move(arr));
    +
    30 }
    +
    +
    31
    +
    +
    32 void add_temporaries(std::vector<array> arrays) {
    +
    33 temporaries_.insert(
    +
    34 temporaries_.end(),
    +
    35 std::make_move_iterator(arrays.begin()),
    +
    36 std::make_move_iterator(arrays.end()));
    +
    37 }
    +
    +
    38
    +
    +
    39 std::vector<array>& temporaries() {
    +
    40 return temporaries_;
    +
    41 }
    +
    +
    42
    +
    43 template <class F, class... Args>
    +
    +
    44 void dispatch(F&& f, Args&&... args) {
    +
    45 num_ops_ = (num_ops_ + 1) % DISPATCHES_PER_TASK;
    +
    46 auto task = std::bind(std::forward<F>(f), std::forward<Args>(args)...);
    +
    47 if (num_ops_ == 0) {
    +
    48 scheduler::notify_new_task(stream_);
    +
    49 auto task_wrap = [s = stream_, task = std::move(task)]() mutable {
    +
    50 task();
    +
    51 scheduler::notify_task_completion(s);
    +
    52 };
    +
    53 scheduler::enqueue(stream_, std::move(task_wrap));
    +
    54 } else {
    +
    55 scheduler::enqueue(stream_, std::move(task));
    +
    56 }
    +
    57 }
    +
    +
    58
    +
    59 private:
    +
    60 Stream stream_;
    +
    61 std::vector<array> temporaries_;
    +
    62 int num_ops_{0};
    +
    63};
    +
    +
    64
    +
    65CommandEncoder& get_command_encoder(Stream stream);
    +
    66
    +
    67} // namespace mlx::core::cpu
    +
    + +
    mlx::core::array
    Definition array.h:24
    +
    mlx::core::cpu
    Definition encoder.h:10
    +
    mlx::core::cpu::DISPATCHES_PER_TASK
    constexpr int DISPATCHES_PER_TASK
    Definition encoder.h:13
    +
    mlx::core::cpu::get_command_encoder
    CommandEncoder & get_command_encoder(Stream stream)
    +
    mlx::core::scheduler::notify_task_completion
    void notify_task_completion(const Stream &stream)
    Definition scheduler.h:177
    +
    mlx::core::scheduler::notify_new_task
    void notify_new_task(const Stream &stream)
    Definition scheduler.h:173
    +
    mlx::core::scheduler::enqueue
    void enqueue(const Stream &stream, F &&f)
    Definition scheduler.h:165
    +
    mlx::core::Args
    std::vector< array > Args
    Definition export.h:11
    + +
    mlx::core::Stream
    Definition stream.h:9
    +
    mlx::core::cpu::CommandEncoder
    Definition encoder.h:15
    +
    mlx::core::cpu::CommandEncoder::add_temporary
    void add_temporary(array arr)
    Definition encoder.h:28
    +
    mlx::core::cpu::CommandEncoder::CommandEncoder
    CommandEncoder(Stream stream)
    Definition encoder.h:16
    +
    mlx::core::cpu::CommandEncoder::add_temporaries
    void add_temporaries(std::vector< array > arrays)
    Definition encoder.h:32
    +
    mlx::core::cpu::CommandEncoder::operator=
    CommandEncoder & operator=(const CommandEncoder &)=delete
    +
    mlx::core::cpu::CommandEncoder::temporaries
    std::vector< array > & temporaries()
    Definition encoder.h:39
    +
    mlx::core::cpu::CommandEncoder::CommandEncoder
    CommandEncoder(const CommandEncoder &)=delete
    +
    mlx::core::cpu::CommandEncoder::set_input_array
    void set_input_array(const array &a)
    Definition encoder.h:23
    +
    mlx::core::cpu::CommandEncoder::CommandEncoder
    CommandEncoder(CommandEncoder &&)=delete
    +
    mlx::core::cpu::CommandEncoder::set_output_array
    void set_output_array(array &a)
    Definition encoder.h:24
    +
    mlx::core::cpu::CommandEncoder::dispatch
    void dispatch(F &&f, Args &&... args)
    Definition encoder.h:44
    +
    mlx::core::cpu::CommandEncoder::operator=
    CommandEncoder & operator=(CommandEncoder &&)=delete
    +
    +
    + + + + diff --git a/docs/build/html/backend_2common_2load_8h.html b/docs/build/html/eval_8h.html similarity index 82% rename from docs/build/html/backend_2common_2load_8h.html rename to docs/build/html/eval_8h.html index 83f8d0753..a04f1176e 100644 --- a/docs/build/html/backend_2common_2load_8h.html +++ b/docs/build/html/eval_8h.html @@ -5,7 +5,7 @@ -MLX: mlx/backend/common/load.h File Reference +MLX: mlx/backend/cpu/eval.h File Reference @@ -76,7 +76,7 @@ $(function() { codefold.init(0); });
    @@ -105,13 +105,13 @@ $(function(){initNavTree('backend_2common_2load_8h.html',''); initResizable(true
    Namespaces | Functions
    -
    load.h File Reference
    +
    eval.h File Reference
    #include "mlx/array.h"
    -#include "mlx/io/load.h"
    +#include "mlx/stream.h"
    -

    Go to the source code of this file.

    +

    Go to the source code of this file.

    @@ -119,18 +119,20 @@ Namespaces + +

    Namespaces

     
    namespace  mlx::core
     
    namespace  mlx::core::cpu
     
    - - + +

    Functions

    void mlx::core::load (array &out, size_t offset, const std::shared_ptr< io::Reader > &reader, bool swap_endianess)
     
    void mlx::core::cpu::eval (array &arr)
     
    diff --git a/docs/build/html/eval_8h.js b/docs/build/html/eval_8h.js new file mode 100644 index 000000000..900ac0819 --- /dev/null +++ b/docs/build/html/eval_8h.js @@ -0,0 +1,4 @@ +var eval_8h = +[ + [ "mlx::core::cpu::eval", "namespacemlx_1_1core_1_1cpu.html#a3f721e92f604a57ed204a13d1ba9cad5", null ] +]; \ No newline at end of file diff --git a/docs/build/html/backend_2common_2load_8h_source.html b/docs/build/html/eval_8h_source.html similarity index 69% rename from docs/build/html/backend_2common_2load_8h_source.html rename to docs/build/html/eval_8h_source.html index cc8dd5356..a86d467fb 100644 --- a/docs/build/html/backend_2common_2load_8h_source.html +++ b/docs/build/html/eval_8h_source.html @@ -5,7 +5,7 @@ -MLX: mlx/backend/common/load.h Source File +MLX: mlx/backend/cpu/eval.h Source File @@ -76,7 +76,7 @@ $(function() { codefold.init(0); });
    @@ -102,34 +102,32 @@ $(function(){initNavTree('backend_2common_2load_8h_source.html',''); initResizab
    -
    load.h
    +
    eval.h
    -Go to the documentation of this file.
    1// Copyright © 2024 Apple Inc.
    +Go to the documentation of this file.
    1// Copyright © 2025 Apple Inc.
    2
    -
    3#include "mlx/array.h"
    -
    4#include "mlx/io/load.h"
    -
    5
    -
    6namespace mlx::core {
    +
    3#pragma once
    +
    4
    +
    5#include "mlx/array.h"
    +
    6#include "mlx/stream.h"
    7
    -
    8void load(
    -
    9 array& out,
    -
    10 size_t offset,
    -
    11 const std::shared_ptr<io::Reader>& reader,
    -
    12 bool swap_endianess);
    -
    13
    -
    14} // namespace mlx::core
    +
    8namespace mlx::core::cpu {
    +
    9
    +
    10void eval(array& arr);
    +
    11
    +
    12} // namespace mlx::core::cpu
    mlx::core::array
    Definition array.h:24
    - -
    mlx::core
    Definition allocator.h:7
    -
    mlx::core::load
    void load(array &out, size_t offset, const std::shared_ptr< io::Reader > &reader, bool swap_endianess)
    +
    mlx::core::cpu
    Definition encoder.h:10
    +
    mlx::core::cpu::eval
    void eval(array &arr)
    +
    diff --git a/docs/build/html/event_8h_source.html b/docs/build/html/event_8h_source.html index 23fe9ada7..699de004d 100644 --- a/docs/build/html/event_8h_source.html +++ b/docs/build/html/event_8h_source.html @@ -116,76 +116,76 @@ $(function(){initNavTree('event_8h_source.html',''); initResizable(true); });
    9namespace mlx::core {
    10
    -
    11class Event {
    +
    11class Event {
    12 public:
    -
    13 Event() = default;
    -
    14
    -
    15 Event(const Stream& steam);
    -
    16
    -
    17 // Wait for the event to be signaled at its current value
    -
    18 void wait();
    -
    19
    -
    20 // Signal the event at its current value
    -
    21 void signal();
    -
    22
    -
    23 // Check if the event has been signaled at its current value
    -
    24 bool is_signaled() const;
    -
    25
    -
    26 // Check if the event is valid
    -
    -
    27 bool valid() const {
    -
    28 return event_ != nullptr;
    -
    29 }
    -
    +
    13 Event() {};
    +
    14 explicit Event(Stream stream);
    +
    15
    +
    16 // Wait for the event to be signaled at its current value
    +
    17 void wait();
    +
    18
    +
    19 // Signal the event at its current value
    +
    20 void signal();
    +
    21
    +
    22 // Wait in the given stream for the event to be signaled at its current value
    +
    23 void wait(Stream stream);
    +
    24
    +
    25 // Signal the event at its current value in the given stream
    +
    26 void signal(Stream stream);
    +
    27
    +
    28 // Check if the event has been signaled at its current value
    +
    29 bool is_signaled() const;
    30
    -
    -
    31 uint64_t value() const {
    -
    32 return value_;
    -
    33 }
    +
    31 // Check if the event is valid
    +
    +
    32 bool valid() const {
    +
    33 return event_ != nullptr;
    +
    34 }
    -
    34
    -
    -
    35 void set_value(uint64_t v) {
    -
    36 value_ = v;
    -
    37 }
    +
    35
    +
    +
    36 uint64_t value() const {
    +
    37 return value_;
    +
    38 }
    -
    38
    -
    -
    39 const Stream& stream() const {
    -
    40 if (!valid()) {
    -
    41 throw std::runtime_error(
    -
    42 "[Event::stream] Cannot access stream on invalid event.");
    -
    43 }
    -
    44 return stream_;
    -
    45 }
    +
    39
    +
    +
    40 void set_value(uint64_t v) {
    +
    41 value_ = v;
    +
    42 }
    -
    46
    -
    -
    47 const std::shared_ptr<void>& raw_event() const {
    -
    48 return event_;
    -
    49 }
    +
    43
    +
    +
    44 const Stream& stream() const {
    +
    45 if (!valid()) {
    +
    46 throw std::runtime_error(
    +
    47 "[Event::stream] Cannot access stream on invalid event.");
    +
    48 }
    +
    49 return stream_;
    +
    50 }
    -
    50
    -
    51 private:
    -
    52 // Default constructed stream should never be used
    -
    53 // since the event is not yet valid
    -
    54 Stream stream_{0, Device::cpu};
    -
    55 std::shared_ptr<void> event_;
    -
    56 uint64_t value_{0};
    -
    57};
    +
    51
    +
    52 private:
    +
    53 // Default constructed stream should never be used
    +
    54 // since the event is not yet valid
    +
    55 Stream stream_{0, Device::cpu};
    +
    56 std::shared_ptr<void> event_{nullptr};
    +
    57 uint64_t value_{0};
    +
    58};
    -
    58
    -
    59} // namespace mlx::core
    +
    59
    +
    60} // namespace mlx::core
    mlx::core::Event::is_signaled
    bool is_signaled() const
    -
    mlx::core::Event::set_value
    void set_value(uint64_t v)
    Definition event.h:35
    -
    mlx::core::Event::Event
    Event(const Stream &steam)
    -
    mlx::core::Event::stream
    const Stream & stream() const
    Definition event.h:39
    +
    mlx::core::Event::set_value
    void set_value(uint64_t v)
    Definition event.h:40
    +
    mlx::core::Event::stream
    const Stream & stream() const
    Definition event.h:44
    - -
    mlx::core::Event::valid
    bool valid() const
    Definition event.h:27
    -
    mlx::core::Event::value
    uint64_t value() const
    Definition event.h:31
    -
    mlx::core::Event::raw_event
    const std::shared_ptr< void > & raw_event() const
    Definition event.h:47
    +
    mlx::core::Event::Event
    Event()
    Definition event.h:13
    +
    mlx::core::Event::valid
    bool valid() const
    Definition event.h:32
    +
    mlx::core::Event::signal
    void signal(Stream stream)
    +
    mlx::core::Event::value
    uint64_t value() const
    Definition event.h:36
    +
    mlx::core::Event::wait
    void wait(Stream stream)
    +
    mlx::core::Event::Event
    Event(Stream stream)
    mlx::core
    Definition allocator.h:7
    mlx::core::Device::cpu
    static constexpr DeviceType cpu
    Definition device.h:13
    diff --git a/docs/build/html/examples/linear_regression.html b/docs/build/html/examples/linear_regression.html index 0a1ee1786..9b5af6615 100644 --- a/docs/build/html/examples/linear_regression.html +++ b/docs/build/html/examples/linear_regression.html @@ -8,7 +8,7 @@ - Linear Regression — MLX 0.23.2 documentation + Linear Regression — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
    diff --git a/docs/build/html/examples/llama-inference.html b/docs/build/html/examples/llama-inference.html index d1624e191..148ce9eaf 100644 --- a/docs/build/html/examples/llama-inference.html +++ b/docs/build/html/examples/llama-inference.html @@ -8,7 +8,7 @@ - LLM inference — MLX 0.23.2 documentation + LLM inference — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
    diff --git a/docs/build/html/examples/mlp.html b/docs/build/html/examples/mlp.html index 6a6db109a..3a3119a0e 100644 --- a/docs/build/html/examples/mlp.html +++ b/docs/build/html/examples/mlp.html @@ -8,7 +8,7 @@ - Multi-Layer Perceptron — MLX 0.23.2 documentation + Multi-Layer Perceptron — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
    diff --git a/docs/build/html/export__impl_8h.html b/docs/build/html/export__impl_8h.html index 3b92c07c1..7c53da06d 100644 --- a/docs/build/html/export__impl_8h.html +++ b/docs/build/html/export__impl_8h.html @@ -108,7 +108,7 @@ $(function(){initNavTree('export__impl_8h.html',''); initResizable(true); });
    export_impl.h File Reference
    -
    #include "mlx/io/load.h"
    +
    #include "mlx/io/load.h"

    Go to the source code of this file.

    diff --git a/docs/build/html/export__impl_8h_source.html b/docs/build/html/export__impl_8h_source.html index 28c407a10..7d5f46a97 100644 --- a/docs/build/html/export__impl_8h_source.html +++ b/docs/build/html/export__impl_8h_source.html @@ -107,7 +107,7 @@ $(function(){initNavTree('export__impl_8h_source.html',''); initResizable(true);
    Go to the documentation of this file.
    1// Copyright © 2024 Apple Inc.
    2
    -
    3#include "mlx/io/load.h"
    +
    3#include "mlx/io/load.h"
    4
    5#pragma once
    6
    @@ -185,7 +185,7 @@ $(function(){initNavTree('export__impl_8h_source.html',''); initResizable(true);
    70
    71} // namespace mlx::core
    mlx::core::io::FileWriter
    Definition load.h:109
    - +
    mlx::core
    Definition allocator.h:7
    mlx::core::Args
    std::vector< array > Args
    Definition export.h:11
    mlx::core::Kwargs
    std::map< std::string, array > Kwargs
    Definition export.h:12
    diff --git a/docs/build/html/fast_8h.html b/docs/build/html/fast_8h.html index 39e7f0a0d..66756e682 100644 --- a/docs/build/html/fast_8h.html +++ b/docs/build/html/fast_8h.html @@ -110,6 +110,7 @@ $(function(){initNavTree('fast_8h.html',''); initResizable(true); });
    #include <optional>
    +#include <variant>
    #include "mlx/utils.h"

    Go to the source code of this file.

    @@ -140,9 +141,9 @@ Functions
    - - - + + + diff --git a/docs/build/html/fast_8h.js b/docs/build/html/fast_8h.js index e67b6d541..6748a4771 100644 --- a/docs/build/html/fast_8h.js +++ b/docs/build/html/fast_8h.js @@ -9,5 +9,5 @@ var fast_8h = [ "mlx::core::fast::rms_norm", "namespacemlx_1_1core_1_1fast.html#a85ec3abc6b9d968c58275f5eef916f01", null ], [ "mlx::core::fast::rope", "namespacemlx_1_1core_1_1fast.html#a1632b78950f0c8c31b24be7d80faeb39", null ], [ "mlx::core::fast::rope", "namespacemlx_1_1core_1_1fast.html#a534ef357eae24892684a6ecd866d3fab", null ], - [ "mlx::core::fast::scaled_dot_product_attention", "namespacemlx_1_1core_1_1fast.html#a3663b50265b0a9c0cca2b5376852e059", null ] + [ "mlx::core::fast::scaled_dot_product_attention", "namespacemlx_1_1core_1_1fast.html#a4207ab2eb838335c0074f6bbb6b4cfc5", null ] ]; \ No newline at end of file diff --git a/docs/build/html/fast_8h_source.html b/docs/build/html/fast_8h_source.html index 2f3fd8a3f..e68f41407 100644 --- a/docs/build/html/fast_8h_source.html +++ b/docs/build/html/fast_8h_source.html @@ -110,102 +110,103 @@ $(function(){initNavTree('fast_8h_source.html',''); initResizable(true); });
    3#pragma once
    4
    5#include <optional>
    -
    6
    -
    7#include "mlx/utils.h"
    -
    8
    -
    -
    9namespace mlx::core::fast {
    -
    10
    -
    11array rms_norm(
    -
    12 const array& x,
    -
    13 const std::optional<array>& weight,
    -
    14 float eps,
    -
    15 StreamOrDevice s = {});
    -
    16
    -
    17array layer_norm(
    -
    18 const array& x,
    -
    19 const std::optional<array>& weight,
    -
    20 const std::optional<array>& bias,
    -
    21 float eps,
    -
    22 StreamOrDevice s = {});
    -
    23
    -
    24array rope(
    -
    25 const array& x,
    -
    26 int dims,
    -
    27 bool traditional,
    -
    28 std::optional<float> base,
    -
    29 float scale,
    -
    30 int offset,
    -
    31 const std::optional<array>& freqs = std::nullopt,
    -
    32 StreamOrDevice s = {});
    -
    33
    -
    34array rope(
    -
    35 const array& x,
    -
    36 int dims,
    -
    37 bool traditional,
    -
    38 std::optional<float> base,
    -
    39 float scale,
    -
    40 const array& offset,
    -
    41 const std::optional<array>& freqs = std::nullopt,
    -
    42 StreamOrDevice s = {});
    -
    43
    -
    45array scaled_dot_product_attention(
    -
    46 const array& queries,
    -
    47 const array& keys,
    -
    48 const array& values,
    -
    49 const float scale,
    -
    50 const std::optional<array>& mask = std::nullopt,
    -
    51 const std::optional<int> memory_efficient_threshold = std::nullopt,
    -
    52 StreamOrDevice s = {});
    -
    53
    -
    54std::tuple<array, array, array> affine_quantize(
    -
    55 const array& w,
    -
    56 int group_size = 64,
    -
    57 int bits = 4,
    -
    58 StreamOrDevice s = {});
    -
    59
    -
    60array affine_dequantize(
    -
    61 const array& w,
    -
    62 const array& scales,
    -
    63 const array& biases,
    -
    64 int group_size = 64,
    -
    65 int bits = 4,
    -
    66 StreamOrDevice s = {});
    -
    67
    -
    68typedef std::variant<int, bool, Dtype> TemplateArg;
    -
    69
    -
    70typedef std::function<std::vector<array>(
    -
    71 const std::vector<array>&,
    -
    72 const std::vector<Shape>&,
    -
    73 const std::vector<Dtype>&,
    -
    74 std::tuple<int, int, int>,
    +
    6#include <variant>
    +
    7
    +
    8#include "mlx/utils.h"
    +
    9
    +
    +
    10namespace mlx::core::fast {
    +
    11
    +
    12array rms_norm(
    +
    13 const array& x,
    +
    14 const std::optional<array>& weight,
    +
    15 float eps,
    +
    16 StreamOrDevice s = {});
    +
    17
    +
    18array layer_norm(
    +
    19 const array& x,
    +
    20 const std::optional<array>& weight,
    +
    21 const std::optional<array>& bias,
    +
    22 float eps,
    +
    23 StreamOrDevice s = {});
    +
    24
    +
    25array rope(
    +
    26 const array& x,
    +
    27 int dims,
    +
    28 bool traditional,
    +
    29 std::optional<float> base,
    +
    30 float scale,
    +
    31 int offset,
    +
    32 const std::optional<array>& freqs = std::nullopt,
    +
    33 StreamOrDevice s = {});
    +
    34
    +
    35array rope(
    +
    36 const array& x,
    +
    37 int dims,
    +
    38 bool traditional,
    +
    39 std::optional<float> base,
    +
    40 float scale,
    +
    41 const array& offset,
    +
    42 const std::optional<array>& freqs = std::nullopt,
    +
    43 StreamOrDevice s = {});
    +
    44
    +
    46array scaled_dot_product_attention(
    +
    47 const array& queries,
    +
    48 const array& keys,
    +
    49 const array& values,
    +
    50 const float scale,
    +
    51 const std::variant<std::monostate, std::string, array>& mask = {},
    +
    52 const std::optional<int> memory_efficient_threshold = std::nullopt,
    +
    53 StreamOrDevice s = {});
    +
    54
    +
    55std::tuple<array, array, array> affine_quantize(
    +
    56 const array& w,
    +
    57 int group_size = 64,
    +
    58 int bits = 4,
    +
    59 StreamOrDevice s = {});
    +
    60
    +
    61array affine_dequantize(
    +
    62 const array& w,
    +
    63 const array& scales,
    +
    64 const array& biases,
    +
    65 int group_size = 64,
    +
    66 int bits = 4,
    +
    67 StreamOrDevice s = {});
    +
    68
    +
    69typedef std::variant<int, bool, Dtype> TemplateArg;
    +
    70
    +
    71typedef std::function<std::vector<array>(
    +
    72 const std::vector<array>&,
    +
    73 const std::vector<Shape>&,
    +
    74 const std::vector<Dtype>&,
    75 std::tuple<int, int, int>,
    -
    76 std::vector<std::pair<std::string, TemplateArg>>,
    -
    77 std::optional<float>,
    -
    78 bool,
    -
    79 StreamOrDevice)>
    -
    80 MetalKernelFunction;
    -
    81
    -
    82MetalKernelFunction metal_kernel(
    -
    83 const std::string& name,
    -
    84 const std::vector<std::string>& input_names,
    -
    85 const std::vector<std::string>& output_names,
    -
    86 const std::string& source,
    -
    87 const std::string& header = "",
    -
    88 bool ensure_row_contiguous = true,
    -
    89 bool atomic_outputs = false);
    -
    90
    -
    91} // namespace mlx::core::fast
    +
    76 std::tuple<int, int, int>,
    +
    77 std::vector<std::pair<std::string, TemplateArg>>,
    +
    78 std::optional<float>,
    +
    79 bool,
    +
    80 StreamOrDevice)>
    +
    81 MetalKernelFunction;
    +
    82
    +
    83MetalKernelFunction metal_kernel(
    +
    84 const std::string& name,
    +
    85 const std::vector<std::string>& input_names,
    +
    86 const std::vector<std::string>& output_names,
    +
    87 const std::string& source,
    +
    88 const std::string& header = "",
    +
    89 bool ensure_row_contiguous = true,
    +
    90 bool atomic_outputs = false);
    +
    91
    +
    92} // namespace mlx::core::fast
    mlx::core::array
    Definition array.h:24
    -
    mlx::core::fast
    Definition fast.h:9
    +
    mlx::core::fast
    Definition fast.h:10
    mlx::core::fast::layer_norm
    array layer_norm(const array &x, const std::optional< array > &weight, const std::optional< array > &bias, float eps, StreamOrDevice s={})
    mlx::core::fast::affine_dequantize
    array affine_dequantize(const array &w, const array &scales, const array &biases, int group_size=64, int bits=4, StreamOrDevice s={})
    -
    mlx::core::fast::scaled_dot_product_attention
    array scaled_dot_product_attention(const array &queries, const array &keys, const array &values, const float scale, const std::optional< array > &mask=std::nullopt, const std::optional< int > memory_efficient_threshold=std::nullopt, StreamOrDevice s={})
    Computes: O = softmax(Q @ K.T) @ V.
    +
    mlx::core::fast::scaled_dot_product_attention
    array scaled_dot_product_attention(const array &queries, const array &keys, const array &values, const float scale, const std::variant< std::monostate, std::string, array > &mask={}, const std::optional< int > memory_efficient_threshold=std::nullopt, StreamOrDevice s={})
    Computes: O = softmax(Q @ K.T) @ V.
    mlx::core::fast::rope
    array rope(const array &x, int dims, bool traditional, std::optional< float > base, float scale, int offset, const std::optional< array > &freqs=std::nullopt, StreamOrDevice s={})
    mlx::core::fast::rms_norm
    array rms_norm(const array &x, const std::optional< array > &weight, float eps, StreamOrDevice s={})
    -
    mlx::core::fast::TemplateArg
    std::variant< int, bool, Dtype > TemplateArg
    Definition fast.h:68
    -
    mlx::core::fast::MetalKernelFunction
    std::function< std::vector< array >(const std::vector< array > &, const std::vector< Shape > &, const std::vector< Dtype > &, std::tuple< int, int, int >, std::tuple< int, int, int >, std::vector< std::pair< std::string, TemplateArg > >, std::optional< float >, bool, StreamOrDevice)> MetalKernelFunction
    Definition fast.h:80
    +
    mlx::core::fast::TemplateArg
    std::variant< int, bool, Dtype > TemplateArg
    Definition fast.h:69
    +
    mlx::core::fast::MetalKernelFunction
    std::function< std::vector< array >(const std::vector< array > &, const std::vector< Shape > &, const std::vector< Dtype > &, std::tuple< int, int, int >, std::tuple< int, int, int >, std::vector< std::pair< std::string, TemplateArg > >, std::optional< float >, bool, StreamOrDevice)> MetalKernelFunction
    Definition fast.h:81
    mlx::core::fast::affine_quantize
    std::tuple< array, array, array > affine_quantize(const array &w, int group_size=64, int bits=4, StreamOrDevice s={})
    mlx::core::fast::metal_kernel
    MetalKernelFunction metal_kernel(const std::string &name, const std::vector< std::string > &input_names, const std::vector< std::string > &output_names, const std::string &source, const std::string &header="", bool ensure_row_contiguous=true, bool atomic_outputs=false)
    mlx::core::StreamOrDevice
    std::variant< std::monostate, Stream, Device > StreamOrDevice
    Definition utils.h:15
    diff --git a/docs/build/html/fast__primitives_8h_source.html b/docs/build/html/fast__primitives_8h_source.html index bf53e86fa..3346cfc3b 100644 --- a/docs/build/html/fast__primitives_8h_source.html +++ b/docs/build/html/fast__primitives_8h_source.html @@ -353,142 +353,144 @@ $(function(){initNavTree('fast__primitives_8h_source.html',''); initResizable(tr
    203
    -
    204class ScaledDotProductAttention : public Custom {
    +
    204class ScaledDotProductAttention : public Custom {
    205 public:
    -
    206 explicit ScaledDotProductAttention(
    +
    206 explicit ScaledDotProductAttention(
    207 Stream stream,
    208 std::function<std::vector<array>(std::vector<array>)> fallback,
    -
    209 const float scale)
    -
    210 : Custom(stream, fallback), scale_(scale) {}
    +
    209 const float scale,
    +
    210 const bool do_causal)
    +
    211 : Custom(stream, fallback), scale_(scale), do_causal_(do_causal) {}
    -
    211
    -
    -
    212 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    213 override {
    -
    214 throw std::runtime_error("NYI");
    -
    215 }
    +
    212
    +
    +
    213 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    214 override {
    +
    215 throw std::runtime_error("NYI");
    +
    216 }
    -
    216
    -
    -
    217 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    218 override {
    -
    219 eval_gpu(inputs, outputs[0]);
    -
    220 }
    +
    217
    +
    +
    218 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    219 override {
    +
    220 eval_gpu(inputs, outputs[0]);
    +
    221 }
    -
    221
    -
    222 void eval_gpu(const std::vector<array>& inputs, array& out);
    -
    223 bool is_equivalent(const Primitive& other) const override;
    -
    224
    -
    225 DEFINE_PRINT(ScaledDotProductAttention);
    -
    -
    226 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    227 auto state() const {
    -
    228 return std::make_pair(nullptr, scale_);
    -
    229 }
    +
    222
    +
    223 void eval_gpu(const std::vector<array>& inputs, array& out);
    +
    224 bool is_equivalent(const Primitive& other) const override;
    +
    225
    +
    226 DEFINE_PRINT(ScaledDotProductAttention);
    +
    +
    227 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    228 auto state() const {
    +
    229 return std::make_tuple(nullptr, scale_, do_causal_);
    +
    230 }
    -
    230
    -
    231 private:
    -
    232 std::function<std::vector<array>(std::vector<array>)> fallback_;
    -
    233 float scale_;
    -
    234};
    +
    231
    +
    232 private:
    +
    233 std::function<std::vector<array>(std::vector<array>)> fallback_;
    +
    234 float scale_;
    +
    235 bool do_causal_;
    +
    236};
    -
    235
    -
    -
    236class AffineQuantize : public Custom {
    -
    237 public:
    -
    -
    238 explicit AffineQuantize(
    -
    239 Stream stream,
    -
    240 std::function<std::vector<array>(std::vector<array>)> fallback,
    -
    241 int group_size,
    -
    242 int bits,
    -
    243 bool dequantize)
    -
    244 : Custom(stream, fallback),
    -
    245 group_size_(group_size),
    -
    246 bits_(bits),
    -
    247 dequantize_(dequantize) {}
    +
    237
    +
    +
    238class AffineQuantize : public Custom {
    +
    239 public:
    +
    +
    240 explicit AffineQuantize(
    +
    241 Stream stream,
    +
    242 std::function<std::vector<array>(std::vector<array>)> fallback,
    +
    243 int group_size,
    +
    244 int bits,
    +
    245 bool dequantize)
    +
    246 : Custom(stream, fallback),
    +
    247 group_size_(group_size),
    +
    248 bits_(bits),
    +
    249 dequantize_(dequantize) {}
    -
    248
    -
    249 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    250 override;
    -
    251
    -
    252 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    253 override;
    -
    254
    -
    255 DEFINE_PRINT(AffineQuantize);
    +
    250
    +
    251 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    252 override;
    +
    253
    +
    254 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    255 override;
    256
    -
    257 bool is_equivalent(const Primitive& other) const override;
    -
    258 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    -
    259 auto state() const {
    -
    260 return std::make_tuple(nullptr, group_size_, bits_, dequantize_);
    -
    261 }
    +
    257 DEFINE_PRINT(AffineQuantize);
    +
    258
    +
    259 bool is_equivalent(const Primitive& other) const override;
    +
    260 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    +
    261 auto state() const {
    +
    262 return std::make_tuple(nullptr, group_size_, bits_, dequantize_);
    +
    263 }
    -
    262
    -
    263 private:
    -
    264 std::function<std::vector<array>(std::vector<array>)> fallback_;
    -
    265 int group_size_;
    -
    266 int bits_;
    -
    267 bool dequantize_;
    -
    268};
    +
    264
    +
    265 private:
    +
    266 std::function<std::vector<array>(std::vector<array>)> fallback_;
    +
    267 int group_size_;
    +
    268 int bits_;
    +
    269 bool dequantize_;
    +
    270};
    -
    269
    -
    -
    270struct CustomKernelShapeInfo {
    -
    271 bool shape = false;
    -
    272 bool strides = false;
    -
    273 bool ndim = false;
    -
    274};
    +
    271
    +
    +
    272struct CustomKernelShapeInfo {
    +
    273 bool shape = false;
    +
    274 bool strides = false;
    +
    275 bool ndim = false;
    +
    276};
    -
    275
    -
    -
    276class CustomKernel : public Primitive {
    -
    277 public:
    -
    -
    278 CustomKernel(
    -
    279 Stream stream,
    -
    280 std::string name,
    -
    281 std::string source,
    -
    282 std::tuple<int, int, int> grid,
    -
    283 std::tuple<int, int, int> threadgroup,
    -
    284 std::vector<CustomKernelShapeInfo> shape_infos,
    -
    285 bool ensure_row_contiguous,
    -
    286 std::optional<float> init_value)
    -
    287 : Primitive(stream),
    -
    288 source_(std::move(source)),
    -
    289 name_(std::move(name)),
    -
    290 grid_(grid),
    -
    291 threadgroup_(threadgroup),
    -
    292 shape_infos_(std::move(shape_infos)),
    -
    293 ensure_row_contiguous_(ensure_row_contiguous),
    -
    294 init_value_(init_value) {}
    +
    277
    +
    +
    278class CustomKernel : public Primitive {
    +
    279 public:
    +
    +
    280 CustomKernel(
    +
    281 Stream stream,
    +
    282 std::string name,
    +
    283 std::string source,
    +
    284 std::tuple<int, int, int> grid,
    +
    285 std::tuple<int, int, int> threadgroup,
    +
    286 std::vector<CustomKernelShapeInfo> shape_infos,
    +
    287 bool ensure_row_contiguous,
    +
    288 std::optional<float> init_value)
    +
    289 : Primitive(stream),
    +
    290 source_(std::move(source)),
    +
    291 name_(std::move(name)),
    +
    292 grid_(grid),
    +
    293 threadgroup_(threadgroup),
    +
    294 shape_infos_(std::move(shape_infos)),
    +
    295 ensure_row_contiguous_(ensure_row_contiguous),
    +
    296 init_value_(init_value) {}
    -
    295
    -
    -
    296 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    297 override {
    -
    298 throw std::runtime_error("Custom Metal kernels only run on GPU.");
    -
    299 }
    +
    297
    +
    +
    298 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    299 override {
    +
    300 throw std::runtime_error("Custom Metal kernels only run on GPU.");
    +
    301 }
    -
    300
    -
    301 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    302 override;
    -
    303
    -
    304 DEFINE_PRINT(CustomKernel);
    +
    302
    +
    303 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    304 override;
    305
    -
    306 private:
    -
    307 std::string source_;
    -
    308 std::string name_;
    -
    309 std::tuple<int, int, int> grid_;
    -
    310 std::tuple<int, int, int> threadgroup_;
    -
    311 std::vector<CustomKernelShapeInfo> shape_infos_;
    -
    312 bool ensure_row_contiguous_;
    -
    313 std::optional<float> init_value_;
    -
    314};
    +
    306 DEFINE_PRINT(CustomKernel);
    +
    307
    +
    308 private:
    +
    309 std::string source_;
    +
    310 std::string name_;
    +
    311 std::tuple<int, int, int> grid_;
    +
    312 std::tuple<int, int, int> threadgroup_;
    +
    313 std::vector<CustomKernelShapeInfo> shape_infos_;
    +
    314 bool ensure_row_contiguous_;
    +
    315 std::optional<float> init_value_;
    +
    316};
    -
    315
    -
    316} // namespace mlx::core::fast
    +
    317
    +
    318} // namespace mlx::core::fast
    mlx::core::Primitive::stream
    const Stream & stream()
    The stream the primitive will run on.
    Definition primitives.h:58
    mlx::core::Primitive::is_equivalent
    virtual bool is_equivalent(const Primitive &other) const
    Equivalence check defaults to false unless overridden by the primitive.
    Definition primitives.h:107
    mlx::core::Primitive::Primitive
    Primitive(Stream stream)
    Definition primitives.h:50
    @@ -498,16 +500,16 @@ $(function(){initNavTree('fast__primitives_8h_source.html',''); initResizable(tr
    mlx::core::fast::AffineQuantize::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    mlx::core::fast::AffineQuantize::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::fast::AffineQuantize::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    -
    mlx::core::fast::AffineQuantize::AffineQuantize
    AffineQuantize(Stream stream, std::function< std::vector< array >(std::vector< array >)> fallback, int group_size, int bits, bool dequantize)
    Definition fast_primitives.h:238
    -
    mlx::core::fast::AffineQuantize::state
    auto state() const
    Definition fast_primitives.h:259
    +
    mlx::core::fast::AffineQuantize::AffineQuantize
    AffineQuantize(Stream stream, std::function< std::vector< array >(std::vector< array >)> fallback, int group_size, int bits, bool dequantize)
    Definition fast_primitives.h:240
    +
    mlx::core::fast::AffineQuantize::state
    auto state() const
    Definition fast_primitives.h:261
    mlx::core::fast::Custom::Custom
    Custom(Stream stream, std::function< std::vector< array >(std::vector< array >)> fallback)
    Definition fast_primitives.h:14
    mlx::core::fast::Custom::vjp
    virtual std::vector< array > vjp(const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs) override
    The vector-Jacobian product.
    mlx::core::fast::Custom::vmap
    virtual std::pair< std::vector< array >, std::vector< int > > vmap(const std::vector< array > &inputs, const std::vector< int > &axes) override
    The primitive must know how to vectorize itself across the given axes.
    mlx::core::fast::Custom::jvp
    virtual std::vector< array > jvp(const std::vector< array > &primals, const std::vector< array > &tangents, const std::vector< int > &argnums) override
    The Jacobian-vector product.
    mlx::core::fast::CustomKernel::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    -
    mlx::core::fast::CustomKernel::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    Definition fast_primitives.h:296
    -
    mlx::core::fast::CustomKernel::CustomKernel
    CustomKernel(Stream stream, std::string name, std::string source, std::tuple< int, int, int > grid, std::tuple< int, int, int > threadgroup, std::vector< CustomKernelShapeInfo > shape_infos, bool ensure_row_contiguous, std::optional< float > init_value)
    Definition fast_primitives.h:278
    +
    mlx::core::fast::CustomKernel::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    Definition fast_primitives.h:298
    +
    mlx::core::fast::CustomKernel::CustomKernel
    CustomKernel(Stream stream, std::string name, std::string source, std::tuple< int, int, int > grid, std::tuple< int, int, int > threadgroup, std::vector< CustomKernelShapeInfo > shape_infos, bool ensure_row_contiguous, std::optional< float > init_value)
    Definition fast_primitives.h:280
    mlx::core::fast::LayerNorm::DEFINE_PRINT
    DEFINE_PRINT(LayerNorm) bool is_equivalent(const Primitive &other) const override
    mlx::core::fast::LayerNorm::LayerNorm
    LayerNorm(Stream stream, std::function< std::vector< array >(std::vector< array >)> fallback, float eps)
    Definition fast_primitives.h:100
    mlx::core::fast::LayerNorm::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    Definition fast_primitives.h:106
    @@ -536,22 +538,23 @@ $(function(){initNavTree('fast__primitives_8h_source.html',''); initResizable(tr
    mlx::core::fast::RoPE::RoPE
    RoPE(Stream stream, std::function< std::vector< array >(std::vector< array >)> fallback, int dims, bool traditional, float base, float scale, bool forward)
    Definition fast_primitives.h:159
    mlx::core::fast::RoPE::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    mlx::core::fast::RoPE::vjp
    std::vector< array > vjp(const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs) override
    The vector-Jacobian product.
    -
    mlx::core::fast::ScaledDotProductAttention::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    Definition fast_primitives.h:217
    -
    mlx::core::fast::ScaledDotProductAttention::DEFINE_INPUT_OUTPUT_SHAPE
    DEFINE_INPUT_OUTPUT_SHAPE() auto state() const
    Definition fast_primitives.h:226
    +
    mlx::core::fast::ScaledDotProductAttention::ScaledDotProductAttention
    ScaledDotProductAttention(Stream stream, std::function< std::vector< array >(std::vector< array >)> fallback, const float scale, const bool do_causal)
    Definition fast_primitives.h:206
    +
    mlx::core::fast::ScaledDotProductAttention::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    Definition fast_primitives.h:218
    +
    mlx::core::fast::ScaledDotProductAttention::DEFINE_INPUT_OUTPUT_SHAPE
    DEFINE_INPUT_OUTPUT_SHAPE() auto state() const
    Definition fast_primitives.h:227
    mlx::core::fast::ScaledDotProductAttention::DEFINE_PRINT
    DEFINE_PRINT(ScaledDotProductAttention)
    -
    mlx::core::fast::ScaledDotProductAttention::ScaledDotProductAttention
    ScaledDotProductAttention(Stream stream, std::function< std::vector< array >(std::vector< array >)> fallback, const float scale)
    Definition fast_primitives.h:206
    mlx::core::fast::ScaledDotProductAttention::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out)
    -
    mlx::core::fast::ScaledDotProductAttention::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    Definition fast_primitives.h:212
    +
    mlx::core::fast::ScaledDotProductAttention::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    Definition fast_primitives.h:213
    mlx::core::fast::ScaledDotProductAttention::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::std
    array std(const array &a, bool keepdims, int ddof=0, StreamOrDevice s={})
    Computes the standard deviation of the elements of an array.
    mlx::core::dequantize
    array dequantize(const array &w, const array &scales, const array &biases, int group_size=64, int bits=4, StreamOrDevice s={})
    Dequantize a matrix produced by quantize()
    -
    mlx::core::fast
    Definition fast.h:9
    +
    mlx::core::fast
    Definition fast.h:10
    +
    do_causal
    constant bool do_causal
    Definition steel_attention.h:13
    mlx::core::Stream
    Definition stream.h:9
    -
    mlx::core::fast::CustomKernelShapeInfo
    Definition fast_primitives.h:270
    -
    mlx::core::fast::CustomKernelShapeInfo::strides
    bool strides
    Definition fast_primitives.h:272
    -
    mlx::core::fast::CustomKernelShapeInfo::shape
    bool shape
    Definition fast_primitives.h:271
    -
    mlx::core::fast::CustomKernelShapeInfo::ndim
    bool ndim
    Definition fast_primitives.h:273
    +
    mlx::core::fast::CustomKernelShapeInfo
    Definition fast_primitives.h:272
    +
    mlx::core::fast::CustomKernelShapeInfo::strides
    bool strides
    Definition fast_primitives.h:274
    +
    mlx::core::fast::CustomKernelShapeInfo::shape
    bool shape
    Definition fast_primitives.h:273
    +
    mlx::core::fast::CustomKernelShapeInfo::ndim
    bool ndim
    Definition fast_primitives.h:275
    diff --git a/docs/build/html/fence_8h.html b/docs/build/html/fence_8h.html index 52f893a40..674ce653f 100644 --- a/docs/build/html/fence_8h.html +++ b/docs/build/html/fence_8h.html @@ -5,7 +5,7 @@ -MLX: mlx/backend/metal/fence.h File Reference +MLX: mlx/fence.h File Reference @@ -108,7 +108,8 @@ $(function(){initNavTree('fence_8h.html',''); initResizable(true); });
    fence.h File Reference
    -
    #include "mlx/backend/metal/device.h"
    +
    #include <vector>
    +#include "mlx/array.h"

    Go to the source code of this file.

     
    array mlx::core::fast::rope (const array &x, int dims, bool traditional, std::optional< float > base, float scale, const array &offset, const std::optional< array > &freqs=std::nullopt, StreamOrDevice s={})
     
    array mlx::core::fast::scaled_dot_product_attention (const array &queries, const array &keys, const array &values, const float scale, const std::optional< array > &mask=std::nullopt, const std::optional< int > memory_efficient_threshold=std::nullopt, StreamOrDevice s={})
     Computes: O = softmax(Q @ K.T) @ V.
     
    array mlx::core::fast::scaled_dot_product_attention (const array &queries, const array &keys, const array &values, const float scale, const std::variant< std::monostate, std::string, array > &mask={}, const std::optional< int > memory_efficient_threshold=std::nullopt, StreamOrDevice s={})
     Computes: O = softmax(Q @ K.T) @ V.
     
    std::tuple< array, array, array > mlx::core::fast::affine_quantize (const array &w, int group_size=64, int bits=4, StreamOrDevice s={})
     
    array mlx::core::fast::affine_dequantize (const array &w, const array &scales, const array &biases, int group_size=64, int bits=4, StreamOrDevice s={})
    @@ -129,7 +130,7 @@ Namespaces diff --git a/docs/build/html/fence_8h_source.html b/docs/build/html/fence_8h_source.html index 45ecd60c3..b53a5c2a9 100644 --- a/docs/build/html/fence_8h_source.html +++ b/docs/build/html/fence_8h_source.html @@ -5,7 +5,7 @@ -MLX: mlx/backend/metal/fence.h Source File +MLX: mlx/fence.h Source File @@ -107,52 +107,50 @@ $(function(){initNavTree('fence_8h_source.html',''); initResizable(true); });
    Go to the documentation of this file.
    1// Copyright © 2024 Apple Inc.
    2
    -
    3#include "mlx/backend/metal/device.h"
    +
    3#include <vector>
    4
    -
    5namespace mlx::core {
    +
    5#include "mlx/array.h"
    6
    -
    7/* A fence to be used for synchronizing work between the CPU and GPU
    -
    8 *
    -
    9 * Calls to `update_gpu` should be paired with calls to `wait`. This ensures
    -
    10 * that the array passed to `update_gpu` is computed and visible to the CPU
    -
    11 * after the call to `wait` returns.
    -
    12 *
    -
    13 * Calls to `update` should be paired with calls to `wait_gpu`. This ensures
    -
    14 * that the array passed to `wait_gpu` will not be read by the GPU until the CPU
    -
    15 * has called `update`.
    -
    16 *
    -
    17 * The fence supports slow (default) and fast mode. Fast mode requires setting
    -
    18 * the environment variable `MLX_METAL_FAST_SYNCH=1`. Fast mode also requires
    -
    19 * Metal 3.2+ (macOS 15+, iOS 18+).
    -
    20 */
    -
    -
    21class Fence {
    -
    22 public:
    -
    23 Fence(const Stream& stream);
    -
    24
    -
    25 void update_gpu(const array& x);
    -
    26 void wait_gpu(array& x);
    -
    27
    -
    28 void wait();
    -
    29 void update();
    -
    30
    -
    31 private:
    -
    32 Stream stream_;
    -
    33 std::shared_ptr<void> fence_;
    -
    34 uint32_t cpu_count_{0};
    -
    35 uint32_t gpu_count_{0};
    -
    36 bool use_fast_;
    -
    37 std::atomic_uint* cpu_value();
    -
    38};
    +
    7namespace mlx::core {
    +
    8
    +
    9/* A fence to be used for synchronizing work between streams.
    +
    10 *
    +
    11 * Calls to `wait` wait in the given stream until all previous calls to update
    +
    12 * are complete on their given stream.
    +
    13 *
    +
    14 * The array passed to `update` is computed and visible after the call to
    +
    15 * `wait` returns. The array passed to `wait` will not be read until all
    +
    16 * previous calls to `update` have completed.
    +
    17 *
    +
    18 * Note, calls to `update` should always from the same thread or explicitly
    +
    19 * synchronized so that they occur in sequence. Calls to `wait` can be on any
    +
    20 * thread.
    +
    21 *
    +
    22 * For the Metal back-end the fence supports slow (default) and fast mode.
    +
    23 * Fast mode requires setting the environment variable
    +
    24 * `MLX_METAL_FAST_SYNCH=1`. Fast mode also requires Metal 3.2+ (macOS 15+,
    +
    25 * iOS 18+).
    +
    26 */
    +
    +
    27class Fence {
    +
    28 public:
    +
    29 Fence() {};
    +
    30 explicit Fence(Stream stream);
    +
    31
    +
    32 void update(Stream stream, const array& x);
    +
    33 void wait(Stream stream, const array& x);
    +
    34
    +
    35 private:
    +
    36 std::shared_ptr<void> fence_{nullptr};
    +
    37};
    -
    39
    -
    40} // namespace mlx::core
    - - -
    mlx::core::Fence::Fence
    Fence(const Stream &stream)
    - -
    mlx::core::Fence::update_gpu
    void update_gpu(const array &x)
    -
    mlx::core::Fence::wait_gpu
    void wait_gpu(array &x)
    +
    38
    +
    39} // namespace mlx::core
    + +
    mlx::core::Fence::update
    void update(Stream stream, const array &x)
    +
    mlx::core::Fence::Fence
    Fence(Stream stream)
    +
    mlx::core::Fence::wait
    void wait(Stream stream, const array &x)
    +
    mlx::core::Fence::Fence
    Fence()
    Definition fence.h:29
    mlx::core::array
    Definition array.h:24
    mlx::core
    Definition allocator.h:7
    mlx::core::Stream
    Definition stream.h:9
    @@ -161,7 +159,7 @@ $(function(){initNavTree('fence_8h_source.html',''); initResizable(true); }); diff --git a/docs/build/html/files.html b/docs/build/html/files.html index bb157e442..b3f66c1be 100644 --- a/docs/build/html/files.html +++ b/docs/build/html/files.html @@ -116,183 +116,183 @@ $(function(){initNavTree('files.html',''); initResizable(true); });
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
     compiled.h
     copy.h
     hadamard.h
     load.h
     reduce.h
     slicing.h
     ternary.h
     utils.h
     ▼ cpu
     ► simd
     arange.h
     binary.h
     binary_ops.h
     binary_two.h
     compiled_preamble.h
     copy.h
     gemm.h
     jit_compiler.h
     lapack.h
     slicing.h
     ternary.h
     threefry.h
     unary.h
     unary_ops.h
     ▼ metal
     ► jit
     ► kernels
     allocator.h
     binary.h
     copy.h
     device.h
     event.h
     fence.h
     kernels.h
     matmul.h
     metal.h
     metal_impl.h
     reduce.h
     resident.h
     slicing.h
     ternary.h
     unary.h
     utils.h
     ▼ distributed
     ▼ mpi
     mpi.h
     ▼ ring
     ring.h
     distributed.h
     distributed_impl.h
     ops.h
     primitives.h
     ▼ io
     gguf.h
     load.h
     ▼ types
     bf16.h
     complex.h
     fp16.h
     half_types.h
     limits.h
     allocator.h
     array.h
     compile.h
     compile_impl.h
     device.h
     dtype.h
     einsum.h
     event.h
     export.h
     export_impl.h
     fast.h
     fast_primitives.h
     fft.h
     graph_utils.h
     io.h
     linalg.h
     mlx.h
     ops.h
     primitives.h
     random.h
     scheduler.h
     stream.h
     threadpool.h
     transforms.h
     transforms_impl.h
     utils.h
     version.h
     reduce.h
     slicing.h
     ternary.h
     utils.h
     ▼ cpu
     ► simd
     arange.h
     binary.h
     binary_ops.h
     binary_two.h
     compiled_preamble.h
     copy.h
     encoder.h
     eval.h
     gemm.h
     jit_compiler.h
     lapack.h
     slicing.h
     ternary.h
     threefry.h
     unary.h
     unary_ops.h
     ▼ metal
     ► jit
     ► kernels
     allocator.h
     binary.h
     copy.h
     device.h
     kernels.h
     matmul.h
     metal.h
     metal_impl.h
     reduce.h
     resident.h
     slicing.h
     ternary.h
     unary.h
     utils.h
     ▼ distributed
     ▼ mpi
     mpi.h
     ▼ ring
     ring.h
     distributed.h
     distributed_impl.h
     ops.h
     primitives.h
     ▼ io
     gguf.h
     load.h
     ▼ types
     bf16.h
     complex.h
     fp16.h
     half_types.h
     limits.h
     allocator.h
     array.h
     compile.h
     compile_impl.h
     device.h
     dtype.h
     einsum.h
     event.h
     export.h
     export_impl.h
     fast.h
     fast_primitives.h
     fence.h
     fft.h
     graph_utils.h
     io.h
     linalg.h
     mlx.h
     ops.h
     primitives.h
     random.h
     scheduler.h
     stream.h
     threadpool.h
     transforms.h
     transforms_impl.h
     utils.h
     version.h
    diff --git a/docs/build/html/functions_a.html b/docs/build/html/functions_a.html index 3c815a8b2..35a0f1f4b 100644 --- a/docs/build/html/functions_a.html +++ b/docs/build/html/functions_a.html @@ -111,8 +111,8 @@ $(function(){initNavTree('functions_a.html',''); initResizable(true); });
  • Abs() : mlx::core::Abs
  • accum_type : mlx::steel::AccumHelper< T >
  • Add() : mlx::core::Add
    • -
  • add_temporaries() : mlx::core::metal::Device
    • -
  • add_temporary() : mlx::core::metal::Device
    • +
  • add_temporaries() : mlx::core::cpu::CommandEncoder, mlx::core::metal::Device
    • +
  • add_temporary() : mlx::core::cpu::CommandEncoder, mlx::core::metal::Device
  • AddMM() : mlx::core::AddMM
  • adj_implicit_m : mlx::steel::Conv2DGeneralJumpParams
  • adj_out_h : mlx::steel::Conv2DGeneralJumpParams
    • @@ -121,8 +121,8 @@ $(function(){initNavTree('functions_a.html',''); initResizable(true); });
  • advance() : pocketfft::detail::multi_iter< N >, pocketfft::detail::rev_iter, pocketfft::detail::simple_iter
  • AffineQuantize() : mlx::core::fast::AffineQuantize
  • aligned_allocator() : pocketfft::detail::threading::aligned_allocator< T >
    • -
  • all_gather() : mlx::core::distributed::detail::GroupImpl
    • -
  • all_sum() : mlx::core::distributed::detail::GroupImpl
    • +
  • all_gather() : mlx::core::distributed::detail::GroupImpl
    • +
  • all_sum() : mlx::core::distributed::detail::GroupImpl
  • AllGather() : mlx::core::distributed::AllGather
  • allocate() : pocketfft::detail::threading::aligned_allocator< T >
  • Allocator() : mlx::core::allocator::Allocator
    • diff --git a/docs/build/html/functions_b.html b/docs/build/html/functions_b.html index 95eacadb1..ca126dc5d 100644 --- a/docs/build/html/functions_b.html +++ b/docs/build/html/functions_b.html @@ -134,10 +134,10 @@ $(function(){initNavTree('functions_b.html',''); initResizable(true); });
  • block_sort() : KernelMergeSort< T, U, ARG_SORT, BLOCK_THREADS, N_PER_THREAD, CompareOp >, KernelMultiBlockMergeSort< ValT, IdxT, ARG_SORT, BLOCK_THREADS, N_PER_THREAD, CompareOp >
  • BlockLoader() : mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >
  • BlockLoaderT() : mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >
    • -
  • blockM : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >
    • +
  • blockM : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >
  • BlockMaskedMM() : mlx::core::BlockMaskedMM
  • BlockMMA() : mlx::steel::BlockMMA< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, lda_tgp, ldb_tgp, AccumType, Epilogue >
    • -
  • blockN : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >
    • +
  • blockN : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >
  • Broadcast() : mlx::core::Broadcast
  • BroadcastAxes() : mlx::core::BroadcastAxes
  • BROWS : mlx::steel::Conv2DInputBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderLargeFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoader< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >
    • diff --git a/docs/build/html/functions_c.html b/docs/build/html/functions_c.html index 248667a39..6ddccd8ee 100644 --- a/docs/build/html/functions_c.html +++ b/docs/build/html/functions_c.html @@ -120,7 +120,7 @@ $(function(){initNavTree('functions_c.html',''); initResizable(true); });
  • col_contiguous : mlx::core::array::Flags
  • col_frag_type : mlx::steel::BaseMMAFrag< T, 8, 8 >
  • command_buffer_needs_commit() : mlx::core::metal::Device
    • -
  • CommandEncoder() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
    • +
  • CommandEncoder() : mlx::core::CommandEncoder, mlx::core::cpu::CommandEncoder, mlx::core::metal::CommandEncoder
  • commit_command_buffer() : mlx::core::metal::Device
  • Compiled() : mlx::core::Compiled
  • complex128_t() : mlx::core::complex128_t
    • diff --git a/docs/build/html/functions_d.html b/docs/build/html/functions_d.html index d1a96f70b..64e3ca09b 100644 --- a/docs/build/html/functions_d.html +++ b/docs/build/html/functions_d.html @@ -118,6 +118,7 @@ $(function(){initNavTree('functions_d.html',''); initResizable(true); });
  • denorm_min() : metal::_numeric_limits_impl< bfloat16_t >
  • Depends() : mlx::core::Depends
  • detach() : mlx::core::array
    • +
  • detach_event() : mlx::core::array
  • Device() : mlx::core::Device, mlx::core::metal::Device
  • device() : mlx::core::Primitive, mlx::core::Stream
  • DeviceStream() : mlx::core::metal::DeviceStream
    • @@ -126,6 +127,7 @@ $(function(){initNavTree('functions_d.html',''); initResizable(true); });
  • digits : metal::_numeric_limits_impl< bfloat16_t >
  • digits10 : metal::_numeric_limits_impl< bfloat16_t >
  • dim : LoopedElemToLoc< DIM, OffsetT, General >, LoopedElemToLoc< 1, OffsetT, false >, LoopedElemToLoc< 1, OffsetT, true >
    • +
  • dispatch() : mlx::core::cpu::CommandEncoder
  • dispatch_threadgroups() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
  • dispatch_threads() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
  • DistPrimitive() : mlx::core::distributed::DistPrimitive
    • diff --git a/docs/build/html/functions_e.html b/docs/build/html/functions_e.html index f30c1e350..a1ad61baa 100644 --- a/docs/build/html/functions_e.html +++ b/docs/build/html/functions_e.html @@ -125,7 +125,7 @@ $(function(){initNavTree('functions_e.html',''); initResizable(true); });
  • eval_cpu() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Recv, mlx::core::distributed::Send, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::AffineQuantize, mlx::core::fast::CustomKernel, mlx::core::fast::LayerNorm, mlx::core::fast::LayerNormVJP, mlx::core::fast::RMSNorm, mlx::core::fast::RMSNormVJP, mlx::core::fast::RoPE, mlx::core::fast::ScaledDotProductAttention, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::LUF, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QRF, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::UnaryPrimitive, mlx::core::Unflatten, mlx::core::View
  • eval_gpu() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Recv, mlx::core::distributed::Send, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::AffineQuantize, mlx::core::fast::CustomKernel, mlx::core::fast::LayerNorm, mlx::core::fast::LayerNormVJP, mlx::core::fast::RMSNorm, mlx::core::fast::RMSNormVJP, mlx::core::fast::RoPE, mlx::core::fast::ScaledDotProductAttention, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::LUF, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QRF, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::UnaryPrimitive, mlx::core::Unflatten, mlx::core::View
  • evaluated : mlx::core::array
    • -
  • Event() : mlx::core::Event
    • +
  • Event() : mlx::core::Event
  • event() : mlx::core::array
  • excess : mlx::steel::ChannelHelper< n_channels_ >, mlx::steel::ChannelHelper< 1 >, mlx::steel::ChannelHelper< 2 >, mlx::steel::ChannelHelper< 3 >, mlx::steel::ChannelHelper< 4 >
  • exec() : mlx::core::JitCompiler, pocketfft::detail::cfftp< T0 >, pocketfft::detail::fftblue< T0 >, pocketfft::detail::pocketfft_c< T0 >, pocketfft::detail::pocketfft_r< T0 >, pocketfft::detail::rfftp< T0 >, pocketfft::detail::T_dcst23< T0 >, pocketfft::detail::T_dcst4< T0 >, pocketfft::detail::T_dct1< T0 >, pocketfft::detail::T_dst1< T0 >
    • diff --git a/docs/build/html/functions_eval.html b/docs/build/html/functions_eval.html index 3e35901fe..5deea8c69 100644 --- a/docs/build/html/functions_eval.html +++ b/docs/build/html/functions_eval.html @@ -150,7 +150,6 @@ $(function(){initNavTree('functions_eval.html',''); initResizable(true); });

    - s -

    diff --git a/docs/build/html/functions_f.html b/docs/build/html/functions_f.html index 1d6c872fd..6434a5445 100644 --- a/docs/build/html/functions_f.html +++ b/docs/build/html/functions_f.html @@ -110,7 +110,7 @@ $(function(){initNavTree('functions_f.html',''); initResizable(true); });
  • f_wgt_jump_h : mlx::steel::Conv2DGeneralJumpParams
  • f_wgt_jump_w : mlx::steel::Conv2DGeneralJumpParams
  • fdc : mlx::steel::GEMMAddMMParams
    • -
  • Fence() : mlx::core::Fence, mlx::core::metal::Fence
    • +
  • Fence() : mlx::core::Fence, mlx::core::metal::Fence
  • fence : mlx::core::metal::DeviceStream, mlx::core::metal::Fence
  • fence_mtx : mlx::core::metal::DeviceStream
  • FFT() : mlx::core::FFT
    • diff --git a/docs/build/html/functions_func_a.html b/docs/build/html/functions_func_a.html index d68db5057..a1648d477 100644 --- a/docs/build/html/functions_func_a.html +++ b/docs/build/html/functions_func_a.html @@ -107,14 +107,14 @@ $(function(){initNavTree('functions_func_a.html',''); initResizable(true); });

    - a -

    • Abs() : mlx::core::Abs
    • Add() : mlx::core::Add
      • -
    • add_temporaries() : mlx::core::metal::Device
      • -
    • add_temporary() : mlx::core::metal::Device
      • +
    • add_temporaries() : mlx::core::cpu::CommandEncoder, mlx::core::metal::Device
      • +
    • add_temporary() : mlx::core::cpu::CommandEncoder, mlx::core::metal::Device
    • AddMM() : mlx::core::AddMM
    • advance() : pocketfft::detail::multi_iter< N >, pocketfft::detail::rev_iter, pocketfft::detail::simple_iter
    • AffineQuantize() : mlx::core::fast::AffineQuantize
    • aligned_allocator() : pocketfft::detail::threading::aligned_allocator< T >
      • -
    • all_gather() : mlx::core::distributed::detail::GroupImpl
      • -
    • all_sum() : mlx::core::distributed::detail::GroupImpl
      • +
    • all_gather() : mlx::core::distributed::detail::GroupImpl
      • +
    • all_sum() : mlx::core::distributed::detail::GroupImpl
    • AllGather() : mlx::core::distributed::AllGather
    • allocate() : pocketfft::detail::threading::aligned_allocator< T >
    • Allocator() : mlx::core::allocator::Allocator
      • diff --git a/docs/build/html/functions_func_c.html b/docs/build/html/functions_func_c.html index 8a71c3fee..90e960437 100644 --- a/docs/build/html/functions_func_c.html +++ b/docs/build/html/functions_func_c.html @@ -114,7 +114,7 @@ $(function(){initNavTree('functions_func_c.html',''); initResizable(true); });
    • cmplx() : pocketfft::detail::cmplx< T >
    • cndarr() : pocketfft::detail::cndarr< T >
    • command_buffer_needs_commit() : mlx::core::metal::Device
      • -
    • CommandEncoder() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
      • +
    • CommandEncoder() : mlx::core::CommandEncoder, mlx::core::cpu::CommandEncoder, mlx::core::metal::CommandEncoder
    • commit_command_buffer() : mlx::core::metal::Device
    • Compiled() : mlx::core::Compiled
    • complex128_t() : mlx::core::complex128_t
      • diff --git a/docs/build/html/functions_func_d.html b/docs/build/html/functions_func_d.html index 0d6f126af..8cdbb31fc 100644 --- a/docs/build/html/functions_func_d.html +++ b/docs/build/html/functions_func_d.html @@ -116,9 +116,11 @@ $(function(){initNavTree('functions_func_d.html',''); initResizable(true); });
    • denorm_min() : metal::_numeric_limits_impl< bfloat16_t >
    • Depends() : mlx::core::Depends
    • detach() : mlx::core::array
      • +
    • detach_event() : mlx::core::array
    • Device() : mlx::core::Device, mlx::core::metal::Device
    • device() : mlx::core::Primitive
    • DeviceStream() : mlx::core::metal::DeviceStream
      • +
    • dispatch() : mlx::core::cpu::CommandEncoder
    • dispatch_threadgroups() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
    • dispatch_threads() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
    • DistPrimitive() : mlx::core::distributed::DistPrimitive
      • diff --git a/docs/build/html/functions_func_e.html b/docs/build/html/functions_func_e.html index 76e755ce3..92e675b39 100644 --- a/docs/build/html/functions_func_e.html +++ b/docs/build/html/functions_func_e.html @@ -119,7 +119,7 @@ $(function(){initNavTree('functions_func_e.html',''); initResizable(true); });
    • eval() : mlx::core::array
    • eval_cpu() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Recv, mlx::core::distributed::Send, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::AffineQuantize, mlx::core::fast::CustomKernel, mlx::core::fast::LayerNorm, mlx::core::fast::LayerNormVJP, mlx::core::fast::RMSNorm, mlx::core::fast::RMSNormVJP, mlx::core::fast::RoPE, mlx::core::fast::ScaledDotProductAttention, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::LUF, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QRF, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::UnaryPrimitive, mlx::core::Unflatten, mlx::core::View
    • eval_gpu() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Recv, mlx::core::distributed::Send, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::AffineQuantize, mlx::core::fast::CustomKernel, mlx::core::fast::LayerNorm, mlx::core::fast::LayerNormVJP, mlx::core::fast::RMSNorm, mlx::core::fast::RMSNormVJP, mlx::core::fast::RoPE, mlx::core::fast::ScaledDotProductAttention, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::LUF, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QRF, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::UnaryPrimitive, mlx::core::Unflatten, mlx::core::View
      • -
    • Event() : mlx::core::Event
      • +
    • Event() : mlx::core::Event
    • event() : mlx::core::array
    • exec() : mlx::core::JitCompiler, pocketfft::detail::cfftp< T0 >, pocketfft::detail::fftblue< T0 >, pocketfft::detail::pocketfft_c< T0 >, pocketfft::detail::pocketfft_r< T0 >, pocketfft::detail::rfftp< T0 >, pocketfft::detail::T_dcst23< T0 >, pocketfft::detail::T_dcst4< T0 >, pocketfft::detail::T_dct1< T0 >, pocketfft::detail::T_dst1< T0 >
    • exec_r() : pocketfft::detail::fftblue< T0 >
      • diff --git a/docs/build/html/functions_func_f.html b/docs/build/html/functions_func_f.html index fa6d14243..3b0b7c3bd 100644 --- a/docs/build/html/functions_func_f.html +++ b/docs/build/html/functions_func_f.html @@ -105,7 +105,7 @@ $(function(){initNavTree('functions_func_f.html',''); initResizable(true); });
      Here is a list of all functions with links to the classes they belong to:

      - f -

        -
      • Fence() : mlx::core::Fence, mlx::core::metal::Fence
        • +
      • Fence() : mlx::core::Fence, mlx::core::metal::Fence
      • FFT() : mlx::core::FFT
      • fftblue() : pocketfft::detail::fftblue< T0 >
      • FileWriter() : mlx::core::io::FileWriter
        • diff --git a/docs/build/html/functions_func_l.html b/docs/build/html/functions_func_l.html index 8bc70565e..ae2f98274 100644 --- a/docs/build/html/functions_func_l.html +++ b/docs/build/html/functions_func_l.html @@ -119,9 +119,9 @@ $(function(){initNavTree('functions_func_l.html',''); initResizable(true); });
      • Load() : mlx::core::Load
      • load() : mlx::steel::BaseMMAFrag< T, 8, 8 >, mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >, ReadWriter< in_T, out_T, step, four_step_real >
      • load_padded() : ReadWriter< in_T, out_T, step, four_step_real >
        • -
      • load_safe() : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, mlx::steel::BaseMMAFrag< T, 8, 8 >, mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >, QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
        • +
      • load_safe() : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, mlx::steel::BaseMMAFrag< T, 8, 8 >, mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >, QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
      • load_strided() : ReadWriter< in_T, out_T, step, four_step_real >
        • -
      • load_unsafe() : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, mlx::steel::Conv2DInputBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderLargeFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoader< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
        • +
      • load_unsafe() : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, mlx::steel::Conv2DInputBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderLargeFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoader< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
      • location() : LoopedElemToLoc< DIM, OffsetT, General >, LoopedElemToLoc< 1, OffsetT, false >, LoopedElemToLoc< 1, OffsetT, true >
      • Log() : mlx::core::Log
      • Log1p() : mlx::core::Log1p
        • diff --git a/docs/build/html/functions_func_m.html b/docs/build/html/functions_func_m.html index a2ff4946c..3430de5cb 100644 --- a/docs/build/html/functions_func_m.html +++ b/docs/build/html/functions_func_m.html @@ -118,7 +118,6 @@ $(function(){initNavTree('functions_func_m.html',''); initResizable(true); });
      • Minimum() : mlx::core::Minimum
      • mma() : mlx::steel::BaseMMAFrag< T, 8, 8 >, mlx::steel::BlockMMA< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, lda_tgp, ldb_tgp, AccumType, Epilogue >
      • MMATile() : mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >
        • -
      • move_shared_buffer() : mlx::core::array
      • mtl_device() : mlx::core::metal::Device
      • mtl_residency_set() : mlx::core::metal::ResidencySet
      • multi_iter() : pocketfft::detail::multi_iter< N >
        • diff --git a/docs/build/html/functions_func_o.html b/docs/build/html/functions_func_o.html index b9c97832f..e8a14cb13 100644 --- a/docs/build/html/functions_func_o.html +++ b/docs/build/html/functions_func_o.html @@ -123,7 +123,7 @@ $(function(){initNavTree('functions_func_o.html',''); initResizable(true); });
      • operator+=() : pocketfft::detail::cmplx< T >
      • operator-() : pocketfft::detail::cmplx< T >
      • operator-=() : pocketfft::detail::cmplx< T >
        • -
      • operator=() : mlx::core::_MLX_BFloat16, mlx::core::_MLX_Float16, mlx::core::allocator::Allocator, mlx::core::array::Data, mlx::core::array, mlx::core::CommandEncoder, mlx::core::FunctionExporter, mlx::core::io::FileWriter, mlx::core::metal::CommandEncoder, mlx::core::metal::Device, mlx::core::metal::ResidencySet, mlx::core::Primitive, mlx::core::scheduler::Scheduler, mlx::core::UnaryPrimitive
        • +
      • operator=() : mlx::core::_MLX_BFloat16, mlx::core::_MLX_Float16, mlx::core::allocator::Allocator, mlx::core::array::Data, mlx::core::array, mlx::core::CommandEncoder, mlx::core::cpu::CommandEncoder, mlx::core::FunctionExporter, mlx::core::io::FileWriter, mlx::core::metal::CommandEncoder, mlx::core::metal::Device, mlx::core::metal::ResidencySet, mlx::core::Primitive, mlx::core::scheduler::Scheduler, mlx::core::UnaryPrimitive
      • operator[]() : mlx::core::simd::Simd< T, N >, mlx::core::simd::Simd< float16_t, N >, mlx::core::simd::Simd< T, 1 >, pocketfft::detail::arr< T >, pocketfft::detail::cndarr< T >, pocketfft::detail::ndarr< T >, pocketfft::detail::sincos_2pibyn< T >
      • out_of_bounds() : ReadWriter< in_T, out_T, step, four_step_real >
      • output_shape() : mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::ExpandDims, mlx::core::Flatten, mlx::core::Reshape, mlx::core::Squeeze, mlx::core::Unflatten
        • diff --git a/docs/build/html/functions_func_r.html b/docs/build/html/functions_func_r.html index feb7ae31a..d464963e1 100644 --- a/docs/build/html/functions_func_r.html +++ b/docs/build/html/functions_func_r.html @@ -107,18 +107,17 @@ $(function(){initNavTree('functions_func_r.html',''); initResizable(true); });

        - r -

        diff --git a/docs/build/html/functions_func_s.html b/docs/build/html/functions_func_s.html index 013164287..6dbce8da9 100644 --- a/docs/build/html/functions_func_s.html +++ b/docs/build/html/functions_func_s.html @@ -106,8 +106,7 @@ $(function(){initNavTree('functions_func_s.html',''); initResizable(true); });

        - s -

        • sanity_check() : pocketfft::detail::util
          • -
        • ScalarVector() : mlx::core::ScalarVector< Op >
          • -
        • ScaledDotProductAttention() : mlx::core::fast::ScaledDotProductAttention
          • +
        • ScaledDotProductAttention() : mlx::core::fast::ScaledDotProductAttention
        • Scan() : mlx::core::Scan
        • Scatter() : mlx::core::Scatter
        • ScatterAxis() : mlx::core::ScatterAxis
          • @@ -116,7 +115,7 @@ $(function(){initNavTree('functions_func_s.html',''); initResizable(true); });
        • seek() : mlx::core::ContiguousIterator, mlx::core::io::FileWriter, mlx::core::io::ParallelFileReader, mlx::core::io::Reader, mlx::core::io::Writer
        • Select() : mlx::core::Select
        • Send() : mlx::core::distributed::Send
          • -
        • send() : mlx::core::distributed::detail::GroupImpl
          • +
        • send() : mlx::core::distributed::detail::GroupImpl
        • Set() : pocketfft::detail::cmplx< T >
        • set_buffer() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
        • set_bytes() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
          • @@ -124,10 +123,10 @@ $(function(){initNavTree('functions_func_s.html',''); initResizable(true); });
        • set_compute_pipeline_state() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
        • set_data() : mlx::core::array
        • set_default_stream() : mlx::core::scheduler::Scheduler
          • -
        • set_input_array() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
          • +
        • set_input_array() : mlx::core::CommandEncoder, mlx::core::cpu::CommandEncoder, mlx::core::metal::CommandEncoder
        • set_memory_limit() : mlx::core::metal::MetalAllocator
        • set_name() : mlx::core::NodeNamer
          • -
        • set_output_array() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
          • +
        • set_output_array() : mlx::core::CommandEncoder, mlx::core::cpu::CommandEncoder, mlx::core::metal::CommandEncoder
        • set_residency_set() : mlx::core::metal::Device
        • set_siblings() : mlx::core::array
        • set_status() : mlx::core::array
          • @@ -174,7 +173,7 @@ $(function(){initNavTree('functions_func_s.html',''); initResizable(true); });
        • Stream() : mlx::core::Stream
        • stream() : mlx::core::Event, mlx::core::Primitive
        • StreamContext() : mlx::core::StreamContext
          • -
        • StreamThread() : mlx::core::scheduler::StreamThread
          • +
        • StreamThread() : mlx::core::scheduler::StreamThread
        • stride() : pocketfft::detail::arr_info
        • stride_in() : pocketfft::detail::multi_iter< N >
        • stride_out() : pocketfft::detail::multi_iter< N >
          • diff --git a/docs/build/html/functions_func_t.html b/docs/build/html/functions_func_t.html index dcac85821..b0ecebbee 100644 --- a/docs/build/html/functions_func_t.html +++ b/docs/build/html/functions_func_t.html @@ -112,6 +112,7 @@ $(function(){initNavTree('functions_func_t.html',''); initResizable(true); });
        • Tan() : mlx::core::Tan
        • Tanh() : mlx::core::Tanh
        • tell() : mlx::core::io::FileWriter, mlx::core::io::ParallelFileReader, mlx::core::io::Reader, mlx::core::io::Writer
          • +
        • temporaries() : mlx::core::cpu::CommandEncoder
        • thread_count() : pocketfft::detail::util
        • thread_fn() : mlx::core::scheduler::StreamThread
        • thread_pool() : pocketfft::detail::threading::thread_pool
          • diff --git a/docs/build/html/functions_func_u.html b/docs/build/html/functions_func_u.html index a15fcdc75..76f13dee7 100644 --- a/docs/build/html/functions_func_u.html +++ b/docs/build/html/functions_func_u.html @@ -107,9 +107,9 @@ $(function(){initNavTree('functions_func_u.html',''); initResizable(true); });

          - u -

          diff --git a/docs/build/html/functions_func_v.html b/docs/build/html/functions_func_v.html index 2a4f355d8..fb891150e 100644 --- a/docs/build/html/functions_func_v.html +++ b/docs/build/html/functions_func_v.html @@ -108,8 +108,6 @@ $(function(){initNavTree('functions_func_v.html',''); initResizable(true); });
        • val() : mlx::core::Dtype
        • valid() : mlx::core::Event
        • value() : mlx::core::Event
          • -
        • VectorScalar() : mlx::core::VectorScalar< Op >
          • -
        • VectorVector() : mlx::core::VectorVector< Op >
        • View() : mlx::core::View
        • vjp() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::Custom, mlx::core::fast::LayerNorm, mlx::core::fast::RMSNorm, mlx::core::fast::RoPE, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten
        • vmap() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Send, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::Custom, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, mlx::core::View
          • diff --git a/docs/build/html/functions_func_w.html b/docs/build/html/functions_func_w.html index c368b830b..c088fb47d 100644 --- a/docs/build/html/functions_func_w.html +++ b/docs/build/html/functions_func_w.html @@ -105,10 +105,9 @@ $(function(){initNavTree('functions_func_w.html',''); initResizable(true); });
          Here is a list of all functions with links to the classes they belong to:

          - w -

            -
          • wait() : mlx::core::array, mlx::core::Event, mlx::core::Fence, pocketfft::detail::threading::latch
            • +
          • wait() : mlx::core::array, mlx::core::Event, mlx::core::Fence, pocketfft::detail::threading::latch
          • wait_for_fence() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
          • wait_for_one() : mlx::core::scheduler::Scheduler
            • -
          • wait_gpu() : mlx::core::Fence
          • write() : mlx::core::io::FileWriter, mlx::core::io::Writer, ReadWriter< in_T, out_T, step, four_step_real >
          • write_padded() : ReadWriter< in_T, out_T, step, four_step_real >
          • write_strided() : ReadWriter< in_T, out_T, step, four_step_real >
            • diff --git a/docs/build/html/functions_h.html b/docs/build/html/functions_h.html index 7d4bd420a..307462d2e 100644 --- a/docs/build/html/functions_h.html +++ b/docs/build/html/functions_h.html @@ -107,10 +107,10 @@ $(function(){initNavTree('functions_h.html',''); initResizable(true); });

            - h -

            diff --git a/docs/build/html/functions_k.html b/docs/build/html/functions_k.html index 414022f80..23dd9d2c6 100644 --- a/docs/build/html/functions_k.html +++ b/docs/build/html/functions_k.html @@ -120,6 +120,7 @@ $(function(){initNavTree('functions_k.html',''); initResizable(true); });
          • kFragSize : mlx::steel::BlockMMA< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, lda_tgp, ldb_tgp, AccumType, Epilogue >
          • Kind : mlx::core::Dtype
          • kL : mlx::steel::AttnParams
            • +
          • kL_rem : mlx::steel::AttnParams
          • kNumFrags : mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >
          • kRows : mlx::steel::CShape< R, C >, mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >
          • kRowsPerThread : mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >
            • diff --git a/docs/build/html/functions_l.html b/docs/build/html/functions_l.html index 453a84e05..a871ceb7a 100644 --- a/docs/build/html/functions_l.html +++ b/docs/build/html/functions_l.html @@ -125,9 +125,9 @@ $(function(){initNavTree('functions_l.html',''); initResizable(true); });
          • Load() : mlx::core::Load
          • load() : mlx::steel::BaseMMAFrag< T, 8, 8 >, mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >, ReadWriter< in_T, out_T, step, four_step_real >
          • load_padded() : ReadWriter< in_T, out_T, step, four_step_real >
            • -
          • load_safe() : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, mlx::steel::BaseMMAFrag< T, 8, 8 >, mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >, QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
            • +
          • load_safe() : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, mlx::steel::BaseMMAFrag< T, 8, 8 >, mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >, QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
          • load_strided() : ReadWriter< in_T, out_T, step, four_step_real >
            • -
          • load_unsafe() : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, mlx::steel::Conv2DInputBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderLargeFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoader< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
            • +
          • load_unsafe() : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, mlx::steel::Conv2DInputBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderLargeFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoader< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
          • loader_a_t : mlx::steel::GEMMKernel< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, MN_aligned, K_aligned, AccumType, Epilogue >
          • loader_b_t : mlx::steel::GEMMKernel< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, MN_aligned, K_aligned, AccumType, Epilogue >
          • loc : mlx::core::ContiguousIterator
            • diff --git a/docs/build/html/functions_m.html b/docs/build/html/functions_m.html index 1d526fa62..c2d66df8e 100644 --- a/docs/build/html/functions_m.html +++ b/docs/build/html/functions_m.html @@ -106,6 +106,7 @@ $(function(){initNavTree('functions_m.html',''); initResizable(true); });

            - m -

            diff --git a/docs/build/html/functions_s.html b/docs/build/html/functions_s.html index f35244a6f..23017a128 100644 --- a/docs/build/html/functions_s.html +++ b/docs/build/html/functions_s.html @@ -107,20 +107,18 @@ $(function(){initNavTree('functions_s.html',''); initResizable(true); });

            - s -

            • sanity_check() : pocketfft::detail::util
            • scalar_t : mlx::core::simd::Simd< T, N >, mlx::core::simd::Simd< float16_t, N >, mlx::core::simd::Simd< T, 1 >
              • -
            • ScalarVector() : mlx::core::ScalarVector< Op >
            • scale : mlx::steel::AttnParams, ScaleOp< OutT, InT >, TransformScale< T >
              • -
            • ScaledDotProductAttention() : mlx::core::fast::ScaledDotProductAttention
              • +
            • ScaledDotProductAttention() : mlx::core::fast::ScaledDotProductAttention
            • scales : QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
            • Scan() : mlx::core::Scan
            • Scatter() : mlx::core::Scatter
            • ScatterAxis() : mlx::core::ScatterAxis
              • -
            • scheduled : mlx::core::array
            • Scheduler() : mlx::core::scheduler::Scheduler
            • seed() : mlx::core::random::KeySequence
            • seek() : mlx::core::ContiguousIterator, mlx::core::io::FileWriter, mlx::core::io::ParallelFileReader, mlx::core::io::Reader, mlx::core::io::Writer
            • Select() : mlx::core::Select
            • Send() : mlx::core::distributed::Send
              • -
            • send() : mlx::core::distributed::detail::GroupImpl
              • +
            • send() : mlx::core::distributed::detail::GroupImpl
            • Set() : pocketfft::detail::cmplx< T >
            • set_buffer() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
            • set_bytes() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
              • @@ -128,10 +126,10 @@ $(function(){initNavTree('functions_s.html',''); initResizable(true); });
            • set_compute_pipeline_state() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
            • set_data() : mlx::core::array
            • set_default_stream() : mlx::core::scheduler::Scheduler
              • -
            • set_input_array() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
              • +
            • set_input_array() : mlx::core::CommandEncoder, mlx::core::cpu::CommandEncoder, mlx::core::metal::CommandEncoder
            • set_memory_limit() : mlx::core::metal::MetalAllocator
            • set_name() : mlx::core::NodeNamer
              • -
            • set_output_array() : mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
              • +
            • set_output_array() : mlx::core::CommandEncoder, mlx::core::cpu::CommandEncoder, mlx::core::metal::CommandEncoder
            • set_residency_set() : mlx::core::metal::Device
            • set_siblings() : mlx::core::array
            • set_status() : mlx::core::array
              • @@ -189,9 +187,9 @@ $(function(){initNavTree('functions_s.html',''); initResizable(true); });
            • store_safe() : mlx::steel::BaseMMAFrag< T, 8, 8 >, mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >
            • str : MLXConvParams< NDIM >, pocketfft::detail::arr_info
            • Stream() : mlx::core::Stream
              • -
            • stream() : mlx::core::Event, mlx::core::Primitive, mlx::core::scheduler::StreamThread
              • +
            • stream() : mlx::core::Event, mlx::core::Primitive
            • StreamContext() : mlx::core::StreamContext
              • -
            • StreamThread() : mlx::core::scheduler::StreamThread
              • +
            • StreamThread() : mlx::core::scheduler::StreamThread
            • stride() : pocketfft::detail::arr_info
            • stride_in() : pocketfft::detail::multi_iter< N >
            • stride_out() : pocketfft::detail::multi_iter< N >
              • diff --git a/docs/build/html/functions_t.html b/docs/build/html/functions_t.html index 9c6989b26..029467699 100644 --- a/docs/build/html/functions_t.html +++ b/docs/build/html/functions_t.html @@ -113,9 +113,9 @@ $(function(){initNavTree('functions_t.html',''); initResizable(true); });
            • Tanh() : mlx::core::Tanh
            • TCOLS : mlx::steel::Conv2DInputBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderLargeFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoader< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >
            • tell() : mlx::core::io::FileWriter, mlx::core::io::ParallelFileReader, mlx::core::io::Reader, mlx::core::io::Writer
              • -
            • temporaries : mlx::core::metal::DeviceStream
              • +
            • temporaries() : mlx::core::cpu::CommandEncoder, mlx::core::metal::DeviceStream
            • ten : mlx::core::Log
              • -
            • tgp_mem_size : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, mlx::steel::GEMMKernel< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, MN_aligned, K_aligned, AccumType, Epilogue >
              • +
            • tgp_mem_size : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, mlx::steel::GEMMKernel< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, MN_aligned, K_aligned, AccumType, Epilogue >
            • tgp_mem_size_a : mlx::steel::GEMMKernel< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, MN_aligned, K_aligned, AccumType, Epilogue >
            • tgp_mem_size_b : mlx::steel::GEMMKernel< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, MN_aligned, K_aligned, AccumType, Epilogue >
            • tgp_padding_a : mlx::steel::GEMMKernel< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, MN_aligned, K_aligned, AccumType, Epilogue >
              • @@ -129,8 +129,8 @@ $(function(){initNavTree('functions_t.html',''); initResizable(true); });
            • thread_sort_t : BlockMergeSort< ValT, IdxT, ARG_SORT, BLOCK_THREADS, N_PER_THREAD, CompareOp >
            • ThreadPool() : ThreadPool
            • threads_per_tg : ReadWriter< in_T, out_T, step, four_step_real >
              • -
            • threadsM : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >
              • -
            • threadsN : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >
              • +
            • threadsM : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >
              • +
            • threadsN : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >
            • tile_stride : mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
            • tile_stride_a : mlx::steel::BlockMMA< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, lda_tgp, ldb_tgp, AccumType, Epilogue >
            • tile_stride_b : mlx::steel::BlockMMA< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, lda_tgp, ldb_tgp, AccumType, Epilogue >
              • diff --git a/docs/build/html/functions_u.html b/docs/build/html/functions_u.html index c7a888212..20a85d16d 100644 --- a/docs/build/html/functions_u.html +++ b/docs/build/html/functions_u.html @@ -107,10 +107,10 @@ $(function(){initNavTree('functions_u.html',''); initResizable(true); });

              - u -

              diff --git a/docs/build/html/functions_v.html b/docs/build/html/functions_v.html index e6a5a12ac..57ed4a95d 100644 --- a/docs/build/html/functions_v.html +++ b/docs/build/html/functions_v.html @@ -115,8 +115,6 @@ $(function(){initNavTree('functions_v.html',''); initResizable(true); });
            • value() : mlx::core::Event, mlx::core::simd::Simd< T, N >, mlx::core::simd::Simd< float16_t, N >, mlx::core::simd::Simd< T, 1 >, mlx::steel::integral_constant< T, v >
            • value_type : mlx::core::array::ArrayIterator, mlx::steel::integral_constant< T, v >, pocketfft::detail::threading::aligned_allocator< T >
            • vec_size : mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, mlx::steel::ChannelHelper< n_channels_ >, mlx::steel::ChannelHelper< 1 >, mlx::steel::ChannelHelper< 2 >, mlx::steel::ChannelHelper< 3 >, mlx::steel::ChannelHelper< 4 >, mlx::steel::Conv2DInputBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderLargeFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoader< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >
              • -
            • VectorScalar() : mlx::core::VectorScalar< Op >
              • -
            • VectorVector() : mlx::core::VectorVector< Op >
            • View() : mlx::core::View
            • vjp() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::Custom, mlx::core::fast::LayerNorm, mlx::core::fast::RMSNorm, mlx::core::fast::RoPE, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten
            • vmap() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Send, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::Custom, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, mlx::core::View
              • diff --git a/docs/build/html/functions_vars_b.html b/docs/build/html/functions_vars_b.html index 2228eb02d..af0357924 100644 --- a/docs/build/html/functions_vars_b.html +++ b/docs/build/html/functions_vars_b.html @@ -124,8 +124,8 @@ $(function(){initNavTree('functions_vars_b.html',''); initResizable(true); });
            • biases : QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
            • bits_ : _MLX_BFloat16, mlx::core::_MLX_BFloat16, mlx::core::_MLX_Float16
            • bj : mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, mlx::steel::Conv2DInputBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderLargeFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoader< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
              • -
            • blockM : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >
              • -
            • blockN : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >
              • +
            • blockM : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >
              • +
            • blockN : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >
            • BROWS : mlx::steel::Conv2DInputBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderLargeFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoader< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >
            • Bs_offset : mlx::steel::BlockMMA< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, lda_tgp, ldb_tgp, AccumType, Epilogue >
            • Btile : mlx::steel::BlockMMA< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, lda_tgp, ldb_tgp, AccumType, Epilogue >
              • diff --git a/docs/build/html/functions_vars_h.html b/docs/build/html/functions_vars_h.html index ccd8b9789..65e297a23 100644 --- a/docs/build/html/functions_vars_h.html +++ b/docs/build/html/functions_vars_h.html @@ -106,10 +106,10 @@ $(function(){initNavTree('functions_vars_h.html',''); initResizable(true); });

              - h -

              diff --git a/docs/build/html/functions_vars_k.html b/docs/build/html/functions_vars_k.html index cd10c4f98..2e4859046 100644 --- a/docs/build/html/functions_vars_k.html +++ b/docs/build/html/functions_vars_k.html @@ -118,6 +118,7 @@ $(function(){initNavTree('functions_vars_k.html',''); initResizable(true); });
            • kFragRows : mlx::steel::BaseMMAFrag< T, 8, 8 >, mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >
            • kFragSize : mlx::steel::BlockMMA< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, lda_tgp, ldb_tgp, AccumType, Epilogue >
            • kL : mlx::steel::AttnParams
              • +
            • kL_rem : mlx::steel::AttnParams
            • kNumFrags : mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >
            • kRows : mlx::steel::CShape< R, C >, mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >
            • kRowsPerThread : mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >
              • diff --git a/docs/build/html/functions_vars_m.html b/docs/build/html/functions_vars_m.html index 05e98c931..1a48a20d2 100644 --- a/docs/build/html/functions_vars_m.html +++ b/docs/build/html/functions_vars_m.html @@ -106,6 +106,7 @@ $(function(){initNavTree('functions_vars_m.html',''); initResizable(true); });

              - m -

              diff --git a/docs/build/html/functions_vars_s.html b/docs/build/html/functions_vars_s.html index 4d1660278..2325fbf5e 100644 --- a/docs/build/html/functions_vars_s.html +++ b/docs/build/html/functions_vars_s.html @@ -121,7 +121,6 @@ $(function(){initNavTree('functions_vars_s.html',''); initResizable(true); });
            • start_row : mlx::steel::Conv2DWeightBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >
            • stop : mlx::core::scheduler::StreamThread
            • str : MLXConvParams< NDIM >, pocketfft::detail::arr_info
              • -
            • stream : mlx::core::scheduler::StreamThread
            • strided_device_idx : ReadWriter< in_T, out_T, step, four_step_real >
            • strided_shared_idx : ReadWriter< in_T, out_T, step, four_step_real >
            • strides : Indices< IdxT, NIDX >, mlx::core::fast::CustomKernelShapeInfo, mlx::core::ReductionPlan
              • diff --git a/docs/build/html/functions_vars_t.html b/docs/build/html/functions_vars_t.html index 4f743cfd1..4bd70b968 100644 --- a/docs/build/html/functions_vars_t.html +++ b/docs/build/html/functions_vars_t.html @@ -107,7 +107,7 @@ $(function(){initNavTree('functions_vars_t.html',''); initResizable(true); });

              - t -

              • TCOLS : mlx::steel::Conv2DInputBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderLargeFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoader< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >
              • temporaries : mlx::core::metal::DeviceStream
                • -
              • tgp_mem_size : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, mlx::steel::GEMMKernel< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, MN_aligned, K_aligned, AccumType, Epilogue >
                • +
              • tgp_mem_size : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, mlx::steel::GEMMKernel< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, MN_aligned, K_aligned, AccumType, Epilogue >
              • tgp_mem_size_a : mlx::steel::GEMMKernel< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, MN_aligned, K_aligned, AccumType, Epilogue >
              • tgp_mem_size_b : mlx::steel::GEMMKernel< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, MN_aligned, K_aligned, AccumType, Epilogue >
              • tgp_padding_a : mlx::steel::GEMMKernel< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, MN_aligned, K_aligned, AccumType, Epilogue >
                • @@ -116,8 +116,8 @@ $(function(){initNavTree('functions_vars_t.html',''); initResizable(true); });
              • thread : mlx::core::scheduler::StreamThread
              • thread_idx : mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, mlx::steel::Conv2DInputBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderLargeFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoader< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderGeneral< T, BM, BN, BK, tgp_size, tgp_padding >, mlx::steel::Conv2DWeightBlockLoaderSmallChannels< T, BM, BN, BK, tgp_size, n_channels, tgp_padding >, QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
              • threads_per_tg : ReadWriter< in_T, out_T, step, four_step_real >
                • -
              • threadsM : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >
                • -
              • threadsN : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >
                • +
              • threadsM : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >
                • +
              • threadsN : GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >
              • tile_stride : mlx::steel::BlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, alignment, n_reads, TCOLS, TROWS >, mlx::steel::BlockLoaderT< T, BROWS, BCOLS, kDstStrRow, kDstStrCol, reduction_dim, tgp_size, n_reads, TCOLS, TROWS >, QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
              • tile_stride_a : mlx::steel::BlockMMA< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, lda_tgp, ldb_tgp, AccumType, Epilogue >
              • tile_stride_b : mlx::steel::BlockMMA< T, U, BM, BN, BK, WM, WN, transpose_a, transpose_b, lda_tgp, ldb_tgp, AccumType, Epilogue >
                • diff --git a/docs/build/html/functions_w.html b/docs/build/html/functions_w.html index ad37579f8..c2289adc8 100644 --- a/docs/build/html/functions_w.html +++ b/docs/build/html/functions_w.html @@ -105,10 +105,9 @@ $(function(){initNavTree('functions_w.html',''); initResizable(true); });
                Here is a list of all class members with links to the classes they belong to:

                - w -

                +

                - d -

                + +

                - f -

                • float16 : mlx::core
                • float32 : mlx::core
                  • diff --git a/docs/build/html/namespacemlx_1_1core.html b/docs/build/html/namespacemlx_1_1core.html index 2adb6a6b5..07be5fe53 100644 --- a/docs/build/html/namespacemlx_1_1core.html +++ b/docs/build/html/namespacemlx_1_1core.html @@ -117,6 +117,8 @@ $(function(){initNavTree('namespacemlx_1_1core.html',''); initResizable(true); } Namespaces namespace  allocator   +namespace  cpu +  namespace  detail   namespace  distributed @@ -503,8 +505,8 @@ Enumerations Functions BinaryOpType get_binary_op_type (const array &a, const array &b)   -void set_binary_op_output_data (const array &a, const array &b, array &out, BinaryOpType bopt, bool donate_with_move=false) -  +void set_binary_op_output_data (const array &a, const array &b, array &out, BinaryOpType bopt) +  bool is_static_cast (const Primitive &p)   std::string build_lib_name (const std::vector< array > &inputs, const std::vector< array > &outputs, const std::vector< array > &tape, const std::unordered_set< uintptr_t > &constant_ids) @@ -526,14 +528,14 @@ Functions   bool compiled_check_contiguity (const std::vector< array > &inputs, const Shape &shape)   -void compiled_allocate_outputs (const std::vector< array > &inputs, std::vector< array > &outputs, const std::vector< array > &inputs_, const std::unordered_set< uintptr_t > &constant_ids_, bool contiguous, bool move_buffers=false) -  +void compiled_allocate_outputs (const std::vector< array > &inputs, std::vector< array > &outputs, const std::vector< array > &inputs_, const std::unordered_set< uintptr_t > &constant_ids_, bool contiguous) +  +bool set_copy_output_data (const array &in, array &out, CopyType ctype) +  const std::map< int, std::string_view > hadamard_matrices ()   std::pair< int, int > decompose_hadamard (int n)   -void load (array &out, size_t offset, const std::shared_ptr< io::Reader > &reader, bool swap_endianess) -  ReductionPlan get_reduction_plan (const array &x, const std::vector< int > &axes)   std::pair< Shape, Strides > shapes_without_reduction_axes (const array &x, const std::vector< int > &axes) @@ -544,8 +546,8 @@ Functions   TernaryOpType get_ternary_op_type (const array &a, const array &b, const array &c)   -void set_ternary_op_output_data (const array &a, const array &b, const array &c, array &out, TernaryOpType topt, bool donate_with_move=false) -  +void set_ternary_op_output_data (const array &a, const array &b, const array &c, array &out, TernaryOpType topt) +  int64_t elem_to_loc (int elem, const Shape &shape, const Strides &strides)   int64_t elem_to_loc (int elem, const array &a) @@ -567,68 +569,71 @@ Functions   bool is_donatable (const array &in, const array &out)   -void move_or_copy (const array &in, array &out) -  -void move_or_copy (const array &in, array &out, const Strides &strides, array::Flags flags, size_t data_size, size_t offset=0) -  std::pair< bool, Strides > prepare_reshape (const array &in, const array &out)   void shared_buffer_reshape (const array &in, const Strides &out_strides, array &out)   -void arange (const std::vector< array > &inputs, array &out, double start, double step) -  -template<typename T, typename U, typename Op, int D, bool Strided> -void binary_op_dims (const T *a, const T *b, U *out, Op op, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides, int axis) -  -template<typename T, typename U, bool Strided, typename Op> -void binary_op_dispatch_dims (const array &a, const array &b, array &out, Op op, int dim, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides) -  -template<typename T, typename U, typename Op> -void binary_op (const array &a, const array &b, array &out, Op op) -  -template<typename T, typename Op> -void binary_op (const array &a, const array &b, array &out, Op op) -  -template<typename Op> -void binary (const array &a, const array &b, array &out, Op op) -  -void copy (const array &src, array &dst, CopyType ctype) -  -void copy_inplace (const array &src, array &dst, CopyType ctype) -  -void copy_inplace (const array &src, array &dst, const Shape &data_shape, const Strides &i_strides, const Strides &o_strides, int64_t i_offset, int64_t o_offset, CopyType ctype) -  -template<typename T> -void matmul (const array &a, const array &b, array &out, bool a_transposed, bool b_transposed, size_t lda, size_t ldb, float alpha, float beta) -  +template<typename T, typename U, typename Op, int D, bool Strided> +void binary_op_dims (const T *a, const T *b, U *out, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides, int axis) +  +template<typename T, typename U, bool Strided, typename Op> +void binary_op_dispatch_dims (const T *a, const T *b, U *out, int dim, int size, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides) +  +template<typename T, typename U, typename Op> +void binary_op (const array &a, const array &b, array &out, BinaryOpType bopt) +  +template<typename T, typename Op> +void binary_op (const array &a, const array &b, array &out, BinaryOpType bopt) +  +void copy (const array &src, array &dst, CopyType ctype, Stream stream) +  +void copy_inplace (const array &src, array &dst, CopyType ctype, Stream stream) +  +void copy_inplace (const array &src, array &dst, const Shape &data_shape, const Strides &i_strides, const Strides &o_strides, int64_t i_offset, int64_t o_offset, CopyType ctype, Stream stream, const std::optional< array > &dynamic_i_offset=std::nullopt, const std::optional< array > &dynamic_o_offset=std::nullopt) +  +template<typename T> +void matmul (const T *a, const T *b, T *out, bool a_transposed, bool b_transposed, size_t lda, size_t ldb, size_t ldc, float alpha, float beta, size_t batch_size, const Shape &a_shape, const Strides &a_strides, const Shape &b_shape, const Strides &b_strides) +  void shared_buffer_slice (const array &in, const Strides &out_strides, size_t data_offset, size_t data_size, array &out)   template<typename T1, typename T2, typename T3, typename U, typename Op, int D> void ternary_op_dims (const T1 *a, const T2 *b, const T3 *c, U *out, Op op, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &c_strides, const Strides &out_strides, int axis)   -template<typename T1, typename T2, typename T3, typename U, typename Op> -void ternary_op_dispatch_dims (const array &a, const array &b, const array &c, array &out, Op op) -  -template<typename T1, typename T2, typename T3, typename U, typename Op> -void ternary_op (const array &a, const array &b, const array &c, array &out, Op op) -  +template<typename T1, typename T2, typename T3, typename U, typename Op> +void ternary_op_dispatch_dims (const T1 *a_ptr, const T2 *b_ptr, const T3 *c_ptr, U *out_ptr, Op op, size_t size, Shape &shape, std::vector< Strides > &strides) +  +template<typename T1, typename T2, typename T3, typename U, typename Op> +void ternary_op (const array &a, const array &b, const array &c, array &out, Op op, TernaryOpType topt) +  void set_unary_output_data (const array &in, array &out)   -template<typename T, typename U = T, typename Op> -void unary_op (const T *a, U *out, Op op, size_t shape, size_t stride) -  -template<typename T, typename U = T, typename Op> -void unary_op (const array &a, array &out, Op op) -  -template<typename Op> -void unary (const array &a, array &out, Op op) -  -template<typename Op> -void unary_fp (const array &a, array &out, Op op) -  -template<typename Op> -void unary_int (const array &a, array &out, Op op) -  +template<typename T, typename U = T, typename Op> +void unary_op (const T *a, U *out, size_t shape, size_t stride) +  +template<typename T, typename U = T, typename Op> +void unary_op (const array &a, array &out, Op) +  +template<typename Op> +void unary (const array &a, array &out, Op op, Stream stream) +  +template<typename Op> +void unary_real_fp (const array &a, array &out, Op op, Stream stream) +  +template<typename Op> +void unary_fp (const array &a, array &out, Op op, Stream stream) +  +template<typename Op> +void unary_signed (const array &a, array &out, Op op, Stream stream) +  +template<typename Op> +void unary_complex (const array &a, array &out, Op op, Stream stream) +  +template<typename Op> +void unary_complex_to_float (const array &a, array &out, Op op, Stream stream) +  +template<typename Op> +void unary_int (const array &a, array &out, Op op, Stream stream) +  void binary_op_gpu (const std::vector< array > &inputs, std::vector< array > &outputs, const std::string &op, const Stream &s)   void binary_op_gpu (const std::vector< array > &inputs, array &out, const std::string &op, const Stream &s) @@ -649,10 +654,6 @@ Functions   void fill_gpu (const array &val, array &out, const Stream &s)   -void encode_wait (Event e) -  -void encode_signal (Event e) -  MTL::ComputePipelineState * get_arange_kernel (metal::Device &d, const std::string &kernel_name, const array &out)   MTL::ComputePipelineState * get_unary_kernel (metal::Device &d, const std::string &kernel_name, Dtype in_type, Dtype out_type, const std::string op) @@ -748,9 +749,6 @@ Functions template<typename T, typename... Args> void concatenate (std::string &acc, T first, Args... args)   -array unsafe_weak_copy (const array &x) - Get a new array that refers to the same data but has a non-owning pointer to them.
                  -  std::function< std::vector< array >(const std::vector< array > &)> compile (std::function< std::vector< array >(const std::vector< array > &)> fun, bool shapeless=false)  Compile takes a function and returns a compiled function.
                    @@ -2510,6 +2508,8 @@ Functions   Stream to_stream (StreamOrDevice s)   +Stream to_stream (StreamOrDevice s, Device default_) +  PrintFormatter & get_global_formatter ()   void abort_with_exception (const std::exception &error) @@ -3039,37 +3039,6 @@ template<typename... T>
                  -
                  - - -

                  ◆ arange()

                  - -
                  -
                  - - - - - - - - - - - - - - - - - - - - - -
                  void mlx::core::arange (const std::vector< array > & inputs,
                  array & out,
                  double start,
                  double step )
                  -
                  -
                  @@ -3108,41 +3077,8 @@ template<typename... Arrays, typename = enable_for_arrays_t<Arrays...>& - -

                  ◆ binary()

                  - -
                  -
                  -
                  -template<typename Op>
                  - - - - - - - - - - - - - - - - - - - - - -
                  void mlx::core::binary (const array & a,
                  const array & b,
                  array & out,
                  Op op )
                  -
                  - -
                  -
                  - -

                  ◆ binary_op() [1/2]

                  + +

                  ◆ binary_op() [1/2]

                  @@ -3167,15 +3103,15 @@ template<typename T, typename U, typename Op>
                  - Op op ) + BinaryOpType bopt )
                  - -

                  ◆ binary_op() [2/2]

                  + +

                  ◆ binary_op() [2/2]

                  @@ -3200,15 +3136,15 @@ template<typename T, typename Op>
                  - Op op ) + BinaryOpType bopt )
                  - -

                  ◆ binary_op_dims()

                  + +

                  ◆ binary_op_dims()

                  @@ -3230,11 +3166,6 @@ template<typename T, typename U, typename Op, int D, bool Strided>
                  U * out, - - - - Op op, - @@ -3265,8 +3196,8 @@ template<typename T, typename U, typename Op, int D, bool Strided>
                  - -

                  ◆ binary_op_dispatch_dims()

                  + +

                  ◆ binary_op_dispatch_dims()

                  @@ -3276,28 +3207,28 @@ template<typename T, typename U, bool Strided, typename Op>
                  void mlx::core::binary_op_dispatch_dims ( - const array & a, + const T * a, - const array & b, + const T * b, - array & out, - - - - - Op op, + U * out, int dim, + + + + int size, + @@ -3744,8 +3675,8 @@ template<typename F>
                  - -

                  ◆ compiled_allocate_outputs()

                  + +

                  ◆ compiled_allocate_outputs()

                  @@ -3773,12 +3704,7 @@ template<typename F>
                  - bool contiguous, - - - - - bool move_buffers = false ) + bool contiguous )
                  @@ -3888,8 +3814,8 @@ template<typename T, typename... Args>
                  - -

                  ◆ copy()

                  + +

                  ◆ copy()

                  @@ -3907,7 +3833,12 @@ template<typename T, typename... Args>
                  - CopyType ctype ) + CopyType ctype, + + + + + Stream stream )
                  @@ -4109,8 +4040,8 @@ template<typename T, typename... Args>
                  - -

                  ◆ copy_inplace() [1/2]

                  + +

                  ◆ copy_inplace() [1/2]

                  @@ -4153,15 +4084,30 @@ template<typename T, typename... Args>
                  - CopyType ctype ) + CopyType ctype, + + + + + Stream stream, + + + + + const std::optional< array > & dynamic_i_offset = std::nullopt, + + + + + const std::optional< array > & dynamic_o_offset = std::nullopt )
                  - -

                  ◆ copy_inplace() [2/2]

                  + +

                  ◆ copy_inplace() [2/2]

                  @@ -4179,7 +4125,12 @@ template<typename T, typename... Args>
                  - CopyType ctype ) + CopyType ctype, + + + + + Stream stream )
                  @@ -4526,40 +4477,6 @@ template<typename T, typename... Args>

                  Globally enable compilation.

                  This will override the environment variable MLX_DISABLE_COMPILE.

                  - - - -

                  ◆ encode_signal()

                  - -
                  -
                  - - - - - - - -
                  void mlx::core::encode_signal (Event e)
                  -
                  - -
                  -
                  - -

                  ◆ encode_wait()

                  - -
                  -
                  - - - - - - - -
                  void mlx::core::encode_wait (Event e)
                  -
                  -
                  @@ -6616,41 +6533,10 @@ template<typename... Args>
                  -
                  - - -

                  ◆ load() [1/3]

                  - -
                  -
                  - - - - - - - - - - - - - - - - - - - - - -
                  void mlx::core::load (array & out,
                  size_t offset,
                  const std::shared_ptr< io::Reader > & reader,
                  bool swap_endianess )
                  -
                  -
                  -

                  ◆ load() [2/3]

                  +

                  ◆ load() [1/2]

                  @@ -6673,7 +6559,7 @@ template<typename... Args>
                  -

                  ◆ load() [3/3]

                  +

                  ◆ load() [2/2]

                  @@ -6812,8 +6698,8 @@ template<typename... Args>
                  - -

                  ◆ matmul()

                  + +

                  ◆ matmul()

                  @@ -6823,17 +6709,17 @@ template<typename T>
                  void mlx::core::matmul ( - const array & a, + const T * a, - const array & b, + const T * b, - array & out, + T * out, @@ -6855,6 +6741,11 @@ template<typename T>
                  size_t ldb, + + + + size_t ldc, + @@ -6863,69 +6754,32 @@ template<typename T> - float beta ) - - -
                  - -
                  - - -

                  ◆ move_or_copy() [1/2]

                  - -
                  -
                  - - - - - + - - -
                  void mlx::core::move_or_copy (const array & in, float beta,
                  array & out )
                  -
                  - -
                  -
                  - -

                  ◆ move_or_copy() [2/2]

                  - -
                  -
                  - - - - - + - + - + - + - - - - - - +
                  void mlx::core::move_or_copy (const array & in, size_t batch_size,
                  array & out, const Shape & a_shape,
                  const Strides & strides, const Strides & a_strides,
                  array::Flags flags, const Shape & b_shape,
                  size_t data_size,
                  size_t offset = 0 )const Strides & b_strides )
                  @@ -18257,8 +18111,8 @@ template<typename T>
                  - -

                  ◆ set_binary_op_output_data()

                  + +

                  ◆ set_binary_op_output_data()

                  @@ -18284,12 +18138,7 @@ template<typename T>
                  - BinaryOpType bopt, - - - - - bool donate_with_move = false ) + BinaryOpType bopt ) @@ -18318,6 +18167,40 @@ template<typename T>

                  Set the compiler mode to the given value.

                  + + + +

                  ◆ set_copy_output_data()

                  + +
                  +
                  + + + + + +
                  + + + + + + + + + + + + + + + + +
                  bool mlx::core::set_copy_output_data (const array & in,
                  array & out,
                  CopyType ctype )
                  +                   		+inline
                  +
                  +
                  @@ -18356,8 +18239,8 @@ template<typename T> - -

                  ◆ set_ternary_op_output_data()

                  + +

                  ◆ set_ternary_op_output_data()

                  @@ -18388,12 +18271,7 @@ template<typename T>
                  - TernaryOpType topt, - - - - - bool donate_with_move = false ) + TernaryOpType topt ) @@ -18893,8 +18771,8 @@ template<typename T>
                  - -

                  ◆ ternary_op()

                  + +

                  ◆ ternary_op()

                  @@ -18924,7 +18802,12 @@ template<typename T1, typename T2, typename T3, typename U, typename Op> < - Op op ) + Op op, + + + + + TernaryOpType topt )
                  @@ -18999,8 +18882,8 @@ template<typename T1, typename T2, typename T3, typename U, typename Op, int
                  - -

                  ◆ ternary_op_dispatch_dims()

                  + +

                  ◆ ternary_op_dispatch_dims()

                  @@ -19010,27 +18893,42 @@ template<typename T1, typename T2, typename T3, typename U, typename Op> < void mlx::core::ternary_op_dispatch_dims ( - const array & a, + const T1 * a_ptr, - const array & b, + const T2 * b_ptr, - const array & c, + const T3 * c_ptr, - array & out, + U * out_ptr, - Op op ) + Op op, + + + + + size_t size, + + + + + Shape & shape, + + + + + std::vector< Strides > & strides )
                  @@ -19100,7 +18998,7 @@ template<typename T1, typename T2, typename T3, typename U, typename Op> <
                  -

                  ◆ to_stream()

                  +

                  ◆ to_stream() [1/2]

                  @@ -19114,6 +19012,27 @@ template<typename T1, typename T2, typename T3, typename U, typename Op> <
                  +
                  +
                  + +

                  ◆ to_stream() [2/2]

                  + +
                  +
                  + + + + + + + + + + + +
                  Stream mlx::core::to_stream (StreamOrDevice s,
                  Device default_ )
                  +
                  +
                  @@ -19150,8 +19069,8 @@ template<typename T1, typename T2, typename T3, typename U, typename Op> < - -

                  ◆ unary()

                  + +

                  ◆ unary()

                  @@ -19171,15 +19090,86 @@ template<typename Op>
                  - Op op ) + Op op, + + + + + Stream stream )
                  - -

                  ◆ unary_fp()

                  + +

                  ◆ unary_complex()

                  + +
                  +
                  +
                  +template<typename Op>
                  + + + + + + + + + + + + + + + + + + + + + +
                  void mlx::core::unary_complex (const array & a,
                  array & out,
                  Op op,
                  Stream stream )
                  +
                  + +
                  +
                  + +

                  ◆ unary_complex_to_float()

                  + +
                  +
                  +
                  +template<typename Op>
                  + + + + + + + + + + + + + + + + + + + + + +
                  void mlx::core::unary_complex_to_float (const array & a,
                  array & out,
                  Op op,
                  Stream stream )
                  +
                  + +
                  +
                  + +

                  ◆ unary_fp()

                  @@ -19199,15 +19189,20 @@ template<typename Op>
                  - Op op ) + Op op, + + + + + Stream stream )
                  - -

                  ◆ unary_int()

                  + +

                  ◆ unary_int()

                  @@ -19227,15 +19222,20 @@ template<typename Op>
                  - Op op ) + Op op, + + + + + Stream stream )
                  - -

                  ◆ unary_op() [1/2]

                  + +

                  ◆ unary_op() [1/2]

                  @@ -19255,15 +19255,15 @@ template<typename T, typename U = T, typename Op>
                  - Op op ) + Op  )
                  - -

                  ◆ unary_op() [2/2]

                  + +

                  ◆ unary_op() [2/2]

                  @@ -19280,11 +19280,6 @@ template<typename T, typename U = T, typename Op>
                  U * out, - - - - Op op, - @@ -19362,30 +19357,69 @@ template<typename T, typename U = T, typename Op>
                  - -

                  ◆ unsafe_weak_copy()

                  + +

                  ◆ unary_real_fp()

                  - - - - - -
                  +
                  +template<typename Op>
                  - + - + + + + + + + + + + + + + + +
                  array mlx::core::unsafe_weak_copy void mlx::core::unary_real_fp (const array & x)const array & a,
                  array & out,
                  Op op,
                  Stream stream )
                  -                   		-inline
                  -

                  Get a new array that refers to the same data but has a non-owning pointer to them.

                  +
                  +
                  + +

                  ◆ unary_signed()

                  + +
                  +
                  +
                  +template<typename Op>
                  + + + + + + + + + + + + + + + + + + + + + +
                  void mlx::core::unary_signed (const array & a,
                  array & out,
                  Op op,
                  Stream stream )
                  +
                  diff --git a/docs/build/html/namespacemlx_1_1core.js b/docs/build/html/namespacemlx_1_1core.js index 99561d1d4..d56971d4c 100644 --- a/docs/build/html/namespacemlx_1_1core.js +++ b/docs/build/html/namespacemlx_1_1core.js @@ -1,6 +1,7 @@ var namespacemlx_1_1core = [ [ "allocator", "namespacemlx_1_1core_1_1allocator.html", "namespacemlx_1_1core_1_1allocator" ], + [ "cpu", "namespacemlx_1_1core_1_1cpu.html", "namespacemlx_1_1core_1_1cpu" ], [ "detail", "namespacemlx_1_1core_1_1detail.html", "namespacemlx_1_1core_1_1detail" ], [ "distributed", "namespacemlx_1_1core_1_1distributed.html", "namespacemlx_1_1core_1_1distributed" ], [ "env", "namespacemlx_1_1core_1_1env.html", [ @@ -270,7 +271,6 @@ var namespacemlx_1_1core = [ "any", "group__ops.html#gaf240618fc8b06debf5f56e97e84f18ef", null ], [ "any", "group__ops.html#gab1d56277d468a55227f4dad6bc2fc1ce", null ], [ "any", "group__ops.html#gad37df97f253a963bece124198dbaf9ba", null ], - [ "arange", "namespacemlx_1_1core.html#a369aa886219b83cf219e7a7862ce260b", null ], [ "arange", "group__ops.html#ga7ca088b8090b9f84f2e08345cf3f835a", null ], [ "arange", "group__ops.html#ga4c36b841dc5cba391dad029be5a0ad98", null ], [ "arange", "group__ops.html#ga8d7cf9eb15e2daf1469058907e8abc85", null ], @@ -309,11 +309,10 @@ var namespacemlx_1_1core = [ "atleast_2d", "group__ops.html#ga9950299a80c2562f13448758f856d1f5", null ], [ "atleast_3d", "group__ops.html#ga4afd919601e67782ff964465919956a0", null ], [ "atleast_3d", "group__ops.html#gaffdf742ad79440a60dda40062a8074fe", null ], - [ "binary", "namespacemlx_1_1core.html#ae374861abd45cf019c3e6be2026f3798", null ], - [ "binary_op", "namespacemlx_1_1core.html#a9c1c1fdf9a0840a16a4d10a8f74f761d", null ], - [ "binary_op", "namespacemlx_1_1core.html#a2aca3458c56605a74d07ec39876549bc", null ], - [ "binary_op_dims", "namespacemlx_1_1core.html#a7ca09ebf776fe32db580f9038587ec31", null ], - [ "binary_op_dispatch_dims", "namespacemlx_1_1core.html#a66c9ee5018168b9101de52e0122d9755", null ], + [ "binary_op", "namespacemlx_1_1core.html#ae0c47c0bd95bb8c44339159e04c0f604", null ], + [ "binary_op", "namespacemlx_1_1core.html#a5160ef5819f58cf040c9613ecce548f1", null ], + [ "binary_op_dims", "namespacemlx_1_1core.html#aeac6fa9529eedba76b27de9d098de963", null ], + [ "binary_op_dispatch_dims", "namespacemlx_1_1core.html#ad1229ffbba21bdb81f63482a4651bc5a", null ], [ "binary_op_gpu", "namespacemlx_1_1core.html#a094876ea5a2a2445ab64efc8222da202", null ], [ "binary_op_gpu", "namespacemlx_1_1core.html#ad884f4a36308b5b4f8a5d990d2e086df", null ], [ "binary_op_gpu_inplace", "namespacemlx_1_1core.html#a7e6af6624e322e7ad60a3873a66e18a3", null ], @@ -339,7 +338,7 @@ var namespacemlx_1_1core = [ "compile", "namespacemlx_1_1core.html#ace67713d269595f5f2265e46728a6f9c", null ], [ "compile", "namespacemlx_1_1core.html#a55933c6665de9f81059120d6b0de1c87", null ], [ "compile", "namespacemlx_1_1core.html#abf57076f6d2351ba9f1e0cbe478f8afa", null ], - [ "compiled_allocate_outputs", "namespacemlx_1_1core.html#ab8c3c4fc05745f586de922c8266f4fce", null ], + [ "compiled_allocate_outputs", "namespacemlx_1_1core.html#a8ed5ff0d69f6c7d2e092fe811e40d564", null ], [ "compiled_check_contiguity", "namespacemlx_1_1core.html#a562040f4a03f2c0a5d50eb9c8f14a8be", null ], [ "concatenate", "namespacemlx_1_1core.html#a76a2e310857f60f5ea6f1388d45b964d", null ], [ "concatenate", "namespacemlx_1_1core.html#aaf51544472fa87fa974686eacdd2a4a6", null ], @@ -357,14 +356,14 @@ var namespacemlx_1_1core = [ "conv_transpose2d", "group__ops.html#gaebb59971cb9bc45005dc1d398e4f0a3d", null ], [ "conv_transpose3d", "group__ops.html#ga8db814da631d9cd32a8d6563bf4ac530", null ], [ "copy", "group__ops.html#gae306e93af12f774bd80bad6c231b09d6", null ], - [ "copy", "namespacemlx_1_1core.html#a479648542a2bea151b947b18f0e79dd2", null ], + [ "copy", "namespacemlx_1_1core.html#a017bd8bd743e26f1ff971c8749b55daf", null ], [ "copy_gpu", "namespacemlx_1_1core.html#a6a6f4e46c8fc44fdc74c50ace02bcf38", null ], [ "copy_gpu", "namespacemlx_1_1core.html#addaa46a13ac2deb1d9ce621338320e0e", null ], [ "copy_gpu_inplace", "namespacemlx_1_1core.html#a473fb602368f6c73d9105c9a151c4c82", null ], [ "copy_gpu_inplace", "namespacemlx_1_1core.html#a49fc043a981925b9be79e37fc415d966", null ], [ "copy_gpu_inplace", "namespacemlx_1_1core.html#a58ef0842dd1b8f79159d5fb6777d30a1", null ], - [ "copy_inplace", "namespacemlx_1_1core.html#ae85bafda5ab0b4b2289591260cf07685", null ], - [ "copy_inplace", "namespacemlx_1_1core.html#a98495894a796b2cc6d022e7a03432c64", null ], + [ "copy_inplace", "namespacemlx_1_1core.html#a1e4381d42877a5c6050c20e77d13c990", null ], + [ "copy_inplace", "namespacemlx_1_1core.html#ab30708325761c91e7dde245827e9dd91", null ], [ "cos", "group__ops.html#ga39dfdf72b556012aa35ff27a94116e74", null ], [ "cosh", "group__ops.html#ga2181b71cda88007a3092be4795ff0715", null ], [ "cummax", "group__ops.html#gaee37cac8476e8f8d666bcded5bc59143", null ], @@ -391,8 +390,6 @@ var namespacemlx_1_1core = [ "elem_to_loc", "namespacemlx_1_1core.html#ac9c19514210333346f02a4520641847f", null ], [ "elem_to_loc", "namespacemlx_1_1core.html#a59c0af06c5325c04ad8d69563c1c6b0a", null ], [ "enable_compile", "namespacemlx_1_1core.html#a1983a2466bff3bae4d23cf34bd0946c9", null ], - [ "encode_signal", "namespacemlx_1_1core.html#a6d452306f0f046a7d021bd94f8713a89", null ], - [ "encode_wait", "namespacemlx_1_1core.html#a2874ba55b73057b76c23a7429fdd2d6e", null ], [ "equal", "group__ops.html#ga33638dc3a9972dd02be12d0eb85f9bde", null ], [ "erf", "group__ops.html#ga292a335240fd5d6d625fb7a340ff5eb0", null ], [ "erfinv", "group__ops.html#ga76fb9062c64264e34d2e07013390557c", null ], @@ -499,7 +496,6 @@ var namespacemlx_1_1core = [ "less", "group__ops.html#ga9142b8d717699a8abfa2a7398891ff8a", null ], [ "less_equal", "group__ops.html#ga0d49e0c7011d0573c369c13c8f045a09", null ], [ "linspace", "group__ops.html#ga968bcabed902311dcfbd903b0fb886ec", null ], - [ "load", "namespacemlx_1_1core.html#a954de19249da7c1fa39b89bdc47368aa", null ], [ "load", "namespacemlx_1_1core.html#abada9bfa834d7423959362386720f3db", null ], [ "load", "namespacemlx_1_1core.html#ac71a08bf4c052ae3c77e9e89cbea071d", null ], [ "load_gguf", "namespacemlx_1_1core.html#a2aa12b351ce559deb14cda0a5292c2ce", null ], @@ -519,8 +515,8 @@ var namespacemlx_1_1core = [ "logsumexp", "group__ops.html#ga59be50b4e92f1dc20b53460cefa3910d", null ], [ "make_contiguous_strides", "namespacemlx_1_1core.html#a449ef1148816a37bbc7ffd43d3c586a0", null ], [ "make_string", "namespacemlx_1_1core.html#aed148d95e7b5221f1312473deded0d27", null ], - [ "matmul", "namespacemlx_1_1core.html#aaacf0afe13d77a5c49ce96f1e833eb2d", null ], [ "matmul", "group__ops.html#ga753d59f5a9f5f2362865ee83b4dced2a", null ], + [ "matmul", "namespacemlx_1_1core.html#afd07258882634dcda1e6f18f10dc28d5", null ], [ "max", "group__ops.html#ga7fed87d96cc7741d8267f4eac83f5fe7", null ], [ "max", "group__ops.html#ga1ca7b6b91fe2459a7d83897bf013827f", null ], [ "max", "group__ops.html#ga7b638050e03a93f2896c981bc2850a47", null ], @@ -536,8 +532,6 @@ var namespacemlx_1_1core = [ "min", "group__ops.html#ga36fa315eef677f4143868f552cd26d03", null ], [ "min", "group__ops.html#ga0140b91e9cdfc3fef0da8e332f65a9e8", null ], [ "minimum", "group__ops.html#ga49ba00c090f81f331c91b0c97040bce0", null ], - [ "move_or_copy", "namespacemlx_1_1core.html#a830a47d8a317dffb0c88e5a7afe6aee2", null ], - [ "move_or_copy", "namespacemlx_1_1core.html#a9fcb3711b150cb65c7778a35c51284b2", null ], [ "moveaxis", "group__ops.html#ga24067d10a842db2c9d509ea48135a2c3", null ], [ "multiply", "group__ops.html#gaf57392e641640b5d06e4c99518391c38", null ], [ "nan_to_num", "group__ops.html#gab1467c6a9e675152e768afd6dcfb61de", null ], @@ -1027,11 +1021,12 @@ var namespacemlx_1_1core = [ "scatter_min", "group__ops.html#ga0ca16b7579dfc899f3f7fd40245ba7c5", null ], [ "scatter_prod", "group__ops.html#gaf83c53c453faa9083ba27e4b97539339", null ], [ "scatter_prod", "group__ops.html#ga3708b5bcb61e2c63d213c4ce6ad0ffc0", null ], - [ "set_binary_op_output_data", "namespacemlx_1_1core.html#a6a52856325c2eb031d3983eba2108d59", null ], + [ "set_binary_op_output_data", "namespacemlx_1_1core.html#a9f22a9ed98104aaffb929381055b966d", null ], [ "set_compile_mode", "namespacemlx_1_1core.html#a49445a55f976c4397f25ea18e1e92bef", null ], + [ "set_copy_output_data", "namespacemlx_1_1core.html#a3892b68a2e828270caa1c7accf44f038", null ], [ "set_default_device", "namespacemlx_1_1core.html#a312a2de41367fe52caeaf8c0f596a120", null ], [ "set_default_stream", "namespacemlx_1_1core.html#af35a2b06517d8bb7dbb469692b4f841c", null ], - [ "set_ternary_op_output_data", "namespacemlx_1_1core.html#a6f4528d0d338ea5e1f19d345875c26a2", null ], + [ "set_ternary_op_output_data", "namespacemlx_1_1core.html#ae159e1f9193c12eff9a56dfceb1502ef", null ], [ "set_unary_output_data", "namespacemlx_1_1core.html#a4c6a4241bfcdd7bbf30d0e521b79e5a3", null ], [ "shapes_without_reduction_axes", "namespacemlx_1_1core.html#a0bea91a360a984e72d2815353f97ee25", null ], [ "shared_buffer_reshape", "namespacemlx_1_1core.html#a88d88987bd8bf3ca46bf3b5e8aacce9d", null ], @@ -1091,13 +1086,14 @@ var namespacemlx_1_1core = [ "tanh", "group__ops.html#ga5efb19aa0dfa42d8a3d5e1dfd569cd6d", null ], [ "tensordot", "group__ops.html#gaf5c9735f4690327e1500e04e728fae70", null ], [ "tensordot", "group__ops.html#gad7fe00b566f89d607639c1a497cabbc6", null ], - [ "ternary_op", "namespacemlx_1_1core.html#a9dcc3018702ee31c21c8652bdc2182b1", null ], + [ "ternary_op", "namespacemlx_1_1core.html#a48fbbd43d2165ab7f42bac3f228bbda3", null ], [ "ternary_op_dims", "namespacemlx_1_1core.html#a8096c7a688ac3f09cca69a3a85f7f157", null ], - [ "ternary_op_dispatch_dims", "namespacemlx_1_1core.html#ac1c085e305954247d042f5d8803cd85b", null ], + [ "ternary_op_dispatch_dims", "namespacemlx_1_1core.html#a9abcc6efafd9ab5df1293b1793a734d2", null ], [ "ternary_op_gpu", "namespacemlx_1_1core.html#aa63e62b6d3906e4cac871d498515a1cd", null ], [ "ternary_op_gpu_inplace", "namespacemlx_1_1core.html#a37645c0adccb3eb46844115def1a68d7", null ], [ "tile", "group__ops.html#gab105a57b9a4d84496fe1e4d60e13d361", null ], [ "to_stream", "namespacemlx_1_1core.html#a4734a596e57434492ddfe79f2cb9dbf9", null ], + [ "to_stream", "namespacemlx_1_1core.html#a999be930e8a5b35eb33d934eefd548e8", null ], [ "topk", "group__ops.html#ga35b8436c79ff953f6c809598b646f498", null ], [ "topk", "group__ops.html#ga5487dd887c43e5341f3e68ffe47f0f5a", null ], [ "trace", "group__ops.html#gabf786129c7660ed8d5acb5499bc6fefd", null ], @@ -1112,15 +1108,18 @@ var namespacemlx_1_1core = [ "triu", "group__ops.html#gaa9df5917876eeb0cb28b7fa81f880412", null ], [ "type_to_name", "namespacemlx_1_1core.html#af1fdfdaa5644394362e6baba30701bae", null ], [ "type_to_name", "namespacemlx_1_1core.html#aef60e3a8d9c987c9c338b193673d2164", null ], - [ "unary", "namespacemlx_1_1core.html#a6c8fdd03ef891d7f47804bf02e9a8507", null ], - [ "unary_fp", "namespacemlx_1_1core.html#a76a2cb4634f5fd6970a8c3b3753d7a4a", null ], - [ "unary_int", "namespacemlx_1_1core.html#a078859db0d66ff77f97af6dc9764e8eb", null ], - [ "unary_op", "namespacemlx_1_1core.html#ae20f207ad1ed3badc17cecf08f118b5e", null ], - [ "unary_op", "namespacemlx_1_1core.html#a27f00519f9756896734fd4d47fec0625", null ], + [ "unary", "namespacemlx_1_1core.html#a0f3ff0f676d28840c210ef6277caa546", null ], + [ "unary_complex", "namespacemlx_1_1core.html#a9af588b2e7f4e5249cd8b7722ad829c0", null ], + [ "unary_complex_to_float", "namespacemlx_1_1core.html#a0640d1f5bcd9a4f5cdaea9f197a53515", null ], + [ "unary_fp", "namespacemlx_1_1core.html#a6c1b92aea938457e44f93a7955d22823", null ], + [ "unary_int", "namespacemlx_1_1core.html#a50536365b8bcfec55e7d023ae9a6395c", null ], + [ "unary_op", "namespacemlx_1_1core.html#ab9812785763451ceb86486032d614048", null ], + [ "unary_op", "namespacemlx_1_1core.html#aa6b3dfc27a21d26b3fda96022aa60e32", null ], [ "unary_op_gpu", "namespacemlx_1_1core.html#aba2b4accc059f30d4dca88db9f7a6e13", null ], [ "unary_op_gpu_inplace", "namespacemlx_1_1core.html#a668fde2bd280a88f63a68b68a343d375", null ], + [ "unary_real_fp", "namespacemlx_1_1core.html#a940f998c7469d14f5234f78dcaecd48b", null ], + [ "unary_signed", "namespacemlx_1_1core.html#aed2b5550f8424094ef10bdadfe92ec0f", null ], [ "unflatten", "group__ops.html#ga666bcc2187a144247e8c0c224b016625", null ], - [ "unsafe_weak_copy", "namespacemlx_1_1core.html#a357f4172305d2021bde8cf07d99adb7d", null ], [ "value_and_grad", "namespacemlx_1_1core.html#a5a64dc878b29403d27e50bd7a288cc04", null ], [ "value_and_grad", "namespacemlx_1_1core.html#a7620f1ae298127cb6181db9162f012a7", null ], [ "value_and_grad", "namespacemlx_1_1core.html#a2f69ffc30d66b1fca8f24b65be161a51", null ], diff --git a/docs/build/html/namespacemlx_1_1core_1_1cpu.html b/docs/build/html/namespacemlx_1_1core_1_1cpu.html new file mode 100644 index 000000000..bf6269309 --- /dev/null +++ b/docs/build/html/namespacemlx_1_1core_1_1cpu.html @@ -0,0 +1,198 @@ + + + + + + + +MLX: mlx::core::cpu Namespace Reference + + + + + + + + + + + + + + + + +
                  +
                  + + + + + + + +
                  +
                  MLX +
                  +
                  + +   + + + + +
                  +
                  +
                  + + + + +
                  +
                  + +
                  +
                  +
                  + +
                  + +
                  +
                  + + +
                  +
                  +
                  +
                  +
                  +
                  Loading...
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                  Searching...
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                  No Matches
                  +
                  +
                  +
                  +
                  + +
                  +
                  +Classes | +Functions | +Variables
                  +
                  mlx::core::cpu Namespace Reference
                  +
                  +
                  + + + + +

                  +Classes

                  struct  CommandEncoder
                   
                  + + + + + +

                  +Functions

                  CommandEncoder & get_command_encoder (Stream stream)
                   
                  void eval (array &arr)
                   
                  + + + +

                  +Variables

                  constexpr int DISPATCHES_PER_TASK = 10
                   
                  +

                  Function Documentation

                  + +

                  ◆ eval()

                  + +
                  +
                  + + + + + + + +
                  void mlx::core::cpu::eval (array & arr)
                  +
                  + +
                  +
                  + +

                  ◆ get_command_encoder()

                  + +
                  +
                  + + + + + + + +
                  CommandEncoder & mlx::core::cpu::get_command_encoder (Stream stream)
                  +
                  + +
                  +
                  +

                  Variable Documentation

                  + +

                  ◆ DISPATCHES_PER_TASK

                  + +
                  +
                  + + + + + +
                  + + + + +
                  int mlx::core::cpu::DISPATCHES_PER_TASK = 10
                  +                   		+constexpr
                  +
                  + +
                  +
                  +
                  +
                  + + + + diff --git a/docs/build/html/namespacemlx_1_1core_1_1cpu.js b/docs/build/html/namespacemlx_1_1core_1_1cpu.js new file mode 100644 index 000000000..f27119d6d --- /dev/null +++ b/docs/build/html/namespacemlx_1_1core_1_1cpu.js @@ -0,0 +1,7 @@ +var namespacemlx_1_1core_1_1cpu = +[ + [ "CommandEncoder", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html", "structmlx_1_1core_1_1cpu_1_1_command_encoder" ], + [ "eval", "namespacemlx_1_1core_1_1cpu.html#a3f721e92f604a57ed204a13d1ba9cad5", null ], + [ "get_command_encoder", "namespacemlx_1_1core_1_1cpu.html#a65b1789c4b339a108e64fda5f102d933", null ], + [ "DISPATCHES_PER_TASK", "namespacemlx_1_1core_1_1cpu.html#a1fc5871c94ccee8536c6d43f8f6d5557", null ] +]; \ No newline at end of file diff --git a/docs/build/html/namespacemlx_1_1core_1_1distributed_1_1detail.html b/docs/build/html/namespacemlx_1_1core_1_1distributed_1_1detail.html index 4d2c98373..0f445c641 100644 --- a/docs/build/html/namespacemlx_1_1core_1_1distributed_1_1detail.html +++ b/docs/build/html/namespacemlx_1_1core_1_1distributed_1_1detail.html @@ -117,22 +117,20 @@ Classes - - - - - - - - - - - - + + + + + + + + + +

                  Functions

                  Stream communication_stream ()
                   
                  void all_sum (Group group, const array &input, array &output)
                   
                  void all_gather (Group group, const array &input, array &output)
                   
                  void send (Group group, const array &input, int dst)
                   Send an array to the dst rank.
                   
                  void recv (Group group, array &out, int src)
                   Recv an array from the src rank.
                   
                  void all_sum (Group group, const array &input, array &output, Stream stream)
                   
                  void all_gather (Group group, const array &input, array &output, Stream stream)
                   
                  void send (Group group, const array &input, int dst, Stream stream)
                   Send an array to the dst rank.
                   
                  void recv (Group group, array &out, int src, Stream stream)
                   Recv an array from the src rank.
                   

                  Function Documentation

                  - -

                  ◆ all_gather()

                  + +

                  ◆ all_gather()

                  @@ -150,15 +148,20 @@ Functions - array & output ) + array & output, + + + + + Stream stream )
                  - -

                  ◆ all_sum()

                  + +

                  ◆ all_sum()

                  @@ -176,32 +179,20 @@ Functions - array & output ) + array & output, - -
                  - -
                  -
                  - -

                  ◆ communication_stream()

                  - -
                  -
                  - - - - + +
                  Stream mlx::core::distributed::detail::communication_stream () Stream stream )
                  - -

                  ◆ recv()

                  + +

                  ◆ recv()

                  @@ -219,7 +210,12 @@ Functions - int src ) + int src, + + + + + Stream stream )
                  @@ -228,8 +224,8 @@ Functions
                  - -

                  ◆ send()

                  + +

                  ◆ send()

                  @@ -247,7 +243,12 @@ Functions - int dst ) + int dst, + + + + + Stream stream )
                  diff --git a/docs/build/html/namespacemlx_1_1core_1_1distributed_1_1detail.js b/docs/build/html/namespacemlx_1_1core_1_1distributed_1_1detail.js index 41ba22508..69267e584 100644 --- a/docs/build/html/namespacemlx_1_1core_1_1distributed_1_1detail.js +++ b/docs/build/html/namespacemlx_1_1core_1_1distributed_1_1detail.js @@ -1,9 +1,8 @@ var namespacemlx_1_1core_1_1distributed_1_1detail = [ [ "GroupImpl", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl.html", "classmlx_1_1core_1_1distributed_1_1detail_1_1_group_impl" ], - [ "all_gather", "namespacemlx_1_1core_1_1distributed_1_1detail.html#aeb5a1726358213bc75756506f7b54d04", null ], - [ "all_sum", "namespacemlx_1_1core_1_1distributed_1_1detail.html#aa1d225b25f7b6426c48c5e35860ee960", null ], - [ "communication_stream", "namespacemlx_1_1core_1_1distributed_1_1detail.html#ac3612edf0e0e18c1e4ba0ce7c6e35cd6", null ], - [ "recv", "namespacemlx_1_1core_1_1distributed_1_1detail.html#a003de04deb00ecbb19179b3f557df548", null ], - [ "send", "namespacemlx_1_1core_1_1distributed_1_1detail.html#abf33511660ac71df5fc92f2aad6c6e08", null ] + [ "all_gather", "namespacemlx_1_1core_1_1distributed_1_1detail.html#ab3dc0367476257f13fe15d4db946edf5", null ], + [ "all_sum", "namespacemlx_1_1core_1_1distributed_1_1detail.html#a042be875217168ccfc267fba19a627cb", null ], + [ "recv", "namespacemlx_1_1core_1_1distributed_1_1detail.html#a79bb934225482f2104e8ff270b0530c3", null ], + [ "send", "namespacemlx_1_1core_1_1distributed_1_1detail.html#a23c5cf992d4f2b2ce9dfa51593a4876d", null ] ]; \ No newline at end of file diff --git a/docs/build/html/namespacemlx_1_1core_1_1fast.html b/docs/build/html/namespacemlx_1_1core_1_1fast.html index 19cb6d793..7fefae258 100644 --- a/docs/build/html/namespacemlx_1_1core_1_1fast.html +++ b/docs/build/html/namespacemlx_1_1core_1_1fast.html @@ -150,9 +150,9 @@ Functions   array rope (const array &x, int dims, bool traditional, std::optional< float > base, float scale, const array &offset, const std::optional< array > &freqs=std::nullopt, StreamOrDevice s={})   -array scaled_dot_product_attention (const array &queries, const array &keys, const array &values, const float scale, const std::optional< array > &mask=std::nullopt, const std::optional< int > memory_efficient_threshold=std::nullopt, StreamOrDevice s={}) - Computes: O = softmax(Q @ K.T) @ V.
                  -  +array scaled_dot_product_attention (const array &queries, const array &keys, const array &values, const float scale, const std::variant< std::monostate, std::string, array > &mask={}, const std::optional< int > memory_efficient_threshold=std::nullopt, StreamOrDevice s={}) + Computes: O = softmax(Q @ K.T) @ V.
                  +  std::tuple< array, array, array > affine_quantize (const array &w, int group_size=64, int bits=4, StreamOrDevice s={})   array affine_dequantize (const array &w, const array &scales, const array &biases, int group_size=64, int bits=4, StreamOrDevice s={}) @@ -477,8 +477,8 @@ Functions
                  - -

                  ◆ scaled_dot_product_attention()

                  + +

                  ◆ scaled_dot_product_attention()

                  @@ -506,7 +506,7 @@ Functions - const std::optional< array > & mask = std::nullopt, + const std::variant< std::monostate, std::string, array > & mask = {}, diff --git a/docs/build/html/namespacemlx_1_1core_1_1fast.js b/docs/build/html/namespacemlx_1_1core_1_1fast.js index ee949be0e..e6382673f 100644 --- a/docs/build/html/namespacemlx_1_1core_1_1fast.js +++ b/docs/build/html/namespacemlx_1_1core_1_1fast.js @@ -19,5 +19,5 @@ var namespacemlx_1_1core_1_1fast = [ "rms_norm", "namespacemlx_1_1core_1_1fast.html#a85ec3abc6b9d968c58275f5eef916f01", null ], [ "rope", "namespacemlx_1_1core_1_1fast.html#a1632b78950f0c8c31b24be7d80faeb39", null ], [ "rope", "namespacemlx_1_1core_1_1fast.html#a534ef357eae24892684a6ecd866d3fab", null ], - [ "scaled_dot_product_attention", "namespacemlx_1_1core_1_1fast.html#a3663b50265b0a9c0cca2b5376852e059", null ] + [ "scaled_dot_product_attention", "namespacemlx_1_1core_1_1fast.html#a4207ab2eb838335c0074f6bbb6b4cfc5", null ] ]; \ No newline at end of file diff --git a/docs/build/html/namespacemlx_1_1core_1_1metal.html b/docs/build/html/namespacemlx_1_1core_1_1metal.html index 82e859ea8..c413c6be7 100644 --- a/docs/build/html/namespacemlx_1_1core_1_1metal.html +++ b/docs/build/html/namespacemlx_1_1core_1_1metal.html @@ -230,10 +230,12 @@ Functions   std::unique_ptr< void, std::function< void(void *)> > new_scoped_memory_pool ()   -std::function< void()> make_task (array arr, bool signal) -  -std::function< void()> make_synchronize_task (Stream s, std::shared_ptr< std::promise< void > > p) -  +void eval (array &arr) +  +void finalize (Stream s) +  +void synchronize (Stream s) + 

                  Typedef Documentation

                  @@ -423,6 +425,23 @@ Functions

                  Get information about the GPU and system settings.

                  +
                  +
                  + +

                  ◆ eval()

                  + +
                  +
                  + + + + + + + +
                  void mlx::core::metal::eval (array & arr)
                  +
                  +
                  @@ -440,6 +459,23 @@ Functions
                  +
                  + + +

                  ◆ finalize()

                  + +
                  +
                  + + + + + + + +
                  void mlx::core::metal::finalize (Stream s)
                  +
                  +
                  @@ -618,48 +654,6 @@ Functions
                  -
                  - - -

                  ◆ make_synchronize_task()

                  - -
                  -
                  - - - - - - - - - - - -
                  std::function< void()> mlx::core::metal::make_synchronize_task (Stream s,
                  std::shared_ptr< std::promise< void > > p )
                  -
                  - -
                  -
                  - -

                  ◆ make_task()

                  - -
                  -
                  - - - - - - - - - - - -
                  std::function< void()> mlx::core::metal::make_task (array arr,
                  bool signal )
                  -
                  -
                  @@ -1023,6 +1017,23 @@ Functions
                  +
                  + + +

                  ◆ synchronize()

                  + +
                  +
                  + + + + + + + +
                  void mlx::core::metal::synchronize (Stream s)
                  +
                  +
                  diff --git a/docs/build/html/namespacemlx_1_1core_1_1metal.js b/docs/build/html/namespacemlx_1_1core_1_1metal.js index d9c3718c7..24a681ded 100644 --- a/docs/build/html/namespacemlx_1_1core_1_1metal.js +++ b/docs/build/html/namespacemlx_1_1core_1_1metal.js @@ -18,7 +18,9 @@ var namespacemlx_1_1core_1_1metal = [ "copy", "namespacemlx_1_1core_1_1metal.html#aa215e631e2680f04a591b88d91571719", null ], [ "device", "namespacemlx_1_1core_1_1metal.html#a910797b74824e6ee576fbb533dee8b57", null ], [ "device_info", "namespacemlx_1_1core_1_1metal.html#aebddc0ae4bc73a1acebc4a844475593b", null ], + [ "eval", "namespacemlx_1_1core_1_1metal.html#a87f378c14345e475d7e5701a987b66cd", null ], [ "fft", "namespacemlx_1_1core_1_1metal.html#a39f43360d9e916fcf7e86c919b419554", null ], + [ "finalize", "namespacemlx_1_1core_1_1metal.html#a5bfb8d4e6a7d1e51010d81ce008c3232", null ], [ "gather", "namespacemlx_1_1core_1_1metal.html#a545de371fefba1feec2e70b7e9f4187c", null ], [ "gather_axis", "namespacemlx_1_1core_1_1metal.html#adc66b1b48b51ac2d2f1f5bfac1b95ee3", null ], [ "gemm", "namespacemlx_1_1core_1_1metal.html#ac46fd23516a61fc56d997910e4144281", null ], @@ -29,8 +31,6 @@ var namespacemlx_1_1core_1_1metal = [ "get_peak_memory", "namespacemlx_1_1core_1_1metal.html#a4b67d680cefa95f0ed5801f0e14e48ce", null ], [ "hadamard", "namespacemlx_1_1core_1_1metal.html#a8bd0072616087cd568c2c804e7114aa9", null ], [ "is_available", "namespacemlx_1_1core_1_1metal.html#a0cdf2c08c7bc0927a86070adc206987f", null ], - [ "make_synchronize_task", "namespacemlx_1_1core_1_1metal.html#ab31abdda3052162d59f6590a89e38337", null ], - [ "make_task", "namespacemlx_1_1core_1_1metal.html#a4552b7ccdfa7f3cc9895c09799d8048e", null ], [ "new_scoped_memory_pool", "namespacemlx_1_1core_1_1metal.html#a46583a1aba89449fa72e6cb3a7090981", null ], [ "new_stream", "namespacemlx_1_1core_1_1metal.html#a8b4188f9a090a1da42d62b8a369bf106", null ], [ "quantized", "namespacemlx_1_1core_1_1metal.html#a949f029424218ab5c5588563d2e076f5", null ], @@ -52,6 +52,7 @@ var namespacemlx_1_1core_1_1metal = [ "steel_gemm_masked", "namespacemlx_1_1core_1_1metal.html#a962272ca73d26c08f76f706a128fd71f", null ], [ "steel_gemm_splitk", "namespacemlx_1_1core_1_1metal.html#ad0dfd40ba7c09755711ceb731e57a5ac", null ], [ "stop_capture", "namespacemlx_1_1core_1_1metal.html#ac90714424e36fb01e04550de69b8314f", null ], + [ "synchronize", "namespacemlx_1_1core_1_1metal.html#acc15b940ea02dcac263a1af9e39ec16b", null ], [ "ternary", "namespacemlx_1_1core_1_1metal.html#a2d1c92ba6897c0a7a428fed63279b61f", null ], [ "ternary_ops", "namespacemlx_1_1core_1_1metal.html#a11b593b07e9a33e5f78fe4695fb99ec9", null ], [ "unary", "namespacemlx_1_1core_1_1metal.html#afac64fd56ac492d6baf6de7e8a00b039", null ], diff --git a/docs/build/html/namespacemlx_1_1steel.html b/docs/build/html/namespacemlx_1_1steel.html index 81612d445..b9158de66 100644 --- a/docs/build/html/namespacemlx_1_1steel.html +++ b/docs/build/html/namespacemlx_1_1steel.html @@ -115,6 +115,8 @@ $(function(){initNavTree('namespacemlx_1_1steel.html',''); initResizable(true); Classes struct  AccumHelper   +struct  AttnMaskParams +  struct  AttnParams   struct  BaseMMAFrag diff --git a/docs/build/html/namespacemlx_1_1steel.js b/docs/build/html/namespacemlx_1_1steel.js index 4acdb10eb..8d4be1a61 100644 --- a/docs/build/html/namespacemlx_1_1steel.js +++ b/docs/build/html/namespacemlx_1_1steel.js @@ -1,6 +1,7 @@ var namespacemlx_1_1steel = [ [ "AccumHelper", "structmlx_1_1steel_1_1_accum_helper.html", "structmlx_1_1steel_1_1_accum_helper" ], + [ "AttnMaskParams", "structmlx_1_1steel_1_1_attn_mask_params.html", "structmlx_1_1steel_1_1_attn_mask_params" ], [ "AttnParams", "structmlx_1_1steel_1_1_attn_params.html", "structmlx_1_1steel_1_1_attn_params" ], [ "BaseMMAFrag", "structmlx_1_1steel_1_1_base_m_m_a_frag.html", null ], [ "BaseMMAFrag< T, 8, 8 >", 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+"classmlx_1_1core_1_1_slice.html":[2,0,1,0,128], +"classmlx_1_1core_1_1_slice.html#a069dafc62bf71e3ebc0bd99d96ec23be":[1,0,1,0,131,6], +"classmlx_1_1core_1_1_slice.html#a069dafc62bf71e3ebc0bd99d96ec23be":[2,0,1,0,128,6], +"classmlx_1_1core_1_1_slice.html#a291746a527ff991b66249fb2b54b685f":[1,0,1,0,131,7], +"classmlx_1_1core_1_1_slice.html#a291746a527ff991b66249fb2b54b685f":[2,0,1,0,128,7], +"classmlx_1_1core_1_1_slice.html#a3aa025acbf4a9ca9e030a1e6bda102f7":[1,0,1,0,131,0], +"classmlx_1_1core_1_1_slice.html#a3aa025acbf4a9ca9e030a1e6bda102f7":[2,0,1,0,128,0], +"classmlx_1_1core_1_1_slice.html#a43202c3b8966ae1db9ab82072e4918b0":[1,0,1,0,131,3], +"classmlx_1_1core_1_1_slice.html#a43202c3b8966ae1db9ab82072e4918b0":[2,0,1,0,128,3] }; diff --git a/docs/build/html/objects.inv b/docs/build/html/objects.inv index 1af101107..b62719692 100644 Binary files a/docs/build/html/objects.inv and b/docs/build/html/objects.inv differ diff --git a/docs/build/html/ops_8h_source.html b/docs/build/html/ops_8h_source.html index ee75b1820..2dccf161b 100644 --- a/docs/build/html/ops_8h_source.html +++ b/docs/build/html/ops_8h_source.html @@ -119,21 +119,21 @@ $(function(){initNavTree('ops_8h_source.html',''); initResizable(true); });
                  12namespace mlx::core {
                  13
                  18
                  -
                  22array arange(
                  +
                  22array arange(
                  23 double start,
                  24 double stop,
                  25 double step,
                  26 Dtype dtype,
                  27 StreamOrDevice s = {});
                  -
                  28array arange(double start, double stop, double step, StreamOrDevice s = {});
                  -
                  29array arange(double start, double stop, Dtype dtype, StreamOrDevice s = {});
                  -
                  30array arange(double start, double stop, StreamOrDevice s = {});
                  -
                  31array arange(double stop, Dtype dtype, StreamOrDevice s = {});
                  -
                  32array arange(double stop, StreamOrDevice s = {});
                  +
                  28array arange(double start, double stop, double step, StreamOrDevice s = {});
                  +
                  29array arange(double start, double stop, Dtype dtype, StreamOrDevice s = {});
                  +
                  30array arange(double start, double stop, StreamOrDevice s = {});
                  +
                  31array arange(double stop, Dtype dtype, StreamOrDevice s = {});
                  +
                  32array arange(double stop, StreamOrDevice s = {});
                  33
                  -
                  34array arange(int start, int stop, int step, StreamOrDevice s = {});
                  -
                  35array arange(int start, int stop, StreamOrDevice s = {});
                  -
                  36array arange(int stop, StreamOrDevice s = {});
                  +
                  34array arange(int start, int stop, int step, StreamOrDevice s = {});
                  +
                  35array arange(int start, int stop, StreamOrDevice s = {});
                  +
                  36array arange(int stop, StreamOrDevice s = {});
                  37
                  39array linspace(
                  40 double start,
                  @@ -151,7 +151,7 @@ $(function(){initNavTree('ops_8h_source.html',''); initResizable(true); });
                  54 size_t offset,
                  55 StreamOrDevice s = {});
                  56
                  -
                  58array copy(array a, StreamOrDevice s = {});
                  +
                  58array copy(array a, StreamOrDevice s = {});
                  59
                  61array full(Shape shape, array vals, Dtype dtype, StreamOrDevice s = {});
                  62array full(Shape shape, array vals, StreamOrDevice s = {});
                  @@ -950,7 +950,7 @@ $(function(){initNavTree('ops_8h_source.html',''); initResizable(true); });
                  920}
                  921
                  -
                  923array matmul(const array& a, const array& b, StreamOrDevice s = {});
                  +
                  923array matmul(const array& a, const array& b, StreamOrDevice s = {});
                  924
                  926array gather(
                  927 const array& a,
                  @@ -1497,6 +1497,7 @@ $(function(){initNavTree('ops_8h_source.html',''); initResizable(true); });
                  mlx::core::maximum
                  array maximum(const array &a, const array &b, StreamOrDevice s={})
                  Element-wise maximum between two arrays.
                  mlx::core::slice_update
                  array slice_update(const array &src, const array &update, Shape start, Shape stop, Shape strides, StreamOrDevice s={})
                  Update a slice from the source array.
                  mlx::core::argmin
                  array argmin(const array &a, bool keepdims, StreamOrDevice s={})
                  Returns the index of the minimum value in the array.
                  +
                  mlx::core::arange
                  array arange(double start, double stop, double step, Dtype dtype, StreamOrDevice s={})
                  A 1D array of numbers starting at start (optional), stopping at stop, stepping by step (optional).
                  mlx::core::var
                  array var(const array &a, bool keepdims, int ddof=0, StreamOrDevice s={})
                  Computes the variance of the elements of an array.
                  mlx::core::softmax
                  array softmax(const array &a, const std::vector< int > &axes, bool precise=false, StreamOrDevice s={})
                  Softmax of an array.
                  mlx::core::sort
                  array sort(const array &a, StreamOrDevice s={})
                  Returns a sorted copy of the flattened array.
                  @@ -1590,9 +1591,8 @@ $(function(){initNavTree('ops_8h_source.html',''); initResizable(true); });
                  mlx::core::right_shift
                  array right_shift(const array &a, const array &b, StreamOrDevice s={})
                  Shift bits to the right.
                  mlx::core::zeros_like
                  array zeros_like(const array &a, StreamOrDevice s={})
                  mlx::core
                  Definition allocator.h:7
                  -
                  mlx::core::arange
                  void arange(const std::vector< array > &inputs, array &out, double start, double step)
                  Definition arange.h:24
                  +
                  mlx::core::copy
                  void copy(const array &src, array &dst, CopyType ctype, Stream stream)
                  mlx::core::to_stream
                  Stream to_stream(StreamOrDevice s)
                  -
                  mlx::core::copy
                  void copy(const array &src, array &dst, CopyType ctype)
                  mlx::core::slice
                  void slice(const array &in, array &out, const Shape &start_indices, const Shape &strides)
                  mlx::core::int32
                  constexpr Dtype int32
                  Definition dtype.h:77
                  mlx::core::float32
                  constexpr Dtype float32
                  Definition dtype.h:81
                  @@ -1602,7 +1602,7 @@ $(function(){initNavTree('ops_8h_source.html',''); initResizable(true); });
                  mlx::core::operator==
                  bool operator==(const Device &lhs, const Device &rhs)
                  mlx::core::operator!=
                  bool operator!=(const Device &lhs, const Device &rhs)
                  mlx::core::StreamOrDevice
                  std::variant< std::monostate, Stream, Device > StreamOrDevice
                  Definition utils.h:15
                  -
                  mlx::core::matmul
                  void matmul(const array &a, const array &b, array &out, bool a_transposed, bool b_transposed, size_t lda, size_t ldb, float alpha, float beta)
                  +
                  mlx::core::matmul
                  void matmul(const T *a, const T *b, T *out, bool a_transposed, bool b_transposed, size_t lda, size_t ldb, size_t ldc, float alpha, float beta, size_t batch_size, const Shape &a_shape, const Strides &a_strides, const Shape &b_shape, const Strides &b_strides)
                  mlx::core::Dtype
                  Definition dtype.h:13
                  diff --git a/docs/build/html/primitives_8h.html b/docs/build/html/primitives_8h.html index 3c4ef0046..5fbf22596 100644 --- a/docs/build/html/primitives_8h.html +++ b/docs/build/html/primitives_8h.html @@ -112,7 +112,7 @@ $(function(){initNavTree('primitives_8h.html',''); initResizable(true); });
                  #include <unordered_set>
                  #include "mlx/array.h"
                  #include "mlx/device.h"
                  -#include "mlx/io/load.h"
                  +#include "mlx/io/load.h"
                  #include "mlx/stream.h"

                  Go to the source code of this file.

                  diff --git a/docs/build/html/primitives_8h_source.html b/docs/build/html/primitives_8h_source.html index 86e662567..3c927d9d6 100644 --- a/docs/build/html/primitives_8h_source.html +++ b/docs/build/html/primitives_8h_source.html @@ -113,7 +113,7 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  6
                  7#include "mlx/array.h"
                  8#include "mlx/device.h"
                  -
                  9#include "mlx/io/load.h"
                  +
                  9#include "mlx/io/load.h"
                  10#include "mlx/stream.h"
                  11
                  @@ -1538,1391 +1538,1383 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  1231 : UnaryPrimitive(stream),
                  1232 reader_(std::move(reader)),
                  1233 offset_(offset),
                  -
                  1234 swap_endianness_(swap_endianness) {
                  -
                  1235 if (stream.device == Device::gpu) {
                  -
                  1236 io_stream();
                  -
                  1237 }
                  -
                  1238 }
                  +
                  1234 swap_endianness_(swap_endianness) {}
                  -
                  1239
                  -
                  1240 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1241 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1242
                  -
                  1243 DEFINE_PRINT(Load)
                  -
                  1244
                  -
                  1245 private:
                  -
                  1246 Stream& io_stream() {
                  -
                  1247 static Stream io_stream = new_stream(Device::cpu);
                  -
                  1248 return io_stream;
                  -
                  1249 };
                  -
                  1250 std::shared_ptr<io::Reader> reader_;
                  -
                  1251 size_t offset_;
                  -
                  1252 bool swap_endianness_;
                  -
                  1253};
                  +
                  1235
                  +
                  1236 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1237 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1238
                  +
                  1239 DEFINE_PRINT(Load)
                  +
                  1240
                  +
                  1241 private:
                  +
                  1242 std::shared_ptr<io::Reader> reader_;
                  +
                  1243 size_t offset_;
                  +
                  1244 bool swap_endianness_;
                  +
                  1245};
                  -
                  1254
                  -
                  -
                  1255class Log : public UnaryPrimitive {
                  -
                  1256 public:
                  -
                  1257 enum Base { two, ten, e };
                  -
                  1258
                  -
                  -
                  1259 explicit Log(Stream stream, Base base)
                  -
                  1260 : UnaryPrimitive(stream), base_(base) {}
                  +
                  1246
                  +
                  +
                  1247class Log : public UnaryPrimitive {
                  +
                  1248 public:
                  +
                  1249 enum Base { two, ten, e };
                  +
                  1250
                  +
                  +
                  1251 explicit Log(Stream stream, Base base)
                  +
                  1252 : UnaryPrimitive(stream), base_(base) {}
                  +
                  1253
                  +
                  1254 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1255 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1256
                  +
                  1257 DEFINE_VMAP()
                  +
                  1258 DEFINE_GRADS()
                  +
                  1259 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1260 DEFINE_INPUT_OUTPUT_SHAPE()
                  1261
                  -
                  1262 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1263 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1264
                  -
                  1265 DEFINE_VMAP()
                  -
                  1266 DEFINE_GRADS()
                  -
                  1267 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1268 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1269
                  -
                  -
                  1270 Base state() const {
                  -
                  1271 return base_;
                  -
                  1272 };
                  +
                  +
                  1262 Base state() const {
                  +
                  1263 return base_;
                  +
                  1264 };
                  -
                  1273
                  -
                  -
                  1274 void print(std::ostream& os) override {
                  -
                  1275 switch (base_) {
                  -
                  1276 case e:
                  -
                  1277 os << "Log";
                  -
                  1278 break;
                  -
                  1279 case two:
                  -
                  1280 os << "Log2";
                  -
                  1281 break;
                  -
                  1282 case ten:
                  -
                  1283 os << "Log10";
                  -
                  1284 break;
                  -
                  1285 }
                  -
                  1286 }
                  +
                  1265
                  +
                  +
                  1266 void print(std::ostream& os) override {
                  +
                  1267 switch (base_) {
                  +
                  1268 case e:
                  +
                  1269 os << "Log";
                  +
                  1270 break;
                  +
                  1271 case two:
                  +
                  1272 os << "Log2";
                  +
                  1273 break;
                  +
                  1274 case ten:
                  +
                  1275 os << "Log10";
                  +
                  1276 break;
                  +
                  1277 }
                  +
                  1278 }
                  +
                  1279
                  +
                  1280 private:
                  +
                  1281 Base base_;
                  +
                  1282};
                  +
                  +
                  1283
                  +
                  +
                  1284class Log1p : public UnaryPrimitive {
                  +
                  1285 public:
                  +
                  1286 explicit Log1p(Stream stream) : UnaryPrimitive(stream) {}
                  1287
                  -
                  1288 private:
                  -
                  1289 Base base_;
                  -
                  1290};
                  +
                  1288 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1289 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1290
                  +
                  1291 DEFINE_VMAP()
                  +
                  1292 DEFINE_GRADS()
                  +
                  1293 DEFINE_PRINT(Log1p)
                  +
                  1294 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1295};
                  -
                  1291
                  -
                  -
                  1292class Log1p : public UnaryPrimitive {
                  -
                  1293 public:
                  -
                  1294 explicit Log1p(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1295
                  -
                  1296 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1297 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1298
                  -
                  1299 DEFINE_VMAP()
                  -
                  1300 DEFINE_GRADS()
                  -
                  1301 DEFINE_PRINT(Log1p)
                  -
                  1302 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1303};
                  +
                  1296
                  +
                  +
                  1297class LogicalNot : public UnaryPrimitive {
                  +
                  1298 public:
                  +
                  1299 explicit LogicalNot(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1300
                  +
                  1301 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1302 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1303
                  +
                  1304 DEFINE_VMAP()
                  +
                  1305 DEFINE_GRADS()
                  +
                  1306 DEFINE_PRINT(LogicalNot)
                  +
                  1307 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1308 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1309};
                  -
                  1304
                  -
                  -
                  1305class LogicalNot : public UnaryPrimitive {
                  -
                  1306 public:
                  -
                  1307 explicit LogicalNot(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1308
                  -
                  1309 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1310 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1311
                  -
                  1312 DEFINE_VMAP()
                  -
                  1313 DEFINE_GRADS()
                  -
                  1314 DEFINE_PRINT(LogicalNot)
                  -
                  1315 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1316 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1317};
                  +
                  1310
                  +
                  +
                  1311class LogicalAnd : public UnaryPrimitive {
                  +
                  1312 public:
                  +
                  1313 explicit LogicalAnd(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1314
                  +
                  1315 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1316 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1317
                  +
                  1318 DEFINE_VMAP()
                  +
                  1319 DEFINE_GRADS()
                  +
                  1320 DEFINE_PRINT(LogicalAnd)
                  +
                  1321 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1322 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1323};
                  -
                  1318
                  -
                  -
                  1319class LogicalAnd : public UnaryPrimitive {
                  -
                  1320 public:
                  -
                  1321 explicit LogicalAnd(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1322
                  -
                  1323 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1324 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1325
                  -
                  1326 DEFINE_VMAP()
                  -
                  1327 DEFINE_GRADS()
                  -
                  1328 DEFINE_PRINT(LogicalAnd)
                  -
                  1329 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1330 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1331};
                  +
                  1324
                  +
                  +
                  1325class LogicalOr : public UnaryPrimitive {
                  +
                  1326 public:
                  +
                  1327 explicit LogicalOr(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1328
                  +
                  1329 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1330 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1331
                  +
                  1332 DEFINE_VMAP()
                  +
                  1333 DEFINE_GRADS()
                  +
                  1334 DEFINE_PRINT(LogicalOr)
                  +
                  1335 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1336 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1337};
                  -
                  1332
                  -
                  -
                  1333class LogicalOr : public UnaryPrimitive {
                  -
                  1334 public:
                  -
                  1335 explicit LogicalOr(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1336
                  -
                  1337 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1338 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1339
                  -
                  1340 DEFINE_VMAP()
                  -
                  1341 DEFINE_GRADS()
                  -
                  1342 DEFINE_PRINT(LogicalOr)
                  -
                  1343 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1344 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1345};
                  +
                  1338
                  +
                  +
                  1339class LogAddExp : public UnaryPrimitive {
                  +
                  1340 public:
                  +
                  1341 explicit LogAddExp(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1342
                  +
                  1343 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1344 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1345
                  +
                  1346 DEFINE_VMAP()
                  +
                  1347 DEFINE_GRADS()
                  +
                  1348 DEFINE_PRINT(LogAddExp)
                  +
                  1349 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1350 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1351};
                  -
                  1346
                  -
                  -
                  1347class LogAddExp : public UnaryPrimitive {
                  -
                  1348 public:
                  -
                  1349 explicit LogAddExp(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1350
                  -
                  1351 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1352 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1353
                  -
                  1354 DEFINE_VMAP()
                  -
                  1355 DEFINE_GRADS()
                  -
                  1356 DEFINE_PRINT(LogAddExp)
                  -
                  1357 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1358 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1359};
                  +
                  1352
                  +
                  +
                  1353class Matmul : public UnaryPrimitive {
                  +
                  1354 public:
                  +
                  1355 explicit Matmul(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1356
                  +
                  1357 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1358 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1359
                  +
                  1360 DEFINE_GRADS()
                  +
                  1361 DEFINE_VMAP()
                  +
                  1362 DEFINE_PRINT(Matmul)
                  +
                  1363 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1364 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  +
                  1365};
                  -
                  1360
                  -
                  -
                  1361class Matmul : public UnaryPrimitive {
                  -
                  1362 public:
                  -
                  1363 explicit Matmul(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1364
                  -
                  1365 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1366 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1367
                  -
                  1368 DEFINE_GRADS()
                  -
                  1369 DEFINE_VMAP()
                  -
                  1370 DEFINE_PRINT(Matmul)
                  -
                  1371 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1372 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  -
                  1373};
                  +
                  1366
                  +
                  +
                  1367class Maximum : public UnaryPrimitive {
                  +
                  1368 public:
                  +
                  1369 explicit Maximum(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1370
                  +
                  1371 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1372 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1373
                  +
                  1374 DEFINE_VMAP()
                  +
                  1375 DEFINE_GRADS()
                  +
                  1376 DEFINE_PRINT(Maximum)
                  +
                  1377 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1378 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1379};
                  -
                  1374
                  -
                  -
                  1375class Maximum : public UnaryPrimitive {
                  -
                  1376 public:
                  -
                  1377 explicit Maximum(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1378
                  -
                  1379 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1380 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1381
                  -
                  1382 DEFINE_VMAP()
                  -
                  1383 DEFINE_GRADS()
                  -
                  1384 DEFINE_PRINT(Maximum)
                  -
                  1385 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1386 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1387};
                  +
                  1380
                  +
                  +
                  1381class Minimum : public UnaryPrimitive {
                  +
                  1382 public:
                  +
                  1383 explicit Minimum(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1384
                  +
                  1385 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1386 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1387
                  +
                  1388 DEFINE_VMAP()
                  +
                  1389 DEFINE_GRADS()
                  +
                  1390 DEFINE_PRINT(Minimum)
                  +
                  1391 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1392 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1393};
                  -
                  1388
                  -
                  -
                  1389class Minimum : public UnaryPrimitive {
                  -
                  1390 public:
                  -
                  1391 explicit Minimum(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1392
                  -
                  1393 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1394 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1395
                  -
                  1396 DEFINE_VMAP()
                  -
                  1397 DEFINE_GRADS()
                  -
                  1398 DEFINE_PRINT(Minimum)
                  -
                  1399 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1400 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1401};
                  +
                  1394
                  +
                  +
                  1395class Multiply : public UnaryPrimitive {
                  +
                  1396 public:
                  +
                  1397 explicit Multiply(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1398
                  +
                  1399 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1400 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1401
                  +
                  1402 DEFINE_VMAP()
                  +
                  1403 DEFINE_GRADS()
                  +
                  1404 DEFINE_PRINT(Multiply)
                  +
                  1405 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1406 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1407};
                  -
                  1402
                  -
                  -
                  1403class Multiply : public UnaryPrimitive {
                  -
                  1404 public:
                  -
                  1405 explicit Multiply(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1406
                  -
                  1407 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1408 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1409
                  -
                  1410 DEFINE_VMAP()
                  -
                  1411 DEFINE_GRADS()
                  -
                  1412 DEFINE_PRINT(Multiply)
                  -
                  1413 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1414 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1415};
                  +
                  1408
                  +
                  +
                  1409class Negative : public UnaryPrimitive {
                  +
                  1410 public:
                  +
                  1411 explicit Negative(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1412
                  +
                  1413 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1414 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1415
                  +
                  1416 DEFINE_VMAP()
                  +
                  1417 DEFINE_GRADS()
                  +
                  1418 DEFINE_PRINT(Negative)
                  +
                  1419 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1420 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1421};
                  -
                  1416
                  -
                  -
                  1417class Negative : public UnaryPrimitive {
                  -
                  1418 public:
                  -
                  1419 explicit Negative(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1420
                  -
                  1421 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1422 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1423
                  -
                  1424 DEFINE_VMAP()
                  -
                  1425 DEFINE_GRADS()
                  -
                  1426 DEFINE_PRINT(Negative)
                  -
                  1427 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1428 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1429};
                  +
                  1422
                  +
                  +
                  1423class NotEqual : public UnaryPrimitive {
                  +
                  1424 public:
                  +
                  1425 explicit NotEqual(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1426
                  +
                  1427 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1428 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1429
                  +
                  1430 DEFINE_VMAP()
                  +
                  1431 DEFINE_GRADS()
                  +
                  1432 DEFINE_PRINT(NotEqual)
                  +
                  1433 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1434 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1435};
                  -
                  1430
                  -
                  -
                  1431class NotEqual : public UnaryPrimitive {
                  -
                  1432 public:
                  -
                  1433 explicit NotEqual(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1434
                  -
                  1435 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1436 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1437
                  -
                  1438 DEFINE_VMAP()
                  -
                  1439 DEFINE_GRADS()
                  -
                  1440 DEFINE_PRINT(NotEqual)
                  -
                  1441 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1442 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1443};
                  +
                  1436
                  +
                  +
                  1437class NumberOfElements : public UnaryPrimitive {
                  +
                  1438 public:
                  +
                  +
                  1439 explicit NumberOfElements(
                  +
                  1440 Stream stream,
                  +
                  1441 std::vector<int> axes,
                  +
                  1442 bool inverted,
                  +
                  1443 Dtype dtype)
                  +
                  1444 : UnaryPrimitive(stream),
                  +
                  1445 axes_(std::move(axes)),
                  +
                  1446 inverted_(inverted),
                  +
                  1447 dtype_(dtype) {}
                  -
                  1444
                  -
                  -
                  1445class NumberOfElements : public UnaryPrimitive {
                  -
                  1446 public:
                  -
                  -
                  1447 explicit NumberOfElements(
                  -
                  1448 Stream stream,
                  -
                  1449 std::vector<int> axes,
                  -
                  1450 bool inverted,
                  -
                  1451 Dtype dtype)
                  -
                  1452 : UnaryPrimitive(stream),
                  -
                  1453 axes_(std::move(axes)),
                  -
                  1454 inverted_(inverted),
                  -
                  1455 dtype_(dtype) {}
                  +
                  1448
                  +
                  1449 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1450 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1451
                  +
                  1452 DEFINE_VMAP()
                  +
                  1453 DEFINE_PRINT(NumberOfElements)
                  +
                  1454 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  1455 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override {
                  +
                  1456 return {{}};
                  +
                  1457 }
                  -
                  1456
                  -
                  1457 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1458 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1459
                  -
                  1460 DEFINE_VMAP()
                  -
                  1461 DEFINE_PRINT(NumberOfElements)
                  -
                  1462 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  1463 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override {
                  -
                  1464 return {{}};
                  -
                  1465 }
                  +
                  +
                  1458 std::tuple<std::vector<int>, bool, Dtype> state() const {
                  +
                  1459 return {axes_, inverted_, dtype_};
                  +
                  1460 }
                  -
                  -
                  1466 std::tuple<std::vector<int>, bool, Dtype> state() const {
                  -
                  1467 return {axes_, inverted_, dtype_};
                  -
                  1468 }
                  +
                  1461
                  +
                  1462 private:
                  +
                  1463 std::vector<int> axes_;
                  +
                  1464 bool inverted_;
                  +
                  1465 Dtype dtype_;
                  +
                  1466
                  +
                  1467 void eval(const std::vector<array>& inputs, array& out);
                  +
                  1468};
                  1469
                  -
                  1470 private:
                  -
                  1471 std::vector<int> axes_;
                  -
                  1472 bool inverted_;
                  -
                  1473 Dtype dtype_;
                  -
                  1474
                  -
                  1475 void eval(const std::vector<array>& inputs, array& out);
                  -
                  1476};
                  +
                  +
                  1470class Pad : public UnaryPrimitive {
                  +
                  1471 public:
                  +
                  +
                  1472 explicit Pad(
                  +
                  1473 Stream stream,
                  +
                  1474 const std::vector<int>& axes,
                  +
                  1475 const Shape& low_pad_size,
                  +
                  1476 const Shape& high_pad_size)
                  +
                  1477 : UnaryPrimitive(stream),
                  +
                  1478 axes_(axes),
                  +
                  1479 low_pad_size_(low_pad_size),
                  +
                  1480 high_pad_size_(high_pad_size) {}
                  -
                  1477
                  -
                  -
                  1478class Pad : public UnaryPrimitive {
                  -
                  1479 public:
                  -
                  -
                  1480 explicit Pad(
                  -
                  1481 Stream stream,
                  -
                  1482 const std::vector<int>& axes,
                  -
                  1483 const Shape& low_pad_size,
                  -
                  1484 const Shape& high_pad_size)
                  -
                  1485 : UnaryPrimitive(stream),
                  -
                  1486 axes_(axes),
                  -
                  1487 low_pad_size_(low_pad_size),
                  -
                  1488 high_pad_size_(high_pad_size) {}
                  +
                  1481
                  +
                  1482 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1483 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1484
                  +
                  1485 DEFINE_VMAP()
                  +
                  1486 DEFINE_GRADS()
                  +
                  1487 DEFINE_PRINT(Pad)
                  +
                  1488 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  1489 auto state() const {
                  +
                  1490 return std::make_tuple(axes_, low_pad_size_, high_pad_size_);
                  +
                  1491 }
                  -
                  1489
                  -
                  1490 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1491 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  1492
                  -
                  1493 DEFINE_VMAP()
                  -
                  1494 DEFINE_GRADS()
                  -
                  1495 DEFINE_PRINT(Pad)
                  -
                  1496 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  1497 auto state() const {
                  -
                  1498 return std::make_tuple(axes_, low_pad_size_, high_pad_size_);
                  -
                  1499 }
                  +
                  1493 private:
                  +
                  1494 std::vector<int> axes_;
                  +
                  1495 Shape low_pad_size_;
                  +
                  1496 Shape high_pad_size_;
                  +
                  1497};
                  -
                  1500
                  -
                  1501 private:
                  -
                  1502 std::vector<int> axes_;
                  -
                  1503 Shape low_pad_size_;
                  -
                  1504 Shape high_pad_size_;
                  -
                  1505};
                  +
                  1498
                  +
                  +
                  1499class Partition : public UnaryPrimitive {
                  +
                  1500 public:
                  +
                  +
                  1501 explicit Partition(Stream stream, int kth, int axis)
                  +
                  1502 : UnaryPrimitive(stream), kth_(kth), axis_(axis) {}
                  +
                  1503
                  +
                  1504 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1505 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  1506
                  -
                  -
                  1507class Partition : public UnaryPrimitive {
                  -
                  1508 public:
                  -
                  -
                  1509 explicit Partition(Stream stream, int kth, int axis)
                  -
                  1510 : UnaryPrimitive(stream), kth_(kth), axis_(axis) {}
                  +
                  1507 DEFINE_VMAP()
                  +
                  1508 DEFINE_GRADS()
                  +
                  1509 DEFINE_PRINT(Partition)
                  +
                  1510 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1511 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  1512 auto state() const {
                  +
                  1513 return std::make_pair(kth_, axis_);
                  +
                  1514 };
                  -
                  1511
                  -
                  1512 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1513 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1514
                  -
                  1515 DEFINE_VMAP()
                  -
                  1516 DEFINE_GRADS()
                  -
                  1517 DEFINE_PRINT(Partition)
                  -
                  1518 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1519 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  1520 auto state() const {
                  -
                  1521 return std::make_pair(kth_, axis_);
                  -
                  1522 };
                  +
                  1515
                  +
                  1516 private:
                  +
                  1517 int kth_;
                  +
                  1518 int axis_;
                  +
                  1519};
                  -
                  1523
                  -
                  1524 private:
                  -
                  1525 int kth_;
                  -
                  1526 int axis_;
                  -
                  1527};
                  +
                  1520
                  +
                  +
                  1521class Power : public UnaryPrimitive {
                  +
                  1522 public:
                  +
                  1523 explicit Power(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1524
                  +
                  1525 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1526 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1527
                  +
                  1528 DEFINE_VMAP()
                  +
                  1529 DEFINE_GRADS()
                  +
                  1530 DEFINE_PRINT(Power)
                  +
                  1531 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1532 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1533};
                  -
                  1528
                  -
                  -
                  1529class Power : public UnaryPrimitive {
                  -
                  1530 public:
                  -
                  1531 explicit Power(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1532
                  -
                  1533 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1534 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1535
                  -
                  1536 DEFINE_VMAP()
                  -
                  1537 DEFINE_GRADS()
                  -
                  1538 DEFINE_PRINT(Power)
                  -
                  1539 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1540 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1541};
                  +
                  1534
                  +
                  +
                  1535class QuantizedMatmul : public UnaryPrimitive {
                  +
                  1536 public:
                  +
                  +
                  1537 explicit QuantizedMatmul(
                  +
                  1538 Stream stream,
                  +
                  1539 int group_size,
                  +
                  1540 int bits,
                  +
                  1541 bool transpose)
                  +
                  1542 : UnaryPrimitive(stream),
                  +
                  1543 group_size_(group_size),
                  +
                  1544 bits_(bits),
                  +
                  1545 transpose_(transpose) {}
                  -
                  1542
                  -
                  -
                  1543class QuantizedMatmul : public UnaryPrimitive {
                  -
                  1544 public:
                  -
                  -
                  1545 explicit QuantizedMatmul(
                  -
                  1546 Stream stream,
                  -
                  1547 int group_size,
                  -
                  1548 int bits,
                  -
                  1549 bool transpose)
                  -
                  1550 : UnaryPrimitive(stream),
                  -
                  1551 group_size_(group_size),
                  -
                  1552 bits_(bits),
                  -
                  1553 transpose_(transpose) {}
                  +
                  1546
                  +
                  1547 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1548 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1549
                  +
                  1550 DEFINE_VMAP()
                  +
                  1551 DEFINE_GRADS()
                  +
                  1552 DEFINE_PRINT(QuantizedMatmul)
                  +
                  1553 bool is_equivalent(const Primitive& other) const override;
                  +
                  1554 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  +
                  +
                  1555 auto state() const {
                  +
                  1556 return std::make_tuple(group_size_, bits_, transpose_);
                  +
                  1557 }
                  -
                  1554
                  -
                  1555 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1556 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1557
                  -
                  1558 DEFINE_VMAP()
                  -
                  1559 DEFINE_GRADS()
                  -
                  1560 DEFINE_PRINT(QuantizedMatmul)
                  -
                  1561 bool is_equivalent(const Primitive& other) const override;
                  -
                  1562 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  -
                  -
                  1563 auto state() const {
                  -
                  1564 return std::make_tuple(group_size_, bits_, transpose_);
                  -
                  1565 }
                  +
                  1558
                  +
                  1559 private:
                  +
                  1560 int group_size_;
                  +
                  1561 int bits_;
                  +
                  1562 bool transpose_;
                  +
                  1563};
                  -
                  1566
                  -
                  1567 private:
                  -
                  1568 int group_size_;
                  -
                  1569 int bits_;
                  -
                  1570 bool transpose_;
                  -
                  1571};
                  +
                  1564
                  +
                  +
                  1565class GatherQMM : public UnaryPrimitive {
                  +
                  1566 public:
                  +
                  +
                  1567 explicit GatherQMM(Stream stream, int group_size, int bits, bool transpose)
                  +
                  1568 : UnaryPrimitive(stream),
                  +
                  1569 group_size_(group_size),
                  +
                  1570 bits_(bits),
                  +
                  1571 transpose_(transpose) {}
                  1572
                  -
                  -
                  1573class GatherQMM : public UnaryPrimitive {
                  -
                  1574 public:
                  -
                  -
                  1575 explicit GatherQMM(Stream stream, int group_size, int bits, bool transpose)
                  -
                  1576 : UnaryPrimitive(stream),
                  -
                  1577 group_size_(group_size),
                  -
                  1578 bits_(bits),
                  -
                  1579 transpose_(transpose) {}
                  +
                  1573 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1574 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1575
                  +
                  1576 DEFINE_VMAP()
                  +
                  1577 DEFINE_GRADS()
                  +
                  1578 DEFINE_PRINT(GatherQMM)
                  +
                  1579 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  1580 auto state() const {
                  +
                  1581 return std::make_tuple(group_size_, bits_, transpose_);
                  +
                  1582 }
                  -
                  1580
                  -
                  1581 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1582 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  1583
                  -
                  1584 DEFINE_VMAP()
                  -
                  1585 DEFINE_GRADS()
                  -
                  1586 DEFINE_PRINT(GatherQMM)
                  -
                  1587 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  1588 auto state() const {
                  -
                  1589 return std::make_tuple(group_size_, bits_, transpose_);
                  -
                  1590 }
                  +
                  1584 private:
                  +
                  1585 int group_size_;
                  +
                  1586 int bits_;
                  +
                  1587 bool transpose_;
                  +
                  1588};
                  -
                  1591
                  -
                  1592 private:
                  -
                  1593 int group_size_;
                  -
                  1594 int bits_;
                  -
                  1595 bool transpose_;
                  -
                  1596};
                  +
                  1589
                  +
                  +
                  1590class RandomBits : public UnaryPrimitive {
                  +
                  1591 public:
                  +
                  +
                  1592 explicit RandomBits(Stream stream, const Shape& shape, int width)
                  +
                  1593 : UnaryPrimitive(stream), shape_(shape), width_(width) {}
                  +
                  1594
                  +
                  1595 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1596 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  1597
                  -
                  -
                  1598class RandomBits : public UnaryPrimitive {
                  -
                  1599 public:
                  -
                  -
                  1600 explicit RandomBits(Stream stream, const Shape& shape, int width)
                  -
                  1601 : UnaryPrimitive(stream), shape_(shape), width_(width) {}
                  +
                  1598 DEFINE_VMAP()
                  +
                  1599 DEFINE_PRINT(RandomBits)
                  +
                  1600 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  1601 std::pair<std::vector<int>, int> state() const {
                  +
                  1602 return {shape_, width_};
                  +
                  1603 };
                  -
                  1602
                  -
                  1603 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1604 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1605
                  -
                  1606 DEFINE_VMAP()
                  -
                  1607 DEFINE_PRINT(RandomBits)
                  -
                  1608 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  1609 std::pair<std::vector<int>, int> state() const {
                  -
                  1610 return {shape_, width_};
                  -
                  1611 };
                  +
                  1604
                  +
                  1605 private:
                  +
                  1606 Shape shape_;
                  +
                  1607 int width_;
                  +
                  1608};
                  -
                  1612
                  -
                  1613 private:
                  -
                  1614 Shape shape_;
                  -
                  1615 int width_;
                  -
                  1616};
                  +
                  1609
                  +
                  +
                  1610class Real : public UnaryPrimitive {
                  +
                  1611 public:
                  +
                  1612 explicit Real(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1613
                  +
                  1614 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1615 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1616
                  +
                  1617 DEFINE_VMAP()
                  +
                  1618 DEFINE_GRADS()
                  +
                  1619 DEFINE_PRINT(Real)
                  +
                  1620 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1621 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1622};
                  -
                  1617
                  -
                  -
                  1618class Real : public UnaryPrimitive {
                  -
                  1619 public:
                  -
                  1620 explicit Real(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1621
                  -
                  1622 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1623 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1624
                  -
                  1625 DEFINE_VMAP()
                  -
                  1626 DEFINE_GRADS()
                  -
                  1627 DEFINE_PRINT(Real)
                  -
                  1628 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1629 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1630};
                  +
                  1623
                  +
                  +
                  1624class Reshape : public UnaryPrimitive {
                  +
                  1625 public:
                  +
                  +
                  1626 explicit Reshape(Stream stream, const Shape& shape)
                  +
                  1627 : UnaryPrimitive(stream), shape_(shape) {}
                  +
                  1628
                  +
                  1629 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1630 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  1631
                  -
                  -
                  1632class Reshape : public UnaryPrimitive {
                  -
                  1633 public:
                  -
                  -
                  1634 explicit Reshape(Stream stream, const Shape& shape)
                  -
                  1635 : UnaryPrimitive(stream), shape_(shape) {}
                  +
                  1632 DEFINE_VMAP()
                  +
                  1633 DEFINE_GRADS()
                  +
                  1634 DEFINE_PRINT(Reshape)
                  +
                  1635 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  1636 std::vector<int> state() const {
                  +
                  1637 return shape_;
                  +
                  1638 };
                  -
                  1636
                  -
                  1637 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1638 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1639
                  -
                  1640 DEFINE_VMAP()
                  -
                  1641 DEFINE_GRADS()
                  -
                  1642 DEFINE_PRINT(Reshape)
                  -
                  1643 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  1644 std::vector<int> state() const {
                  -
                  1645 return shape_;
                  -
                  1646 };
                  +
                  1639 static Shape output_shape(const array& input, Shape shape);
                  +
                  1640 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  +
                  1641
                  +
                  1642 private:
                  +
                  1643 Shape shape_;
                  +
                  1644};
                  -
                  1647 static Shape output_shape(const array& input, Shape shape);
                  -
                  1648 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  +
                  1645
                  +
                  +
                  1646class Reduce : public UnaryPrimitive {
                  +
                  1647 public:
                  +
                  1648 enum ReduceType { And, Or, Sum, Prod, Min, Max };
                  1649
                  -
                  1650 private:
                  -
                  1651 Shape shape_;
                  -
                  1652};
                  +
                  +
                  1650 explicit Reduce(
                  +
                  1651 Stream stream,
                  +
                  1652 ReduceType reduce_type,
                  +
                  1653 const std::vector<int>& axes)
                  +
                  1654 : UnaryPrimitive(stream), reduce_type_(reduce_type), axes_(axes) {}
                  -
                  1653
                  -
                  -
                  1654class Reduce : public UnaryPrimitive {
                  -
                  1655 public:
                  -
                  1656 enum ReduceType { And, Or, Sum, Prod, Min, Max };
                  -
                  1657
                  -
                  -
                  1658 explicit Reduce(
                  -
                  1659 Stream stream,
                  -
                  1660 ReduceType reduce_type,
                  -
                  1661 const std::vector<int>& axes)
                  -
                  1662 : UnaryPrimitive(stream), reduce_type_(reduce_type), axes_(axes) {}
                  -
                  -
                  1663
                  -
                  1664 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1665 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1655
                  +
                  1656 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1657 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1658
                  +
                  1659 DEFINE_VMAP()
                  +
                  1660
                  +
                  1661 std::vector<array> vjp(
                  +
                  1662 const std::vector<array>& primals,
                  +
                  1663 const std::vector<array>& cotangents,
                  +
                  1664 const std::vector<int>& argnums,
                  +
                  1665 const std::vector<array>& outputs) override;
                  1666
                  -
                  1667 DEFINE_VMAP()
                  +
                  1667 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  1668
                  -
                  1669 std::vector<array> vjp(
                  -
                  1670 const std::vector<array>& primals,
                  -
                  1671 const std::vector<array>& cotangents,
                  -
                  1672 const std::vector<int>& argnums,
                  -
                  1673 const std::vector<array>& outputs) override;
                  -
                  1674
                  -
                  1675 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  -
                  1676
                  -
                  -
                  1677 void print(std::ostream& os) override {
                  -
                  1678 switch (reduce_type_) {
                  -
                  1679 case And:
                  -
                  1680 os << "And";
                  -
                  1681 break;
                  -
                  1682 case Or:
                  -
                  1683 os << "Or";
                  -
                  1684 break;
                  -
                  1685 case Sum:
                  -
                  1686 os << "Sum";
                  -
                  1687 break;
                  -
                  1688 case Prod:
                  -
                  1689 os << "Prod";
                  -
                  1690 break;
                  -
                  1691 case Min:
                  -
                  1692 os << "Min";
                  -
                  1693 break;
                  -
                  1694 case Max:
                  -
                  1695 os << "Max";
                  -
                  1696 break;
                  -
                  1697 }
                  -
                  1698 }
                  +
                  +
                  1669 void print(std::ostream& os) override {
                  +
                  1670 switch (reduce_type_) {
                  +
                  1671 case And:
                  +
                  1672 os << "And";
                  +
                  1673 break;
                  +
                  1674 case Or:
                  +
                  1675 os << "Or";
                  +
                  1676 break;
                  +
                  1677 case Sum:
                  +
                  1678 os << "Sum";
                  +
                  1679 break;
                  +
                  1680 case Prod:
                  +
                  1681 os << "Prod";
                  +
                  1682 break;
                  +
                  1683 case Min:
                  +
                  1684 os << "Min";
                  +
                  1685 break;
                  +
                  1686 case Max:
                  +
                  1687 os << "Max";
                  +
                  1688 break;
                  +
                  1689 }
                  +
                  1690 }
                  -
                  1699 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  1700 std::pair<ReduceType, std::vector<int>> state() const {
                  -
                  1701 return {reduce_type_, axes_};
                  -
                  1702 };
                  +
                  1691 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  1692 std::pair<ReduceType, std::vector<int>> state() const {
                  +
                  1693 return {reduce_type_, axes_};
                  +
                  1694 };
                  -
                  1703
                  -
                  1704 private:
                  -
                  1705 ReduceType reduce_type_;
                  -
                  1706 std::vector<int> axes_;
                  -
                  1707};
                  +
                  1695
                  +
                  1696 private:
                  +
                  1697 ReduceType reduce_type_;
                  +
                  1698 std::vector<int> axes_;
                  +
                  1699};
                  -
                  1708
                  -
                  -
                  1709class Round : public UnaryPrimitive {
                  -
                  1710 public:
                  -
                  1711 explicit Round(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1712
                  -
                  1713 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1714 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1715
                  -
                  1716 DEFINE_VMAP()
                  -
                  1717 DEFINE_GRADS()
                  -
                  1718 DEFINE_PRINT(Round)
                  -
                  1719 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1720 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1721};
                  +
                  1700
                  +
                  +
                  1701class Round : public UnaryPrimitive {
                  +
                  1702 public:
                  +
                  1703 explicit Round(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1704
                  +
                  1705 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1706 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1707
                  +
                  1708 DEFINE_VMAP()
                  +
                  1709 DEFINE_GRADS()
                  +
                  1710 DEFINE_PRINT(Round)
                  +
                  1711 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1712 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1713};
                  -
                  1722
                  -
                  -
                  1723class Scan : public UnaryPrimitive {
                  -
                  1724 public:
                  -
                  1725 enum ReduceType { Max, Min, Sum, Prod };
                  -
                  1726
                  -
                  -
                  1727 explicit Scan(
                  -
                  1728 Stream stream,
                  -
                  1729 ReduceType reduce_type,
                  -
                  1730 int axis,
                  -
                  1731 bool reverse,
                  -
                  1732 bool inclusive)
                  -
                  1733 : UnaryPrimitive(stream),
                  -
                  1734 reduce_type_(reduce_type),
                  -
                  1735 axis_(axis),
                  -
                  1736 reverse_(reverse),
                  -
                  1737 inclusive_(inclusive) {}
                  +
                  1714
                  +
                  +
                  1715class Scan : public UnaryPrimitive {
                  +
                  1716 public:
                  +
                  1717 enum ReduceType { Max, Min, Sum, Prod };
                  +
                  1718
                  +
                  +
                  1719 explicit Scan(
                  +
                  1720 Stream stream,
                  +
                  1721 ReduceType reduce_type,
                  +
                  1722 int axis,
                  +
                  1723 bool reverse,
                  +
                  1724 bool inclusive)
                  +
                  1725 : UnaryPrimitive(stream),
                  +
                  1726 reduce_type_(reduce_type),
                  +
                  1727 axis_(axis),
                  +
                  1728 reverse_(reverse),
                  +
                  1729 inclusive_(inclusive) {}
                  -
                  1738
                  -
                  1739 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1740 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1741
                  -
                  1742 DEFINE_VMAP()
                  -
                  1743 DEFINE_GRADS();
                  -
                  1744
                  -
                  -
                  1745 void print(std::ostream& os) override {
                  -
                  1746 os << "Cum";
                  -
                  1747 switch (reduce_type_) {
                  -
                  1748 case Sum:
                  -
                  1749 os << "Sum";
                  -
                  1750 break;
                  -
                  1751 case Prod:
                  -
                  1752 os << "Prod";
                  -
                  1753 break;
                  -
                  1754 case Min:
                  -
                  1755 os << "Min";
                  -
                  1756 break;
                  -
                  1757 case Max:
                  -
                  1758 os << "Max";
                  -
                  1759 break;
                  -
                  1760 }
                  -
                  1761 }
                  +
                  1730
                  +
                  1731 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1732 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1733
                  +
                  1734 DEFINE_VMAP()
                  +
                  1735 DEFINE_GRADS();
                  +
                  1736
                  +
                  +
                  1737 void print(std::ostream& os) override {
                  +
                  1738 os << "Cum";
                  +
                  1739 switch (reduce_type_) {
                  +
                  1740 case Sum:
                  +
                  1741 os << "Sum";
                  +
                  1742 break;
                  +
                  1743 case Prod:
                  +
                  1744 os << "Prod";
                  +
                  1745 break;
                  +
                  1746 case Min:
                  +
                  1747 os << "Min";
                  +
                  1748 break;
                  +
                  1749 case Max:
                  +
                  1750 os << "Max";
                  +
                  1751 break;
                  +
                  1752 }
                  +
                  1753 }
                  -
                  1762 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  1763 auto state() const {
                  -
                  1764 return std::make_tuple(reduce_type_, axis_, reverse_, inclusive_);
                  -
                  1765 }
                  +
                  1754 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  1755 auto state() const {
                  +
                  1756 return std::make_tuple(reduce_type_, axis_, reverse_, inclusive_);
                  +
                  1757 }
                  -
                  1766
                  -
                  1767 private:
                  -
                  1768 ReduceType reduce_type_;
                  -
                  1769 int axis_;
                  -
                  1770 bool reverse_;
                  -
                  1771 bool inclusive_;
                  -
                  1772};
                  +
                  1758
                  +
                  1759 private:
                  +
                  1760 ReduceType reduce_type_;
                  +
                  1761 int axis_;
                  +
                  1762 bool reverse_;
                  +
                  1763 bool inclusive_;
                  +
                  1764};
                  -
                  1773
                  -
                  -
                  1774class Scatter : public UnaryPrimitive {
                  -
                  1775 public:
                  -
                  1776 enum ReduceType { Max, Min, Sum, Prod, None };
                  -
                  1777
                  -
                  -
                  1778 explicit Scatter(
                  -
                  1779 Stream stream,
                  -
                  1780 ReduceType reduce_type,
                  -
                  1781 const std::vector<int>& axes)
                  -
                  1782 : UnaryPrimitive(stream), reduce_type_(reduce_type), axes_(axes) {}
                  +
                  1765
                  +
                  +
                  1766class Scatter : public UnaryPrimitive {
                  +
                  1767 public:
                  +
                  1768 enum ReduceType { Max, Min, Sum, Prod, None };
                  +
                  1769
                  +
                  +
                  1770 explicit Scatter(
                  +
                  1771 Stream stream,
                  +
                  1772 ReduceType reduce_type,
                  +
                  1773 const std::vector<int>& axes)
                  +
                  1774 : UnaryPrimitive(stream), reduce_type_(reduce_type), axes_(axes) {}
                  -
                  1783
                  -
                  1784 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1785 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1786
                  -
                  1787 DEFINE_VMAP();
                  -
                  1788 DEFINE_GRADS();
                  -
                  1789
                  -
                  -
                  1790 void print(std::ostream& os) override {
                  -
                  1791 os << "Scatter";
                  -
                  1792 switch (reduce_type_) {
                  -
                  1793 case Sum:
                  -
                  1794 os << " Sum";
                  -
                  1795 break;
                  -
                  1796 case Prod:
                  -
                  1797 os << " Prod";
                  +
                  1775
                  +
                  1776 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1777 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1778
                  +
                  1779 DEFINE_VMAP();
                  +
                  1780 DEFINE_GRADS();
                  +
                  1781
                  +
                  +
                  1782 void print(std::ostream& os) override {
                  +
                  1783 os << "Scatter";
                  +
                  1784 switch (reduce_type_) {
                  +
                  1785 case Sum:
                  +
                  1786 os << " Sum";
                  +
                  1787 break;
                  +
                  1788 case Prod:
                  +
                  1789 os << " Prod";
                  +
                  1790 break;
                  +
                  1791 case Min:
                  +
                  1792 os << " Min";
                  +
                  1793 break;
                  +
                  1794 case Max:
                  +
                  1795 os << " Max";
                  +
                  1796 break;
                  +
                  1797 case None:
                  1798 break;
                  -
                  1799 case Min:
                  -
                  1800 os << " Min";
                  -
                  1801 break;
                  -
                  1802 case Max:
                  -
                  1803 os << " Max";
                  -
                  1804 break;
                  -
                  1805 case None:
                  -
                  1806 break;
                  -
                  1807 }
                  -
                  1808 }
                  +
                  1799 }
                  +
                  1800 }
                  -
                  1809 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  1810 std::pair<ReduceType, std::vector<int>> state() const {
                  -
                  1811 return {reduce_type_, axes_};
                  -
                  1812 };
                  +
                  1801 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  1802 std::pair<ReduceType, std::vector<int>> state() const {
                  +
                  1803 return {reduce_type_, axes_};
                  +
                  1804 };
                  -
                  1813
                  -
                  1814 private:
                  -
                  1815 ReduceType reduce_type_;
                  -
                  1816 std::vector<int> axes_;
                  -
                  1817};
                  +
                  1805
                  +
                  1806 private:
                  +
                  1807 ReduceType reduce_type_;
                  +
                  1808 std::vector<int> axes_;
                  +
                  1809};
                  -
                  1818
                  -
                  -
                  1819class ScatterAxis : public UnaryPrimitive {
                  -
                  1820 public:
                  -
                  1821 enum ReduceType { Sum, None };
                  -
                  1822
                  -
                  -
                  1823 explicit ScatterAxis(Stream stream, ReduceType reduce_type, int axis)
                  -
                  1824 : UnaryPrimitive(stream), reduce_type_(reduce_type), axis_(axis) {}
                  +
                  1810
                  +
                  +
                  1811class ScatterAxis : public UnaryPrimitive {
                  +
                  1812 public:
                  +
                  1813 enum ReduceType { Sum, None };
                  +
                  1814
                  +
                  +
                  1815 explicit ScatterAxis(Stream stream, ReduceType reduce_type, int axis)
                  +
                  1816 : UnaryPrimitive(stream), reduce_type_(reduce_type), axis_(axis) {}
                  -
                  1825
                  -
                  1826 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1827 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1828
                  -
                  1829 DEFINE_VMAP()
                  -
                  1830 DEFINE_GRADS()
                  -
                  1831
                  -
                  -
                  1832 void print(std::ostream& os) override {
                  -
                  1833 os << "ScatterAxis";
                  -
                  1834 switch (reduce_type_) {
                  -
                  1835 case Sum:
                  -
                  1836 os << " Sum";
                  -
                  1837 break;
                  -
                  1838 case None:
                  -
                  1839 break;
                  -
                  1840 }
                  -
                  1841 }
                  +
                  1817
                  +
                  1818 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1819 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1820
                  +
                  1821 DEFINE_VMAP()
                  +
                  1822 DEFINE_GRADS()
                  +
                  1823
                  +
                  +
                  1824 void print(std::ostream& os) override {
                  +
                  1825 os << "ScatterAxis";
                  +
                  1826 switch (reduce_type_) {
                  +
                  1827 case Sum:
                  +
                  1828 os << " Sum";
                  +
                  1829 break;
                  +
                  1830 case None:
                  +
                  1831 break;
                  +
                  1832 }
                  +
                  1833 }
                  -
                  1842
                  -
                  1843 bool is_equivalent(const Primitive& other) const override;
                  -
                  1844 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  -
                  -
                  1845 std::pair<ReduceType, int> state() const {
                  -
                  1846 return {reduce_type_, axis_};
                  -
                  1847 }
                  +
                  1834
                  +
                  1835 bool is_equivalent(const Primitive& other) const override;
                  +
                  1836 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  +
                  +
                  1837 std::pair<ReduceType, int> state() const {
                  +
                  1838 return {reduce_type_, axis_};
                  +
                  1839 }
                  -
                  1848
                  -
                  1849 private:
                  -
                  1850 ReduceType reduce_type_;
                  -
                  1851 int axis_;
                  -
                  1852};
                  +
                  1840
                  +
                  1841 private:
                  +
                  1842 ReduceType reduce_type_;
                  +
                  1843 int axis_;
                  +
                  1844};
                  -
                  1853
                  -
                  -
                  1854class Sigmoid : public UnaryPrimitive {
                  -
                  1855 public:
                  -
                  1856 explicit Sigmoid(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1857
                  -
                  1858 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1859 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1860
                  -
                  1861 DEFINE_VMAP()
                  -
                  1862 DEFINE_GRADS()
                  -
                  1863 DEFINE_PRINT(Sigmoid)
                  -
                  1864 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1865 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1866};
                  +
                  1845
                  +
                  +
                  1846class Sigmoid : public UnaryPrimitive {
                  +
                  1847 public:
                  +
                  1848 explicit Sigmoid(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1849
                  +
                  1850 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1851 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1852
                  +
                  1853 DEFINE_VMAP()
                  +
                  1854 DEFINE_GRADS()
                  +
                  1855 DEFINE_PRINT(Sigmoid)
                  +
                  1856 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1857 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1858};
                  -
                  1867
                  -
                  -
                  1868class Sign : public UnaryPrimitive {
                  -
                  1869 public:
                  -
                  1870 explicit Sign(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1871
                  -
                  1872 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1873 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1874
                  -
                  1875 DEFINE_VMAP()
                  -
                  1876 DEFINE_GRADS()
                  -
                  1877 DEFINE_PRINT(Sign)
                  -
                  1878 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1879 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1880};
                  +
                  1859
                  +
                  +
                  1860class Sign : public UnaryPrimitive {
                  +
                  1861 public:
                  +
                  1862 explicit Sign(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1863
                  +
                  1864 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1865 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1866
                  +
                  1867 DEFINE_VMAP()
                  +
                  1868 DEFINE_GRADS()
                  +
                  1869 DEFINE_PRINT(Sign)
                  +
                  1870 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1871 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1872};
                  -
                  1881
                  -
                  -
                  1882class Sin : public UnaryPrimitive {
                  -
                  1883 public:
                  -
                  1884 explicit Sin(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1885
                  -
                  1886 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1887 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1888
                  -
                  1889 DEFINE_VMAP()
                  -
                  1890 DEFINE_GRADS()
                  -
                  1891 DEFINE_PRINT(Sin)
                  -
                  1892 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1893 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1894};
                  +
                  1873
                  +
                  +
                  1874class Sin : public UnaryPrimitive {
                  +
                  1875 public:
                  +
                  1876 explicit Sin(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1877
                  +
                  1878 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1879 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1880
                  +
                  1881 DEFINE_VMAP()
                  +
                  1882 DEFINE_GRADS()
                  +
                  1883 DEFINE_PRINT(Sin)
                  +
                  1884 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1885 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1886};
                  -
                  1895
                  -
                  -
                  1896class Sinh : public UnaryPrimitive {
                  -
                  1897 public:
                  -
                  1898 explicit Sinh(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  1899
                  -
                  1900 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1901 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1902
                  -
                  1903 DEFINE_VMAP()
                  -
                  1904 DEFINE_GRADS()
                  -
                  1905 DEFINE_PRINT(Sinh)
                  -
                  1906 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  1907 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  1908};
                  +
                  1887
                  +
                  +
                  1888class Sinh : public UnaryPrimitive {
                  +
                  1889 public:
                  +
                  1890 explicit Sinh(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  1891
                  +
                  1892 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1893 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1894
                  +
                  1895 DEFINE_VMAP()
                  +
                  1896 DEFINE_GRADS()
                  +
                  1897 DEFINE_PRINT(Sinh)
                  +
                  1898 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  1899 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  1900};
                  -
                  1909
                  -
                  -
                  1910class Slice : public UnaryPrimitive {
                  -
                  1911 public:
                  -
                  -
                  1912 explicit Slice(
                  -
                  1913 Stream stream,
                  -
                  1914 const Shape& start_indices,
                  -
                  1915 const Shape& end_indices,
                  -
                  1916 const Shape& strides)
                  -
                  1917 : UnaryPrimitive(stream),
                  -
                  1918 start_indices_(start_indices),
                  -
                  1919 end_indices_(end_indices),
                  -
                  1920 strides_(strides) {}
                  +
                  1901
                  +
                  +
                  1902class Slice : public UnaryPrimitive {
                  +
                  1903 public:
                  +
                  +
                  1904 explicit Slice(
                  +
                  1905 Stream stream,
                  +
                  1906 const Shape& start_indices,
                  +
                  1907 const Shape& end_indices,
                  +
                  1908 const Shape& strides)
                  +
                  1909 : UnaryPrimitive(stream),
                  +
                  1910 start_indices_(start_indices),
                  +
                  1911 end_indices_(end_indices),
                  +
                  1912 strides_(strides) {}
                  +
                  +
                  1913
                  +
                  1914 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1915 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1916
                  +
                  1917 DEFINE_VMAP()
                  +
                  1918 DEFINE_GRADS()
                  +
                  1919 DEFINE_PRINT(Slice)
                  +
                  1920 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  1921 auto state() const {
                  +
                  1922 return std::make_tuple(start_indices_, end_indices_, strides_);
                  +
                  1923 }
                  -
                  1921
                  -
                  1922 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1923 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  1924
                  -
                  1925 DEFINE_VMAP()
                  -
                  1926 DEFINE_GRADS()
                  -
                  1927 DEFINE_PRINT(Slice)
                  -
                  1928 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  1929 auto state() const {
                  -
                  1930 return std::make_tuple(start_indices_, end_indices_, strides_);
                  -
                  1931 }
                  +
                  1925 private:
                  +
                  1926 Shape start_indices_;
                  +
                  1927 Shape end_indices_;
                  +
                  1928 Shape strides_;
                  +
                  1929};
                  -
                  1932
                  -
                  1933 private:
                  -
                  1934 Shape start_indices_;
                  -
                  1935 Shape end_indices_;
                  -
                  1936 Shape strides_;
                  -
                  1937};
                  +
                  1930
                  +
                  +
                  1931class SliceUpdate : public UnaryPrimitive {
                  +
                  1932 public:
                  +
                  +
                  1933 explicit SliceUpdate(
                  +
                  1934 Stream stream,
                  +
                  1935 const Shape& start_indices,
                  +
                  1936 const Shape& end_indices,
                  +
                  1937 const Shape& strides)
                  +
                  1938 : UnaryPrimitive(stream),
                  +
                  1939 start_indices_(start_indices),
                  +
                  1940 end_indices_(end_indices),
                  +
                  1941 strides_(strides) {}
                  -
                  1938
                  -
                  -
                  1939class SliceUpdate : public UnaryPrimitive {
                  -
                  1940 public:
                  -
                  -
                  1941 explicit SliceUpdate(
                  -
                  1942 Stream stream,
                  -
                  1943 const Shape& start_indices,
                  -
                  1944 const Shape& end_indices,
                  -
                  1945 const Shape& strides)
                  -
                  1946 : UnaryPrimitive(stream),
                  -
                  1947 start_indices_(start_indices),
                  -
                  1948 end_indices_(end_indices),
                  -
                  1949 strides_(strides) {}
                  +
                  1942
                  +
                  1943 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1944 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1945
                  +
                  1946 DEFINE_VMAP()
                  +
                  1947 DEFINE_GRADS()
                  +
                  1948 DEFINE_PRINT(SliceUpdate)
                  +
                  1949 bool is_equivalent(const Primitive& other) const override;
                  +
                  1950 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  +
                  1951 auto state() const {
                  +
                  1952 return std::make_tuple(start_indices_, end_indices_, strides_);
                  +
                  1953 }
                  -
                  1950
                  -
                  1951 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1952 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1953
                  -
                  1954 DEFINE_VMAP()
                  -
                  1955 DEFINE_GRADS()
                  -
                  1956 DEFINE_PRINT(SliceUpdate)
                  -
                  1957 bool is_equivalent(const Primitive& other) const override;
                  -
                  1958 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  -
                  1959 auto state() const {
                  -
                  1960 return std::make_tuple(start_indices_, end_indices_, strides_);
                  -
                  1961 }
                  +
                  1954
                  +
                  1955 private:
                  +
                  1956 Shape start_indices_;
                  +
                  1957 Shape end_indices_;
                  +
                  1958 Shape strides_;
                  +
                  1959};
                  -
                  1962
                  -
                  1963 private:
                  -
                  1964 Shape start_indices_;
                  -
                  1965 Shape end_indices_;
                  -
                  1966 Shape strides_;
                  -
                  1967};
                  +
                  1960
                  +
                  +
                  1961class DynamicSlice : public UnaryPrimitive {
                  +
                  1962 public:
                  +
                  +
                  1963 explicit DynamicSlice(Stream stream, std::vector<int> axes, Shape slice_size)
                  +
                  1964 : UnaryPrimitive(stream),
                  +
                  1965 axes_(std::move(axes)),
                  +
                  1966 slice_size_(std::move(slice_size)) {}
                  -
                  1968
                  -
                  -
                  1969class DynamicSlice : public UnaryPrimitive {
                  -
                  1970 public:
                  -
                  -
                  1971 explicit DynamicSlice(Stream stream, std::vector<int> axes, Shape slice_size)
                  -
                  1972 : UnaryPrimitive(stream),
                  -
                  1973 axes_(std::move(axes)),
                  -
                  1974 slice_size_(std::move(slice_size)) {}
                  +
                  1967
                  +
                  1968 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1969 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1970
                  +
                  1971 DEFINE_VMAP()
                  +
                  1972 DEFINE_GRADS()
                  +
                  1973 DEFINE_PRINT(DynamicSlice)
                  +
                  1974 bool is_equivalent(const Primitive& other) const override;
                  +
                  1975 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  +
                  +
                  1976 auto state() const {
                  +
                  1977 return std::make_pair(axes_, slice_size_);
                  +
                  1978 }
                  -
                  1975
                  -
                  1976 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1977 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1978
                  -
                  1979 DEFINE_VMAP()
                  -
                  1980 DEFINE_GRADS()
                  -
                  1981 DEFINE_PRINT(DynamicSlice)
                  -
                  1982 bool is_equivalent(const Primitive& other) const override;
                  -
                  1983 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  -
                  -
                  1984 auto state() const {
                  -
                  1985 return std::make_pair(axes_, slice_size_);
                  -
                  1986 }
                  +
                  1979
                  +
                  1980 private:
                  +
                  1981 std::vector<int> axes_;
                  +
                  1982 Shape slice_size_;
                  +
                  1983};
                  -
                  1987
                  -
                  1988 private:
                  -
                  1989 std::vector<int> axes_;
                  -
                  1990 Shape slice_size_;
                  -
                  1991};
                  +
                  1984
                  +
                  +
                  1985class DynamicSliceUpdate : public UnaryPrimitive {
                  +
                  1986 public:
                  +
                  +
                  1987 explicit DynamicSliceUpdate(Stream stream, std::vector<int> axes)
                  +
                  1988 : UnaryPrimitive(stream), axes_(std::move(axes)) {}
                  +
                  1989
                  +
                  1990 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  1991 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  1992
                  -
                  -
                  1993class DynamicSliceUpdate : public UnaryPrimitive {
                  -
                  1994 public:
                  -
                  -
                  1995 explicit DynamicSliceUpdate(Stream stream, std::vector<int> axes)
                  -
                  1996 : UnaryPrimitive(stream), axes_(std::move(axes)) {}
                  +
                  1993 DEFINE_VMAP()
                  +
                  1994 DEFINE_GRADS()
                  +
                  1995 DEFINE_PRINT(DynamicSliceUpdate)
                  +
                  1996 bool is_equivalent(const Primitive& other) const override;
                  +
                  1997 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  +
                  1998 auto state() const {
                  +
                  1999 return axes_;
                  +
                  2000 }
                  -
                  1997
                  -
                  1998 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  1999 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2000
                  -
                  2001 DEFINE_VMAP()
                  -
                  2002 DEFINE_GRADS()
                  -
                  2003 DEFINE_PRINT(DynamicSliceUpdate)
                  -
                  2004 bool is_equivalent(const Primitive& other) const override;
                  -
                  2005 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  -
                  2006 auto state() const {
                  -
                  2007 return axes_;
                  -
                  2008 }
                  +
                  2001
                  +
                  2002 private:
                  +
                  2003 std::vector<int> axes_;
                  +
                  2004};
                  -
                  2009
                  -
                  2010 private:
                  -
                  2011 std::vector<int> axes_;
                  -
                  2012};
                  +
                  2005
                  +
                  +
                  2006class Softmax : public UnaryPrimitive {
                  +
                  2007 public:
                  +
                  +
                  2008 explicit Softmax(Stream stream, bool precise)
                  +
                  2009 : UnaryPrimitive(stream), precise_(precise) {}
                  +
                  2010
                  +
                  2011 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2012 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  2013
                  -
                  -
                  2014class Softmax : public UnaryPrimitive {
                  -
                  2015 public:
                  -
                  -
                  2016 explicit Softmax(Stream stream, bool precise)
                  -
                  2017 : UnaryPrimitive(stream), precise_(precise) {}
                  -
                  +
                  2014 DEFINE_VMAP()
                  +
                  2015 DEFINE_GRADS()
                  +
                  2016 DEFINE_PRINT(Softmax)
                  +
                  2017 DEFINE_INPUT_OUTPUT_SHAPE()
                  2018
                  -
                  2019 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2020 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2021
                  -
                  2022 DEFINE_VMAP()
                  -
                  2023 DEFINE_GRADS()
                  -
                  2024 DEFINE_PRINT(Softmax)
                  -
                  2025 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  2026
                  -
                  2027 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  2028 auto state() const {
                  -
                  2029 return precise_;
                  -
                  2030 };
                  +
                  2019 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  2020 auto state() const {
                  +
                  2021 return precise_;
                  +
                  2022 };
                  -
                  2031
                  -
                  2032 private:
                  -
                  2033 bool precise_;
                  -
                  2034};
                  +
                  2023
                  +
                  2024 private:
                  +
                  2025 bool precise_;
                  +
                  2026};
                  +
                  2027
                  +
                  +
                  2028class Sort : public UnaryPrimitive {
                  +
                  2029 public:
                  +
                  +
                  2030 explicit Sort(Stream stream, int axis)
                  +
                  2031 : UnaryPrimitive(stream), axis_(axis) {}
                  +
                  +
                  2032
                  +
                  2033 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2034 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  2035
                  -
                  -
                  2036class Sort : public UnaryPrimitive {
                  -
                  2037 public:
                  -
                  -
                  2038 explicit Sort(Stream stream, int axis)
                  -
                  2039 : UnaryPrimitive(stream), axis_(axis) {}
                  +
                  2036 DEFINE_VMAP()
                  +
                  2037 DEFINE_GRADS()
                  +
                  2038 DEFINE_PRINT(Sort)
                  +
                  2039 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  2040 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  2041 auto state() const {
                  +
                  2042 return axis_;
                  +
                  2043 }
                  -
                  2040
                  -
                  2041 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2042 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2043
                  -
                  2044 DEFINE_VMAP()
                  -
                  2045 DEFINE_GRADS()
                  -
                  2046 DEFINE_PRINT(Sort)
                  -
                  2047 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  2048 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  2049 auto state() const {
                  -
                  2050 return axis_;
                  -
                  2051 }
                  +
                  2044
                  +
                  2045 private:
                  +
                  2046 int axis_;
                  +
                  2047};
                  -
                  2052
                  -
                  2053 private:
                  -
                  2054 int axis_;
                  -
                  2055};
                  +
                  2048
                  +
                  +
                  2049class Split : public Primitive {
                  +
                  2050 public:
                  +
                  +
                  2051 explicit Split(Stream stream, const Shape& indices, int axis)
                  +
                  2052 : Primitive(stream), indices_(indices), axis_(axis) {}
                  -
                  2056
                  -
                  -
                  2057class Split : public Primitive {
                  -
                  2058 public:
                  -
                  -
                  2059 explicit Split(Stream stream, const Shape& indices, int axis)
                  -
                  2060 : Primitive(stream), indices_(indices), axis_(axis) {}
                  +
                  2053
                  +
                  2054 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  +
                  2055 override;
                  +
                  2056 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  +
                  2057 override;
                  +
                  2058
                  +
                  2059 DEFINE_VMAP()
                  +
                  2060 DEFINE_GRADS()
                  +
                  2061 DEFINE_PRINT(Split)
                  +
                  2062 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  2063 std::pair<std::vector<int>, int> state() const {
                  +
                  2064 return {indices_, axis_};
                  +
                  2065 };
                  -
                  2061
                  -
                  2062 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  -
                  2063 override;
                  -
                  2064 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  -
                  2065 override;
                  2066
                  -
                  2067 DEFINE_VMAP()
                  -
                  2068 DEFINE_GRADS()
                  -
                  2069 DEFINE_PRINT(Split)
                  -
                  2070 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  2071 std::pair<std::vector<int>, int> state() const {
                  -
                  2072 return {indices_, axis_};
                  -
                  2073 };
                  +
                  2067 private:
                  +
                  2068 void eval(const std::vector<array>& inputs, std::vector<array>& outputs);
                  +
                  2069
                  +
                  2070 Shape indices_;
                  +
                  2071 int axis_;
                  +
                  2072};
                  -
                  2074
                  -
                  2075 private:
                  -
                  2076 void eval(const std::vector<array>& inputs, std::vector<array>& outputs);
                  +
                  2073
                  +
                  +
                  2074class Square : public UnaryPrimitive {
                  +
                  2075 public:
                  +
                  2076 explicit Square(Stream stream) : UnaryPrimitive(stream) {}
                  2077
                  -
                  2078 Shape indices_;
                  -
                  2079 int axis_;
                  -
                  2080};
                  +
                  2078 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2079 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2080
                  +
                  2081 DEFINE_VMAP()
                  +
                  2082 DEFINE_GRADS()
                  +
                  2083 DEFINE_PRINT(Square)
                  +
                  2084 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  2085 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  2086};
                  -
                  2081
                  -
                  -
                  2082class Square : public UnaryPrimitive {
                  -
                  2083 public:
                  -
                  2084 explicit Square(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  2085
                  -
                  2086 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2087 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2088
                  -
                  2089 DEFINE_VMAP()
                  -
                  2090 DEFINE_GRADS()
                  -
                  2091 DEFINE_PRINT(Square)
                  -
                  2092 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  2093 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  2094};
                  +
                  2087
                  +
                  +
                  2088class Sqrt : public UnaryPrimitive {
                  +
                  2089 public:
                  +
                  +
                  2090 explicit Sqrt(Stream stream, bool recip = false)
                  +
                  2091 : UnaryPrimitive(stream), recip_(recip) {}
                  +
                  2092
                  +
                  2093 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2094 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  2095
                  -
                  -
                  2096class Sqrt : public UnaryPrimitive {
                  -
                  2097 public:
                  -
                  -
                  2098 explicit Sqrt(Stream stream, bool recip = false)
                  -
                  2099 : UnaryPrimitive(stream), recip_(recip) {}
                  +
                  2096 DEFINE_VMAP()
                  +
                  2097 DEFINE_GRADS()
                  +
                  2098 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  2099 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  2100 auto state() const {
                  +
                  2101 return recip_;
                  +
                  2102 }
                  -
                  2100
                  -
                  2101 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2102 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  2103
                  -
                  2104 DEFINE_VMAP()
                  -
                  2105 DEFINE_GRADS()
                  -
                  2106 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  2107 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  2108 auto state() const {
                  -
                  2109 return recip_;
                  +
                  +
                  2104 void print(std::ostream& os) override {
                  +
                  2105 if (recip_) {
                  +
                  2106 os << "Rsqrt";
                  +
                  2107 } else {
                  +
                  2108 os << "Sqrt";
                  +
                  2109 }
                  2110 }
                  2111
                  -
                  -
                  2112 void print(std::ostream& os) override {
                  -
                  2113 if (recip_) {
                  -
                  2114 os << "Rsqrt";
                  -
                  2115 } else {
                  -
                  2116 os << "Sqrt";
                  -
                  2117 }
                  -
                  2118 }
                  +
                  2112 private:
                  +
                  2113 bool recip_;
                  +
                  2114};
                  +
                  2115
                  +
                  +
                  2116class StopGradient : public UnaryPrimitive {
                  +
                  2117 public:
                  +
                  2118 explicit StopGradient(Stream stream) : UnaryPrimitive(stream) {}
                  2119
                  -
                  2120 private:
                  -
                  2121 bool recip_;
                  -
                  2122};
                  -
                  -
                  2123
                  -
                  -
                  2124class StopGradient : public UnaryPrimitive {
                  -
                  2125 public:
                  -
                  2126 explicit StopGradient(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  2120 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2121 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2122
                  +
                  2123 DEFINE_VMAP()
                  +
                  2124 DEFINE_PRINT(StopGradient)
                  +
                  2125 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  2126 DEFINE_INPUT_OUTPUT_SHAPE()
                  2127
                  -
                  2128 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2129 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2130
                  -
                  2131 DEFINE_VMAP()
                  -
                  2132 DEFINE_PRINT(StopGradient)
                  -
                  2133 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  2134 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  2128 private:
                  +
                  2129 void eval(const std::vector<array>& inputs, array& out);
                  +
                  2130};
                  +
                  +
                  2131
                  +
                  +
                  2132class Subtract : public UnaryPrimitive {
                  +
                  2133 public:
                  +
                  2134 explicit Subtract(Stream stream) : UnaryPrimitive(stream) {}
                  2135
                  -
                  2136 private:
                  -
                  2137 void eval(const std::vector<array>& inputs, array& out);
                  -
                  2138};
                  +
                  2136 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2137 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2138
                  +
                  2139 DEFINE_VMAP()
                  +
                  2140 DEFINE_GRADS()
                  +
                  2141 DEFINE_PRINT(Subtract)
                  +
                  2142 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  2143 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  2144};
                  -
                  2139
                  -
                  -
                  2140class Subtract : public UnaryPrimitive {
                  -
                  2141 public:
                  -
                  2142 explicit Subtract(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  2143
                  -
                  2144 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2145 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2146
                  -
                  2147 DEFINE_VMAP()
                  -
                  2148 DEFINE_GRADS()
                  -
                  2149 DEFINE_PRINT(Subtract)
                  -
                  2150 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  2151 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  2152};
                  +
                  2145
                  +
                  +
                  2146class Squeeze : public UnaryPrimitive {
                  +
                  2147 public:
                  +
                  +
                  2148 explicit Squeeze(Stream stream, std::vector<int> axes)
                  +
                  2149 : UnaryPrimitive(stream), axes_(std::move(axes)) {}
                  +
                  2150
                  +
                  2151 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2152 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  2153
                  -
                  -
                  2154class Squeeze : public UnaryPrimitive {
                  -
                  2155 public:
                  -
                  -
                  2156 explicit Squeeze(Stream stream, std::vector<int> axes)
                  -
                  2157 : UnaryPrimitive(stream), axes_(std::move(axes)) {}
                  +
                  2154 DEFINE_VMAP()
                  +
                  2155 DEFINE_GRADS()
                  +
                  2156 DEFINE_PRINT(Squeeze)
                  +
                  2157
                  +
                  2158 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  +
                  2159 bool is_equivalent(const Primitive& other) const override;
                  +
                  2160
                  +
                  2161 static Shape output_shape(const array& input, const std::vector<int>& axes);
                  +
                  +
                  2162 auto state() const {
                  +
                  2163 return axes_;
                  +
                  2164 };
                  -
                  2158
                  -
                  2159 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2160 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2161
                  -
                  2162 DEFINE_VMAP()
                  -
                  2163 DEFINE_GRADS()
                  -
                  2164 DEFINE_PRINT(Squeeze)
                  2165
                  -
                  2166 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  -
                  2167 bool is_equivalent(const Primitive& other) const override;
                  -
                  2168
                  -
                  2169 static Shape output_shape(const array& input, const std::vector<int>& axes);
                  -
                  -
                  2170 auto state() const {
                  -
                  2171 return axes_;
                  -
                  2172 };
                  +
                  2166 private:
                  +
                  2167 void eval(const std::vector<array>& inputs, array& out);
                  +
                  2168 std::vector<int> axes_;
                  +
                  2169};
                  -
                  2173
                  -
                  2174 private:
                  -
                  2175 void eval(const std::vector<array>& inputs, array& out);
                  -
                  2176 std::vector<int> axes_;
                  -
                  2177};
                  +
                  2170
                  +
                  +
                  2171class Tan : public UnaryPrimitive {
                  +
                  2172 public:
                  +
                  2173 explicit Tan(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  2174
                  +
                  2175 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2176 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2177
                  +
                  2178 DEFINE_VMAP()
                  +
                  2179 DEFINE_GRADS()
                  +
                  2180 DEFINE_PRINT(Tan)
                  +
                  2181 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  2182 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  2183};
                  -
                  2178
                  -
                  -
                  2179class Tan : public UnaryPrimitive {
                  -
                  2180 public:
                  -
                  2181 explicit Tan(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  2182
                  -
                  2183 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2184 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2185
                  -
                  2186 DEFINE_VMAP()
                  -
                  2187 DEFINE_GRADS()
                  -
                  2188 DEFINE_PRINT(Tan)
                  -
                  2189 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  2190 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  2191};
                  +
                  2184
                  +
                  +
                  2185class Tanh : public UnaryPrimitive {
                  +
                  2186 public:
                  +
                  2187 explicit Tanh(Stream stream) : UnaryPrimitive(stream) {}
                  +
                  2188
                  +
                  2189 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2190 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2191
                  +
                  2192 DEFINE_VMAP()
                  +
                  2193 DEFINE_GRADS()
                  +
                  2194 DEFINE_PRINT(Tanh)
                  +
                  2195 DEFINE_DEFAULT_IS_EQUIVALENT()
                  +
                  2196 DEFINE_INPUT_OUTPUT_SHAPE()
                  +
                  2197};
                  -
                  2192
                  -
                  -
                  2193class Tanh : public UnaryPrimitive {
                  -
                  2194 public:
                  -
                  2195 explicit Tanh(Stream stream) : UnaryPrimitive(stream) {}
                  -
                  2196
                  -
                  2197 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2198 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2199
                  -
                  2200 DEFINE_VMAP()
                  -
                  2201 DEFINE_GRADS()
                  -
                  2202 DEFINE_PRINT(Tanh)
                  -
                  2203 DEFINE_DEFAULT_IS_EQUIVALENT()
                  -
                  2204 DEFINE_INPUT_OUTPUT_SHAPE()
                  -
                  2205};
                  +
                  2198
                  +
                  +
                  2199class Unflatten : public UnaryPrimitive {
                  +
                  2200 public:
                  +
                  +
                  2201 explicit Unflatten(Stream stream, int axis, Shape shape)
                  +
                  2202 : UnaryPrimitive(stream), axis_(axis), shape_(std::move(shape)) {}
                  +
                  2203
                  +
                  2204 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2205 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  2206
                  -
                  -
                  2207class Unflatten : public UnaryPrimitive {
                  -
                  2208 public:
                  -
                  -
                  2209 explicit Unflatten(Stream stream, int axis, Shape shape)
                  -
                  2210 : UnaryPrimitive(stream), axis_(axis), shape_(std::move(shape)) {}
                  +
                  2207 DEFINE_VMAP()
                  +
                  2208 DEFINE_GRADS()
                  +
                  2209 DEFINE_PRINT(Unflatten)
                  +
                  2210 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  +
                  2211 bool is_equivalent(const Primitive& other) const override;
                  +
                  2212
                  +
                  2213 static Shape output_shape(const array& input, int axis, const Shape& shape);
                  +
                  +
                  2214 auto state() const {
                  +
                  2215 return std::make_pair(axis_, shape_);
                  +
                  2216 }
                  -
                  2211
                  -
                  2212 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2213 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2214
                  -
                  2215 DEFINE_VMAP()
                  -
                  2216 DEFINE_GRADS()
                  -
                  2217 DEFINE_PRINT(Unflatten)
                  -
                  2218 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  -
                  2219 bool is_equivalent(const Primitive& other) const override;
                  -
                  2220
                  -
                  2221 static Shape output_shape(const array& input, int axis, const Shape& shape);
                  -
                  -
                  2222 auto state() const {
                  -
                  2223 return std::make_pair(axis_, shape_);
                  -
                  2224 }
                  +
                  2217
                  +
                  2218 private:
                  +
                  2219 int axis_;
                  +
                  2220 Shape shape_;
                  +
                  2221 void eval(const std::vector<array>& inputs, array& out);
                  +
                  2222};
                  -
                  2225
                  -
                  2226 private:
                  -
                  2227 int axis_;
                  -
                  2228 Shape shape_;
                  -
                  2229 void eval(const std::vector<array>& inputs, array& out);
                  -
                  2230};
                  +
                  2223
                  +
                  +
                  2224class View : public UnaryPrimitive {
                  +
                  2225 public:
                  +
                  +
                  2226 explicit View(Stream stream, Dtype dtype)
                  +
                  2227 : UnaryPrimitive(stream), dtype_(dtype) {}
                  +
                  2228
                  +
                  2229 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2230 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  2231
                  -
                  -
                  2232class View : public UnaryPrimitive {
                  -
                  2233 public:
                  -
                  -
                  2234 explicit View(Stream stream, Dtype dtype)
                  -
                  2235 : UnaryPrimitive(stream), dtype_(dtype) {}
                  +
                  2232 DEFINE_VMAP()
                  +
                  2233 void print(std::ostream& os) override;
                  +
                  2234 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  2235 auto state() const {
                  +
                  2236 return dtype_;
                  +
                  2237 }
                  -
                  2236
                  -
                  2237 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2238 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2239
                  -
                  2240 DEFINE_VMAP()
                  -
                  2241 void print(std::ostream& os) override;
                  -
                  2242 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  2243 auto state() const {
                  -
                  2244 return dtype_;
                  -
                  2245 }
                  +
                  2238
                  +
                  2239 private:
                  +
                  2240 Dtype dtype_;
                  +
                  2241};
                  -
                  2246
                  -
                  2247 private:
                  -
                  2248 Dtype dtype_;
                  -
                  2249};
                  +
                  2242
                  +
                  +
                  2243class Transpose : public UnaryPrimitive {
                  +
                  2244 public:
                  +
                  +
                  2245 explicit Transpose(Stream stream, const std::vector<int>& axes)
                  +
                  2246 : UnaryPrimitive(stream), axes_(axes) {}
                  +
                  2247
                  +
                  2248 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2249 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  2250
                  -
                  -
                  2251class Transpose : public UnaryPrimitive {
                  -
                  2252 public:
                  -
                  -
                  2253 explicit Transpose(Stream stream, const std::vector<int>& axes)
                  -
                  2254 : UnaryPrimitive(stream), axes_(axes) {}
                  +
                  2251 DEFINE_VMAP()
                  +
                  2252 DEFINE_GRADS()
                  +
                  2253 DEFINE_PRINT(Transpose)
                  +
                  2254 bool is_equivalent(const Primitive& other) const override;
                  +
                  2255 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  +
                  +
                  2256 std::vector<int> state() const {
                  +
                  2257 return axes_;
                  +
                  2258 };
                  -
                  2255
                  -
                  2256 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2257 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2258
                  -
                  2259 DEFINE_VMAP()
                  -
                  2260 DEFINE_GRADS()
                  -
                  2261 DEFINE_PRINT(Transpose)
                  -
                  2262 bool is_equivalent(const Primitive& other) const override;
                  -
                  2263 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  -
                  -
                  2264 std::vector<int> state() const {
                  -
                  2265 return axes_;
                  -
                  2266 };
                  +
                  2259
                  +
                  2260 private:
                  +
                  2261 std::vector<int> axes_;
                  +
                  2262
                  +
                  2263 void eval(const std::vector<array>& inputs, array& out);
                  +
                  2264};
                  -
                  2267
                  -
                  2268 private:
                  -
                  2269 std::vector<int> axes_;
                  +
                  2265
                  +
                  2266/* QR Factorization primitive. */
                  +
                  +
                  2267class QRF : public Primitive {
                  +
                  2268 public:
                  +
                  2269 explicit QRF(Stream stream) : Primitive(stream) {}
                  2270
                  -
                  2271 void eval(const std::vector<array>& inputs, array& out);
                  -
                  2272};
                  +
                  2271 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  +
                  2272 override;
                  +
                  2273 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  +
                  2274 override;
                  +
                  2275
                  +
                  2276 DEFINE_PRINT(QRF)
                  +
                  2277};
                  -
                  2273
                  -
                  2274/* QR Factorization primitive. */
                  -
                  -
                  2275class QRF : public Primitive {
                  -
                  2276 public:
                  -
                  2277 explicit QRF(Stream stream) : Primitive(stream) {}
                  2278
                  -
                  2279 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  -
                  2280 override;
                  -
                  2281 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  -
                  2282 override;
                  -
                  2283
                  -
                  2284 DEFINE_PRINT(QRF)
                  -
                  2285};
                  +
                  2279/* SVD primitive. */
                  +
                  +
                  2280class SVD : public Primitive {
                  +
                  2281 public:
                  +
                  +
                  2282 explicit SVD(Stream stream, bool compute_uv)
                  +
                  2283 : Primitive(stream), compute_uv_(compute_uv) {}
                  -
                  2286
                  -
                  2287/* SVD primitive. */
                  -
                  -
                  2288class SVD : public Primitive {
                  -
                  2289 public:
                  -
                  -
                  2290 explicit SVD(Stream stream, bool compute_uv)
                  -
                  2291 : Primitive(stream), compute_uv_(compute_uv) {}
                  +
                  2284
                  +
                  2285 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  +
                  2286 override;
                  +
                  2287 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  +
                  2288 override;
                  +
                  2289
                  +
                  2290 DEFINE_VMAP()
                  +
                  2291 DEFINE_PRINT(SVD)
                  +
                  +
                  2292 auto state() const {
                  +
                  2293 return compute_uv_;
                  +
                  2294 }
                  -
                  2292
                  -
                  2293 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  -
                  2294 override;
                  -
                  2295 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  -
                  2296 override;
                  -
                  2297
                  -
                  2298 DEFINE_VMAP()
                  -
                  2299 DEFINE_PRINT(SVD)
                  -
                  -
                  2300 auto state() const {
                  -
                  2301 return compute_uv_;
                  -
                  2302 }
                  +
                  2295
                  +
                  2296 private:
                  +
                  2297 bool compute_uv_;
                  +
                  2298};
                  -
                  2303
                  -
                  2304 private:
                  -
                  2305 bool compute_uv_;
                  -
                  2306};
                  +
                  2299
                  +
                  2300/* Matrix inversion primitive. */
                  +
                  +
                  2301class Inverse : public UnaryPrimitive {
                  +
                  2302 public:
                  +
                  +
                  2303 explicit Inverse(Stream stream, bool tri, bool upper)
                  +
                  2304 : UnaryPrimitive(stream), tri_(tri), upper_(upper) {}
                  -
                  2307
                  -
                  2308/* Matrix inversion primitive. */
                  -
                  -
                  2309class Inverse : public UnaryPrimitive {
                  -
                  2310 public:
                  +
                  2305
                  +
                  2306 void eval_cpu(const std::vector<array>& inputs, array& output) override;
                  +
                  2307 void eval_gpu(const std::vector<array>& inputs, array& output) override;
                  +
                  2308
                  +
                  2309 DEFINE_VMAP()
                  +
                  2310 DEFINE_PRINT(Inverse)
                  -
                  2311 explicit Inverse(Stream stream, bool tri, bool upper)
                  -
                  2312 : UnaryPrimitive(stream), tri_(tri), upper_(upper) {}
                  +
                  2311 auto state() const {
                  +
                  2312 return std::make_pair(tri_, upper_);
                  +
                  2313 }
                  -
                  2313
                  -
                  2314 void eval_cpu(const std::vector<array>& inputs, array& output) override;
                  -
                  2315 void eval_gpu(const std::vector<array>& inputs, array& output) override;
                  -
                  2316
                  -
                  2317 DEFINE_VMAP()
                  -
                  2318 DEFINE_PRINT(Inverse)
                  -
                  -
                  2319 auto state() const {
                  -
                  2320 return std::make_pair(tri_, upper_);
                  -
                  2321 }
                  +
                  2314
                  +
                  2315 private:
                  +
                  2316 bool tri_;
                  +
                  2317 bool upper_;
                  +
                  2318};
                  -
                  2322
                  -
                  2323 private:
                  -
                  2324 bool tri_;
                  -
                  2325 bool upper_;
                  -
                  2326};
                  +
                  2319
                  +
                  +
                  2320class Cholesky : public UnaryPrimitive {
                  +
                  2321 public:
                  +
                  +
                  2322 explicit Cholesky(Stream stream, bool upper)
                  +
                  2323 : UnaryPrimitive(stream), upper_(upper) {}
                  -
                  2327
                  -
                  -
                  2328class Cholesky : public UnaryPrimitive {
                  -
                  2329 public:
                  -
                  -
                  2330 explicit Cholesky(Stream stream, bool upper)
                  -
                  2331 : UnaryPrimitive(stream), upper_(upper) {}
                  +
                  2324
                  +
                  2325 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  +
                  2326 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  +
                  +
                  2327 auto state() const {
                  +
                  2328 return upper_;
                  +
                  2329 }
                  -
                  2332
                  -
                  2333 void eval_cpu(const std::vector<array>& inputs, array& out) override;
                  -
                  2334 void eval_gpu(const std::vector<array>& inputs, array& out) override;
                  -
                  -
                  2335 auto state() const {
                  -
                  2336 return upper_;
                  -
                  2337 }
                  +
                  2330
                  +
                  2331 DEFINE_VMAP()
                  +
                  2332 DEFINE_PRINT(Cholesky)
                  +
                  2333
                  +
                  2334 private:
                  +
                  2335 bool upper_;
                  +
                  2336};
                  -
                  2338
                  -
                  2339 DEFINE_VMAP()
                  -
                  2340 DEFINE_PRINT(Cholesky)
                  -
                  2341
                  -
                  2342 private:
                  -
                  2343 bool upper_;
                  -
                  2344};
                  +
                  2337
                  +
                  +
                  2338class Eigh : public Primitive {
                  +
                  2339 public:
                  +
                  +
                  2340 explicit Eigh(Stream stream, std::string uplo, bool compute_eigenvectors)
                  +
                  2341 : Primitive(stream),
                  +
                  2342 uplo_(std::move(uplo)),
                  +
                  2343 compute_eigenvectors_(compute_eigenvectors) {}
                  -
                  2345
                  -
                  -
                  2346class Eigh : public Primitive {
                  -
                  2347 public:
                  -
                  -
                  2348 explicit Eigh(Stream stream, std::string uplo, bool compute_eigenvectors)
                  -
                  2349 : Primitive(stream),
                  -
                  2350 uplo_(std::move(uplo)),
                  -
                  2351 compute_eigenvectors_(compute_eigenvectors) {}
                  +
                  2344 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  +
                  2345 override;
                  +
                  2346 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  +
                  2347 override;
                  +
                  2348
                  +
                  2349 DEFINE_VMAP()
                  +
                  2350 DEFINE_PRINT(Eigh)
                  +
                  2351
                  +
                  2352 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  +
                  2353
                  +
                  2354 bool is_equivalent(const Primitive& other) const override;
                  +
                  +
                  2355 auto state() const {
                  +
                  2356 return std::make_pair(uplo_, compute_eigenvectors_);
                  +
                  2357 }
                  -
                  2352 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  -
                  2353 override;
                  -
                  2354 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  -
                  2355 override;
                  -
                  2356
                  -
                  2357 DEFINE_VMAP()
                  -
                  2358 DEFINE_PRINT(Eigh)
                  -
                  2359
                  -
                  2360 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
                  -
                  2361
                  -
                  2362 bool is_equivalent(const Primitive& other) const override;
                  -
                  -
                  2363 auto state() const {
                  -
                  2364 return std::make_pair(uplo_, compute_eigenvectors_);
                  -
                  2365 }
                  +
                  2358
                  +
                  2359 private:
                  +
                  2360 std::string uplo_;
                  +
                  2361 bool compute_eigenvectors_;
                  +
                  2362};
                  -
                  2366
                  -
                  2367 private:
                  -
                  2368 std::string uplo_;
                  -
                  2369 bool compute_eigenvectors_;
                  -
                  2370};
                  +
                  2363
                  +
                  2364/* LU Factorization primitive. */
                  +
                  +
                  2365class LUF : public Primitive {
                  +
                  2366 public:
                  +
                  2367 explicit LUF(Stream stream) : Primitive(stream) {}
                  +
                  2368 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  +
                  2369 override;
                  +
                  2370 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  +
                  2371 override;
                  +
                  2372
                  +
                  2373 DEFINE_PRINT(LUF)
                  +
                  2374};
                  -
                  2371
                  -
                  2372/* LU Factorization primitive. */
                  -
                  -
                  2373class LUF : public Primitive {
                  -
                  2374 public:
                  -
                  2375 explicit LUF(Stream stream) : Primitive(stream) {}
                  -
                  2376 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  -
                  2377 override;
                  -
                  2378 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
                  -
                  2379 override;
                  -
                  2380
                  -
                  2381 DEFINE_PRINT(LUF)
                  -
                  2382};
                  -
                  -
                  2383
                  -
                  2384} // namespace mlx::core
                  +
                  2375
                  +
                  2376} // namespace mlx::core
                  mlx::core::Abs::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Abs::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  @@ -3030,8 +3022,8 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  mlx::core::Ceil::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Ceil::Ceil
                  Ceil(Stream stream)
                  Definition primitives.h:567
                  mlx::core::Cholesky::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Cholesky::state
                  auto state() const
                  Definition primitives.h:2335
                  -
                  mlx::core::Cholesky::Cholesky
                  Cholesky(Stream stream, bool upper)
                  Definition primitives.h:2330
                  +
                  mlx::core::Cholesky::state
                  auto state() const
                  Definition primitives.h:2327
                  +
                  mlx::core::Cholesky::Cholesky
                  Cholesky(Stream stream, bool upper)
                  Definition primitives.h:2322
                  mlx::core::Cholesky::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Compiled::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  mlx::core::Compiled::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  @@ -3088,11 +3080,11 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  mlx::core::DynamicSlice::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::DynamicSlice::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::DynamicSlice::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  -
                  mlx::core::DynamicSlice::DynamicSlice
                  DynamicSlice(Stream stream, std::vector< int > axes, Shape slice_size)
                  Definition primitives.h:1971
                  +
                  mlx::core::DynamicSlice::DynamicSlice
                  DynamicSlice(Stream stream, std::vector< int > axes, Shape slice_size)
                  Definition primitives.h:1963
                  mlx::core::DynamicSlice::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::DynamicSlice::state
                  auto state() const
                  Definition primitives.h:1984
                  -
                  mlx::core::DynamicSliceUpdate::state
                  auto state() const
                  Definition primitives.h:2006
                  -
                  mlx::core::DynamicSliceUpdate::DynamicSliceUpdate
                  DynamicSliceUpdate(Stream stream, std::vector< int > axes)
                  Definition primitives.h:1995
                  +
                  mlx::core::DynamicSlice::state
                  auto state() const
                  Definition primitives.h:1976
                  +
                  mlx::core::DynamicSliceUpdate::state
                  auto state() const
                  Definition primitives.h:1998
                  +
                  mlx::core::DynamicSliceUpdate::DynamicSliceUpdate
                  DynamicSliceUpdate(Stream stream, std::vector< int > axes)
                  Definition primitives.h:1987
                  mlx::core::DynamicSliceUpdate::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::DynamicSliceUpdate::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::DynamicSliceUpdate::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  @@ -3100,8 +3092,8 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  mlx::core::Eigh::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
                  mlx::core::Eigh::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
                  A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
                  mlx::core::Eigh::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  -
                  mlx::core::Eigh::state
                  auto state() const
                  Definition primitives.h:2363
                  -
                  mlx::core::Eigh::Eigh
                  Eigh(Stream stream, std::string uplo, bool compute_eigenvectors)
                  Definition primitives.h:2348
                  +
                  mlx::core::Eigh::state
                  auto state() const
                  Definition primitives.h:2355
                  +
                  mlx::core::Eigh::Eigh
                  Eigh(Stream stream, std::string uplo, bool compute_eigenvectors)
                  Definition primitives.h:2340
                  mlx::core::Equal::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:913
                  mlx::core::Equal::Equal
                  Equal(Stream stream, bool equal_nan=false)
                  Definition primitives.h:902
                  mlx::core::Equal::state
                  auto state() const
                  Definition primitives.h:920
                  @@ -3160,8 +3152,8 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  mlx::core::GatherMM::vjp
                  std::vector< array > vjp(const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs) override
                  The vector-Jacobian product.
                  mlx::core::GatherMM::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::GatherMM::GatherMM
                  GatherMM(Stream stream)
                  Definition primitives.h:501
                  -
                  mlx::core::GatherQMM::state
                  auto state() const
                  Definition primitives.h:1588
                  -
                  mlx::core::GatherQMM::GatherQMM
                  GatherQMM(Stream stream, int group_size, int bits, bool transpose)
                  Definition primitives.h:1575
                  +
                  mlx::core::GatherQMM::state
                  auto state() const
                  Definition primitives.h:1580
                  +
                  mlx::core::GatherQMM::GatherQMM
                  GatherQMM(Stream stream, int group_size, int bits, bool transpose)
                  Definition primitives.h:1567
                  mlx::core::GatherQMM::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::GatherQMM::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::GatherQMM::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  @@ -3180,10 +3172,10 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  mlx::core::Imag::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Imag::Imag
                  Imag(Stream stream)
                  Definition primitives.h:1184
                  mlx::core::Inverse::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &output) override
                  -
                  mlx::core::Inverse::Inverse
                  Inverse(Stream stream, bool tri, bool upper)
                  Definition primitives.h:2311
                  -
                  mlx::core::Inverse::state
                  auto state() const
                  Definition primitives.h:2319
                  +
                  mlx::core::Inverse::Inverse
                  Inverse(Stream stream, bool tri, bool upper)
                  Definition primitives.h:2303
                  +
                  mlx::core::Inverse::state
                  auto state() const
                  Definition primitives.h:2311
                  mlx::core::Inverse::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &output) override
                  -
                  mlx::core::LUF::LUF
                  LUF(Stream stream)
                  Definition primitives.h:2375
                  +
                  mlx::core::LUF::LUF
                  LUF(Stream stream)
                  Definition primitives.h:2367
                  mlx::core::LUF::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
                  A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
                  mlx::core::LUF::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
                  mlx::core::LessEqual::LessEqual
                  LessEqual(Stream stream)
                  Definition primitives.h:1212
                  @@ -3197,65 +3189,65 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  mlx::core::Load::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Log1p::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Log1p::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Log1p::Log1p
                  Log1p(Stream stream)
                  Definition primitives.h:1294
                  +
                  mlx::core::Log1p::Log1p
                  Log1p(Stream stream)
                  Definition primitives.h:1286
                  mlx::core::LogAddExp::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::LogAddExp::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::LogAddExp::LogAddExp
                  LogAddExp(Stream stream)
                  Definition primitives.h:1349
                  -
                  mlx::core::Log::Base
                  Base
                  Definition primitives.h:1257
                  -
                  mlx::core::Log::ten
                  @ ten
                  Definition primitives.h:1257
                  -
                  mlx::core::Log::two
                  @ two
                  Definition primitives.h:1257
                  -
                  mlx::core::Log::e
                  @ e
                  Definition primitives.h:1257
                  -
                  mlx::core::Log::Log
                  Log(Stream stream, Base base)
                  Definition primitives.h:1259
                  -
                  mlx::core::Log::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:1274
                  -
                  mlx::core::Log::state
                  Base state() const
                  Definition primitives.h:1270
                  +
                  mlx::core::LogAddExp::LogAddExp
                  LogAddExp(Stream stream)
                  Definition primitives.h:1341
                  +
                  mlx::core::Log::Base
                  Base
                  Definition primitives.h:1249
                  +
                  mlx::core::Log::ten
                  @ ten
                  Definition primitives.h:1249
                  +
                  mlx::core::Log::two
                  @ two
                  Definition primitives.h:1249
                  +
                  mlx::core::Log::e
                  @ e
                  Definition primitives.h:1249
                  +
                  mlx::core::Log::Log
                  Log(Stream stream, Base base)
                  Definition primitives.h:1251
                  +
                  mlx::core::Log::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:1266
                  +
                  mlx::core::Log::state
                  Base state() const
                  Definition primitives.h:1262
                  mlx::core::Log::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Log::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::LogicalAnd::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::LogicalAnd::LogicalAnd
                  LogicalAnd(Stream stream)
                  Definition primitives.h:1321
                  +
                  mlx::core::LogicalAnd::LogicalAnd
                  LogicalAnd(Stream stream)
                  Definition primitives.h:1313
                  mlx::core::LogicalAnd::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::LogicalNot::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::LogicalNot::LogicalNot
                  LogicalNot(Stream stream)
                  Definition primitives.h:1307
                  +
                  mlx::core::LogicalNot::LogicalNot
                  LogicalNot(Stream stream)
                  Definition primitives.h:1299
                  mlx::core::LogicalNot::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::LogicalOr::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::LogicalOr::LogicalOr
                  LogicalOr(Stream stream)
                  Definition primitives.h:1335
                  +
                  mlx::core::LogicalOr::LogicalOr
                  LogicalOr(Stream stream)
                  Definition primitives.h:1327
                  mlx::core::LogicalOr::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Matmul::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Matmul::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Matmul::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  -
                  mlx::core::Matmul::Matmul
                  Matmul(Stream stream)
                  Definition primitives.h:1363
                  -
                  mlx::core::Maximum::Maximum
                  Maximum(Stream stream)
                  Definition primitives.h:1377
                  +
                  mlx::core::Matmul::Matmul
                  Matmul(Stream stream)
                  Definition primitives.h:1355
                  +
                  mlx::core::Maximum::Maximum
                  Maximum(Stream stream)
                  Definition primitives.h:1369
                  mlx::core::Maximum::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Maximum::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Minimum::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Minimum::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Minimum::Minimum
                  Minimum(Stream stream)
                  Definition primitives.h:1391
                  +
                  mlx::core::Minimum::Minimum
                  Minimum(Stream stream)
                  Definition primitives.h:1383
                  mlx::core::Multiply::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Multiply::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Multiply::Multiply
                  Multiply(Stream stream)
                  Definition primitives.h:1405
                  +
                  mlx::core::Multiply::Multiply
                  Multiply(Stream stream)
                  Definition primitives.h:1397
                  mlx::core::Negative::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Negative::Negative
                  Negative(Stream stream)
                  Definition primitives.h:1419
                  +
                  mlx::core::Negative::Negative
                  Negative(Stream stream)
                  Definition primitives.h:1411
                  mlx::core::Negative::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::NotEqual::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::NotEqual::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::NotEqual::NotEqual
                  NotEqual(Stream stream)
                  Definition primitives.h:1433
                  +
                  mlx::core::NotEqual::NotEqual
                  NotEqual(Stream stream)
                  Definition primitives.h:1425
                  mlx::core::NumberOfElements::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::NumberOfElements::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  Definition primitives.h:1463
                  -
                  mlx::core::NumberOfElements::NumberOfElements
                  NumberOfElements(Stream stream, std::vector< int > axes, bool inverted, Dtype dtype)
                  Definition primitives.h:1447
                  +
                  mlx::core::NumberOfElements::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  Definition primitives.h:1455
                  +
                  mlx::core::NumberOfElements::NumberOfElements
                  NumberOfElements(Stream stream, std::vector< int > axes, bool inverted, Dtype dtype)
                  Definition primitives.h:1439
                  mlx::core::NumberOfElements::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::NumberOfElements::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  -
                  mlx::core::NumberOfElements::state
                  std::tuple< std::vector< int >, bool, Dtype > state() const
                  Definition primitives.h:1466
                  -
                  mlx::core::Pad::state
                  auto state() const
                  Definition primitives.h:1497
                  -
                  mlx::core::Pad::Pad
                  Pad(Stream stream, const std::vector< int > &axes, const Shape &low_pad_size, const Shape &high_pad_size)
                  Definition primitives.h:1480
                  +
                  mlx::core::NumberOfElements::state
                  std::tuple< std::vector< int >, bool, Dtype > state() const
                  Definition primitives.h:1458
                  +
                  mlx::core::Pad::state
                  auto state() const
                  Definition primitives.h:1489
                  +
                  mlx::core::Pad::Pad
                  Pad(Stream stream, const std::vector< int > &axes, const Shape &low_pad_size, const Shape &high_pad_size)
                  Definition primitives.h:1472
                  mlx::core::Pad::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::Pad::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Pad::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Partition::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Partition::Partition
                  Partition(Stream stream, int kth, int axis)
                  Definition primitives.h:1509
                  +
                  mlx::core::Partition::Partition
                  Partition(Stream stream, int kth, int axis)
                  Definition primitives.h:1501
                  mlx::core::Partition::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Partition::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  -
                  mlx::core::Partition::state
                  auto state() const
                  Definition primitives.h:1520
                  +
                  mlx::core::Partition::state
                  auto state() const
                  Definition primitives.h:1512
                  mlx::core::Power::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Power::Power
                  Power(Stream stream)
                  Definition primitives.h:1531
                  +
                  mlx::core::Power::Power
                  Power(Stream stream)
                  Definition primitives.h:1523
                  mlx::core::Power::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Primitive
                  Definition primitives.h:48
                  mlx::core::Primitive::eval_cpu
                  virtual void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs)=0
                  A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
                  @@ -3274,139 +3266,139 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  mlx::core::Primitive::eval_gpu
                  virtual void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs)=0
                  mlx::core::Primitive::print
                  virtual void print(std::ostream &os)=0
                  Print the primitive.
                  mlx::core::Primitive::Primitive
                  Primitive(Stream stream)
                  Definition primitives.h:50
                  -
                  mlx::core::QRF::QRF
                  QRF(Stream stream)
                  Definition primitives.h:2277
                  +
                  mlx::core::QRF::QRF
                  QRF(Stream stream)
                  Definition primitives.h:2269
                  mlx::core::QRF::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
                  A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
                  mlx::core::QRF::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
                  mlx::core::QuantizedMatmul::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::QuantizedMatmul::QuantizedMatmul
                  QuantizedMatmul(Stream stream, int group_size, int bits, bool transpose)
                  Definition primitives.h:1545
                  +
                  mlx::core::QuantizedMatmul::QuantizedMatmul
                  QuantizedMatmul(Stream stream, int group_size, int bits, bool transpose)
                  Definition primitives.h:1537
                  mlx::core::QuantizedMatmul::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  mlx::core::QuantizedMatmul::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::QuantizedMatmul::state
                  auto state() const
                  Definition primitives.h:1563
                  +
                  mlx::core::QuantizedMatmul::state
                  auto state() const
                  Definition primitives.h:1555
                  mlx::core::QuantizedMatmul::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::RandomBits::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::RandomBits::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::RandomBits::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  -
                  mlx::core::RandomBits::state
                  std::pair< std::vector< int >, int > state() const
                  Definition primitives.h:1609
                  -
                  mlx::core::RandomBits::RandomBits
                  RandomBits(Stream stream, const Shape &shape, int width)
                  Definition primitives.h:1600
                  +
                  mlx::core::RandomBits::state
                  std::pair< std::vector< int >, int > state() const
                  Definition primitives.h:1601
                  +
                  mlx::core::RandomBits::RandomBits
                  RandomBits(Stream stream, const Shape &shape, int width)
                  Definition primitives.h:1592
                  mlx::core::Real::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Real::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Real::Real
                  Real(Stream stream)
                  Definition primitives.h:1620
                  -
                  mlx::core::Reduce::Reduce
                  Reduce(Stream stream, ReduceType reduce_type, const std::vector< int > &axes)
                  Definition primitives.h:1658
                  -
                  mlx::core::Reduce::ReduceType
                  ReduceType
                  Definition primitives.h:1656
                  -
                  mlx::core::Reduce::Min
                  @ Min
                  Definition primitives.h:1656
                  -
                  mlx::core::Reduce::Or
                  @ Or
                  Definition primitives.h:1656
                  -
                  mlx::core::Reduce::Max
                  @ Max
                  Definition primitives.h:1656
                  -
                  mlx::core::Reduce::And
                  @ And
                  Definition primitives.h:1656
                  -
                  mlx::core::Reduce::Sum
                  @ Sum
                  Definition primitives.h:1656
                  -
                  mlx::core::Reduce::Prod
                  @ Prod
                  Definition primitives.h:1656
                  -
                  mlx::core::Reduce::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:1677
                  +
                  mlx::core::Real::Real
                  Real(Stream stream)
                  Definition primitives.h:1612
                  +
                  mlx::core::Reduce::Reduce
                  Reduce(Stream stream, ReduceType reduce_type, const std::vector< int > &axes)
                  Definition primitives.h:1650
                  +
                  mlx::core::Reduce::ReduceType
                  ReduceType
                  Definition primitives.h:1648
                  +
                  mlx::core::Reduce::Min
                  @ Min
                  Definition primitives.h:1648
                  +
                  mlx::core::Reduce::Or
                  @ Or
                  Definition primitives.h:1648
                  +
                  mlx::core::Reduce::Max
                  @ Max
                  Definition primitives.h:1648
                  +
                  mlx::core::Reduce::And
                  @ And
                  Definition primitives.h:1648
                  +
                  mlx::core::Reduce::Sum
                  @ Sum
                  Definition primitives.h:1648
                  +
                  mlx::core::Reduce::Prod
                  @ Prod
                  Definition primitives.h:1648
                  +
                  mlx::core::Reduce::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:1669
                  mlx::core::Reduce::vjp
                  std::vector< array > vjp(const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs) override
                  The vector-Jacobian product.
                  mlx::core::Reduce::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  mlx::core::Reduce::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::Reduce::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Reduce::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Reduce::state
                  std::pair< ReduceType, std::vector< int > > state() const
                  Definition primitives.h:1700
                  +
                  mlx::core::Reduce::state
                  std::pair< ReduceType, std::vector< int > > state() const
                  Definition primitives.h:1692
                  mlx::core::Remainder::Remainder
                  Remainder(Stream stream)
                  Definition primitives.h:888
                  mlx::core::Remainder::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Remainder::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Reshape::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Reshape::output_shape
                  static Shape output_shape(const array &input, Shape shape)
                  mlx::core::Reshape::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Reshape::Reshape
                  Reshape(Stream stream, const Shape &shape)
                  Definition primitives.h:1634
                  -
                  mlx::core::Reshape::state
                  std::vector< int > state() const
                  Definition primitives.h:1644
                  +
                  mlx::core::Reshape::Reshape
                  Reshape(Stream stream, const Shape &shape)
                  Definition primitives.h:1626
                  +
                  mlx::core::Reshape::state
                  std::vector< int > state() const
                  Definition primitives.h:1636
                  mlx::core::Reshape::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::Reshape::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  -
                  mlx::core::Round::Round
                  Round(Stream stream)
                  Definition primitives.h:1711
                  +
                  mlx::core::Round::Round
                  Round(Stream stream)
                  Definition primitives.h:1703
                  mlx::core::Round::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Round::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::SVD::SVD
                  SVD(Stream stream, bool compute_uv)
                  Definition primitives.h:2290
                  +
                  mlx::core::SVD::SVD
                  SVD(Stream stream, bool compute_uv)
                  Definition primitives.h:2282
                  mlx::core::SVD::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
                  A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
                  mlx::core::SVD::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
                  -
                  mlx::core::SVD::state
                  auto state() const
                  Definition primitives.h:2300
                  +
                  mlx::core::SVD::state
                  auto state() const
                  Definition primitives.h:2292
                  mlx::core::Scan::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Scan::ReduceType
                  ReduceType
                  Definition primitives.h:1725
                  -
                  mlx::core::Scan::Prod
                  @ Prod
                  Definition primitives.h:1725
                  -
                  mlx::core::Scan::Min
                  @ Min
                  Definition primitives.h:1725
                  -
                  mlx::core::Scan::Max
                  @ Max
                  Definition primitives.h:1725
                  -
                  mlx::core::Scan::Sum
                  @ Sum
                  Definition primitives.h:1725
                  +
                  mlx::core::Scan::ReduceType
                  ReduceType
                  Definition primitives.h:1717
                  +
                  mlx::core::Scan::Prod
                  @ Prod
                  Definition primitives.h:1717
                  +
                  mlx::core::Scan::Min
                  @ Min
                  Definition primitives.h:1717
                  +
                  mlx::core::Scan::Max
                  @ Max
                  Definition primitives.h:1717
                  +
                  mlx::core::Scan::Sum
                  @ Sum
                  Definition primitives.h:1717
                  mlx::core::Scan::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  -
                  mlx::core::Scan::state
                  auto state() const
                  Definition primitives.h:1763
                  -
                  mlx::core::Scan::Scan
                  Scan(Stream stream, ReduceType reduce_type, int axis, bool reverse, bool inclusive)
                  Definition primitives.h:1727
                  -
                  mlx::core::Scan::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:1745
                  +
                  mlx::core::Scan::state
                  auto state() const
                  Definition primitives.h:1755
                  +
                  mlx::core::Scan::Scan
                  Scan(Stream stream, ReduceType reduce_type, int axis, bool reverse, bool inclusive)
                  Definition primitives.h:1719
                  +
                  mlx::core::Scan::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:1737
                  mlx::core::Scan::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::ScatterAxis::state
                  std::pair< ReduceType, int > state() const
                  Definition primitives.h:1845
                  -
                  mlx::core::ScatterAxis::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:1832
                  +
                  mlx::core::ScatterAxis::state
                  std::pair< ReduceType, int > state() const
                  Definition primitives.h:1837
                  +
                  mlx::core::ScatterAxis::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:1824
                  mlx::core::ScatterAxis::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::ScatterAxis::ScatterAxis
                  ScatterAxis(Stream stream, ReduceType reduce_type, int axis)
                  Definition primitives.h:1823
                  -
                  mlx::core::ScatterAxis::ReduceType
                  ReduceType
                  Definition primitives.h:1821
                  -
                  mlx::core::ScatterAxis::Sum
                  @ Sum
                  Definition primitives.h:1821
                  -
                  mlx::core::ScatterAxis::None
                  @ None
                  Definition primitives.h:1821
                  +
                  mlx::core::ScatterAxis::ScatterAxis
                  ScatterAxis(Stream stream, ReduceType reduce_type, int axis)
                  Definition primitives.h:1815
                  +
                  mlx::core::ScatterAxis::ReduceType
                  ReduceType
                  Definition primitives.h:1813
                  +
                  mlx::core::ScatterAxis::Sum
                  @ Sum
                  Definition primitives.h:1813
                  +
                  mlx::core::ScatterAxis::None
                  @ None
                  Definition primitives.h:1813
                  mlx::core::ScatterAxis::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::ScatterAxis::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::ScatterAxis::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  mlx::core::Scatter::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  -
                  mlx::core::Scatter::state
                  std::pair< ReduceType, std::vector< int > > state() const
                  Definition primitives.h:1810
                  -
                  mlx::core::Scatter::ReduceType
                  ReduceType
                  Definition primitives.h:1776
                  -
                  mlx::core::Scatter::Sum
                  @ Sum
                  Definition primitives.h:1776
                  -
                  mlx::core::Scatter::Max
                  @ Max
                  Definition primitives.h:1776
                  -
                  mlx::core::Scatter::Prod
                  @ Prod
                  Definition primitives.h:1776
                  -
                  mlx::core::Scatter::None
                  @ None
                  Definition primitives.h:1776
                  -
                  mlx::core::Scatter::Min
                  @ Min
                  Definition primitives.h:1776
                  +
                  mlx::core::Scatter::state
                  std::pair< ReduceType, std::vector< int > > state() const
                  Definition primitives.h:1802
                  +
                  mlx::core::Scatter::ReduceType
                  ReduceType
                  Definition primitives.h:1768
                  +
                  mlx::core::Scatter::Sum
                  @ Sum
                  Definition primitives.h:1768
                  +
                  mlx::core::Scatter::Max
                  @ Max
                  Definition primitives.h:1768
                  +
                  mlx::core::Scatter::Prod
                  @ Prod
                  Definition primitives.h:1768
                  +
                  mlx::core::Scatter::None
                  @ None
                  Definition primitives.h:1768
                  +
                  mlx::core::Scatter::Min
                  @ Min
                  Definition primitives.h:1768
                  mlx::core::Scatter::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Scatter::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:1790
                  +
                  mlx::core::Scatter::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:1782
                  mlx::core::Scatter::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Scatter::Scatter
                  Scatter(Stream stream, ReduceType reduce_type, const std::vector< int > &axes)
                  Definition primitives.h:1778
                  +
                  mlx::core::Scatter::Scatter
                  Scatter(Stream stream, ReduceType reduce_type, const std::vector< int > &axes)
                  Definition primitives.h:1770
                  mlx::core::Select::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Select::Select
                  Select(Stream stream)
                  Definition primitives.h:874
                  mlx::core::Select::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Sigmoid::Sigmoid
                  Sigmoid(Stream stream)
                  Definition primitives.h:1856
                  +
                  mlx::core::Sigmoid::Sigmoid
                  Sigmoid(Stream stream)
                  Definition primitives.h:1848
                  mlx::core::Sigmoid::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Sigmoid::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Sign::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Sign::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Sign::Sign
                  Sign(Stream stream)
                  Definition primitives.h:1870
                  -
                  mlx::core::Sin::Sin
                  Sin(Stream stream)
                  Definition primitives.h:1884
                  +
                  mlx::core::Sign::Sign
                  Sign(Stream stream)
                  Definition primitives.h:1862
                  +
                  mlx::core::Sin::Sin
                  Sin(Stream stream)
                  Definition primitives.h:1876
                  mlx::core::Sin::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Sin::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Sinh::Sinh
                  Sinh(Stream stream)
                  Definition primitives.h:1898
                  +
                  mlx::core::Sinh::Sinh
                  Sinh(Stream stream)
                  Definition primitives.h:1890
                  mlx::core::Sinh::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Sinh::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Slice::state
                  auto state() const
                  Definition primitives.h:1929
                  -
                  mlx::core::Slice::Slice
                  Slice(Stream stream, const Shape &start_indices, const Shape &end_indices, const Shape &strides)
                  Definition primitives.h:1912
                  +
                  mlx::core::Slice::state
                  auto state() const
                  Definition primitives.h:1921
                  +
                  mlx::core::Slice::Slice
                  Slice(Stream stream, const Shape &start_indices, const Shape &end_indices, const Shape &strides)
                  Definition primitives.h:1904
                  mlx::core::Slice::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::Slice::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Slice::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::SliceUpdate::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  -
                  mlx::core::SliceUpdate::SliceUpdate
                  SliceUpdate(Stream stream, const Shape &start_indices, const Shape &end_indices, const Shape &strides)
                  Definition primitives.h:1941
                  +
                  mlx::core::SliceUpdate::SliceUpdate
                  SliceUpdate(Stream stream, const Shape &start_indices, const Shape &end_indices, const Shape &strides)
                  Definition primitives.h:1933
                  mlx::core::SliceUpdate::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::SliceUpdate::state
                  auto state() const
                  Definition primitives.h:1959
                  +
                  mlx::core::SliceUpdate::state
                  auto state() const
                  Definition primitives.h:1951
                  mlx::core::SliceUpdate::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Softmax::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Softmax::Softmax
                  Softmax(Stream stream, bool precise)
                  Definition primitives.h:2016
                  +
                  mlx::core::Softmax::Softmax
                  Softmax(Stream stream, bool precise)
                  Definition primitives.h:2008
                  mlx::core::Softmax::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::Softmax::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Softmax::state
                  auto state() const
                  Definition primitives.h:2028
                  +
                  mlx::core::Softmax::state
                  auto state() const
                  Definition primitives.h:2020
                  mlx::core::Sort::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Sort::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Sort::state
                  auto state() const
                  Definition primitives.h:2049
                  -
                  mlx::core::Sort::Sort
                  Sort(Stream stream, int axis)
                  Definition primitives.h:2038
                  +
                  mlx::core::Sort::state
                  auto state() const
                  Definition primitives.h:2041
                  +
                  mlx::core::Sort::Sort
                  Sort(Stream stream, int axis)
                  Definition primitives.h:2030
                  mlx::core::Sort::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::Split::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
                  -
                  mlx::core::Split::state
                  std::pair< std::vector< int >, int > state() const
                  Definition primitives.h:2071
                  -
                  mlx::core::Split::Split
                  Split(Stream stream, const Shape &indices, int axis)
                  Definition primitives.h:2059
                  +
                  mlx::core::Split::state
                  std::pair< std::vector< int >, int > state() const
                  Definition primitives.h:2063
                  +
                  mlx::core::Split::Split
                  Split(Stream stream, const Shape &indices, int axis)
                  Definition primitives.h:2051
                  mlx::core::Split::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::Split::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
                  A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
                  -
                  mlx::core::Sqrt::state
                  auto state() const
                  Definition primitives.h:2108
                  +
                  mlx::core::Sqrt::state
                  auto state() const
                  Definition primitives.h:2100
                  mlx::core::Sqrt::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Sqrt::Sqrt
                  Sqrt(Stream stream, bool recip=false)
                  Definition primitives.h:2098
                  +
                  mlx::core::Sqrt::Sqrt
                  Sqrt(Stream stream, bool recip=false)
                  Definition primitives.h:2090
                  mlx::core::Sqrt::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Sqrt::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:2112
                  +
                  mlx::core::Sqrt::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  Definition primitives.h:2104
                  mlx::core::Sqrt::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::Square::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Square::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Square::Square
                  Square(Stream stream)
                  Definition primitives.h:2084
                  -
                  mlx::core::Squeeze::Squeeze
                  Squeeze(Stream stream, std::vector< int > axes)
                  Definition primitives.h:2156
                  -
                  mlx::core::Squeeze::state
                  auto state() const
                  Definition primitives.h:2170
                  +
                  mlx::core::Square::Square
                  Square(Stream stream)
                  Definition primitives.h:2076
                  +
                  mlx::core::Squeeze::Squeeze
                  Squeeze(Stream stream, std::vector< int > axes)
                  Definition primitives.h:2148
                  +
                  mlx::core::Squeeze::state
                  auto state() const
                  Definition primitives.h:2162
                  mlx::core::Squeeze::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::Squeeze::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Squeeze::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  @@ -3414,19 +3406,19 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  mlx::core::Squeeze::output_shape
                  static Shape output_shape(const array &input, const std::vector< int > &axes)
                  mlx::core::StopGradient::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::StopGradient::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::StopGradient::StopGradient
                  StopGradient(Stream stream)
                  Definition primitives.h:2126
                  +
                  mlx::core::StopGradient::StopGradient
                  StopGradient(Stream stream)
                  Definition primitives.h:2118
                  mlx::core::Subtract::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Subtract::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Subtract::Subtract
                  Subtract(Stream stream)
                  Definition primitives.h:2142
                  -
                  mlx::core::Tan::Tan
                  Tan(Stream stream)
                  Definition primitives.h:2181
                  +
                  mlx::core::Subtract::Subtract
                  Subtract(Stream stream)
                  Definition primitives.h:2134
                  +
                  mlx::core::Tan::Tan
                  Tan(Stream stream)
                  Definition primitives.h:2173
                  mlx::core::Tan::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Tan::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Tanh::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Tanh::Tanh
                  Tanh(Stream stream)
                  Definition primitives.h:2195
                  +
                  mlx::core::Tanh::Tanh
                  Tanh(Stream stream)
                  Definition primitives.h:2187
                  mlx::core::Tanh::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Transpose::Transpose
                  Transpose(Stream stream, const std::vector< int > &axes)
                  Definition primitives.h:2253
                  +
                  mlx::core::Transpose::Transpose
                  Transpose(Stream stream, const std::vector< int > &axes)
                  Definition primitives.h:2245
                  mlx::core::Transpose::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Transpose::state
                  std::vector< int > state() const
                  Definition primitives.h:2264
                  +
                  mlx::core::Transpose::state
                  std::vector< int > state() const
                  Definition primitives.h:2256
                  mlx::core::Transpose::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Transpose::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::Transpose::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  @@ -3442,17 +3434,17 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  mlx::core::UnaryPrimitive::operator=
                  UnaryPrimitive & operator=(UnaryPrimitive &&other)=delete
                  mlx::core::UnaryPrimitive::~UnaryPrimitive
                  virtual ~UnaryPrimitive()=default
                  mlx::core::Unflatten::output_shapes
                  std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
                  Get the output shapes of the primitive.
                  -
                  mlx::core::Unflatten::Unflatten
                  Unflatten(Stream stream, int axis, Shape shape)
                  Definition primitives.h:2209
                  +
                  mlx::core::Unflatten::Unflatten
                  Unflatten(Stream stream, int axis, Shape shape)
                  Definition primitives.h:2201
                  mlx::core::Unflatten::output_shape
                  static Shape output_shape(const array &input, int axis, const Shape &shape)
                  mlx::core::Unflatten::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::Unflatten::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  mlx::core::Unflatten::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::Unflatten::state
                  auto state() const
                  Definition primitives.h:2222
                  +
                  mlx::core::Unflatten::state
                  auto state() const
                  Definition primitives.h:2214
                  mlx::core::View::eval_cpu
                  void eval_cpu(const std::vector< array > &inputs, array &out) override
                  -
                  mlx::core::View::state
                  auto state() const
                  Definition primitives.h:2243
                  +
                  mlx::core::View::state
                  auto state() const
                  Definition primitives.h:2235
                  mlx::core::View::print
                  void print(std::ostream &os) override
                  Print the primitive.
                  mlx::core::View::is_equivalent
                  bool is_equivalent(const Primitive &other) const override
                  Equivalence check defaults to false unless overridden by the primitive.
                  -
                  mlx::core::View::View
                  View(Stream stream, Dtype dtype)
                  Definition primitives.h:2234
                  +
                  mlx::core::View::View
                  View(Stream stream, Dtype dtype)
                  Definition primitives.h:2226
                  mlx::core::View::eval_gpu
                  void eval_gpu(const std::vector< array > &inputs, array &out) override
                  mlx::core::array
                  Definition array.h:24
                  @@ -3460,10 +3452,9 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  mlx::core::tri
                  array tri(int n, int m, int k, Dtype type, StreamOrDevice s={})
                  mlx::core::transpose
                  array transpose(const array &a, std::vector< int > axes, StreamOrDevice s={})
                  Permutes the dimensions according to the given axes.
                  mlx::core::real
                  array real(const array &a, StreamOrDevice s={})
                  - +
                  mlx::core
                  Definition allocator.h:7
                  mlx::core::Shape
                  std::vector< ShapeElem > Shape
                  Definition array.h:21
                  -
                  mlx::core::new_stream
                  Stream new_stream(Device d)
                  Make a new stream on the given device.
                  mlx::core::Strides
                  std::vector< int64_t > Strides
                  Definition array.h:22
                  mlx::core::eval
                  void eval(std::vector< array > outputs)
                  DEFINE_DEFAULT_IS_EQUIVALENT
                  #define DEFINE_DEFAULT_IS_EQUIVALENT()
                  Definition primitives.h:34
                  @@ -3473,8 +3464,6 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
                  DEFINE_VMAP
                  #define DEFINE_VMAP()
                  Definition primitives.h:12
                  mlx::core::Device
                  Definition device.h:7
                  -
                  mlx::core::Device::gpu
                  static constexpr DeviceType gpu
                  Definition device.h:14
                  -
                  mlx::core::Device::cpu
                  static constexpr DeviceType cpu
                  Definition device.h:13
                  mlx::core::Dtype
                  Definition dtype.h:13
                  mlx::core::Stream
                  Definition stream.h:9
                  mlx::core::Stream::device
                  Device device
                  Definition stream.h:11
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.Device.html b/docs/build/html/python/_autosummary/mlx.core.Device.html index 52a2cc31b..962a35558 100644 --- a/docs/build/html/python/_autosummary/mlx.core.Device.html +++ b/docs/build/html/python/_autosummary/mlx.core.Device.html @@ -8,7 +8,7 @@ - mlx.core.Device — MLX 0.23.2 documentation + mlx.core.Device — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.Dtype.html b/docs/build/html/python/_autosummary/mlx.core.Dtype.html index a6f943e58..cd11b892f 100644 --- a/docs/build/html/python/_autosummary/mlx.core.Dtype.html +++ b/docs/build/html/python/_autosummary/mlx.core.Dtype.html @@ -8,7 +8,7 @@ - mlx.core.Dtype — MLX 0.23.2 documentation + mlx.core.Dtype — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.DtypeCategory.html b/docs/build/html/python/_autosummary/mlx.core.DtypeCategory.html index 1a4aee48f..7e50f8359 100644 --- a/docs/build/html/python/_autosummary/mlx.core.DtypeCategory.html +++ b/docs/build/html/python/_autosummary/mlx.core.DtypeCategory.html @@ -8,7 +8,7 @@ - mlx.core.DtypeCategory — MLX 0.23.2 documentation + mlx.core.DtypeCategory — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.abs.html b/docs/build/html/python/_autosummary/mlx.core.abs.html index 8b962c641..e8bb1a158 100644 --- a/docs/build/html/python/_autosummary/mlx.core.abs.html +++ b/docs/build/html/python/_autosummary/mlx.core.abs.html @@ -8,7 +8,7 @@ - mlx.core.abs — MLX 0.23.2 documentation + mlx.core.abs — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.add.html b/docs/build/html/python/_autosummary/mlx.core.add.html index 1dd3c49b6..9a088ad13 100644 --- a/docs/build/html/python/_autosummary/mlx.core.add.html +++ b/docs/build/html/python/_autosummary/mlx.core.add.html @@ -8,7 +8,7 @@ - mlx.core.add — MLX 0.23.2 documentation + mlx.core.add — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.addmm.html b/docs/build/html/python/_autosummary/mlx.core.addmm.html index 2ddc29497..2264f5da8 100644 --- a/docs/build/html/python/_autosummary/mlx.core.addmm.html +++ b/docs/build/html/python/_autosummary/mlx.core.addmm.html @@ -8,7 +8,7 @@ - mlx.core.addmm — MLX 0.23.2 documentation + mlx.core.addmm — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.all.html b/docs/build/html/python/_autosummary/mlx.core.all.html index 854b29227..de1018cc2 100644 --- a/docs/build/html/python/_autosummary/mlx.core.all.html +++ b/docs/build/html/python/_autosummary/mlx.core.all.html @@ -8,7 +8,7 @@ - mlx.core.all — MLX 0.23.2 documentation + mlx.core.all — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.allclose.html b/docs/build/html/python/_autosummary/mlx.core.allclose.html index a2bc9a885..62e25279d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.allclose.html +++ b/docs/build/html/python/_autosummary/mlx.core.allclose.html @@ -8,7 +8,7 @@ - mlx.core.allclose — MLX 0.23.2 documentation + mlx.core.allclose — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.any.html b/docs/build/html/python/_autosummary/mlx.core.any.html index a1371ff99..18c8466de 100644 --- a/docs/build/html/python/_autosummary/mlx.core.any.html +++ b/docs/build/html/python/_autosummary/mlx.core.any.html @@ -8,7 +8,7 @@ - mlx.core.any — MLX 0.23.2 documentation + mlx.core.any — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.arange.html b/docs/build/html/python/_autosummary/mlx.core.arange.html index 03e95880f..8b6109ffb 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arange.html +++ b/docs/build/html/python/_autosummary/mlx.core.arange.html @@ -8,7 +8,7 @@ - mlx.core.arange — MLX 0.23.2 documentation + mlx.core.arange — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.arccos.html b/docs/build/html/python/_autosummary/mlx.core.arccos.html index 44376fc04..5e6c5511d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arccos.html +++ b/docs/build/html/python/_autosummary/mlx.core.arccos.html @@ -8,7 +8,7 @@ - mlx.core.arccos — MLX 0.23.2 documentation + mlx.core.arccos — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.arccosh.html b/docs/build/html/python/_autosummary/mlx.core.arccosh.html index 00f96ee60..af63cb467 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arccosh.html +++ b/docs/build/html/python/_autosummary/mlx.core.arccosh.html @@ -8,7 +8,7 @@ - mlx.core.arccosh — MLX 0.23.2 documentation + mlx.core.arccosh — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.arcsin.html b/docs/build/html/python/_autosummary/mlx.core.arcsin.html index 258435081..d6323864a 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arcsin.html +++ b/docs/build/html/python/_autosummary/mlx.core.arcsin.html @@ -8,7 +8,7 @@ - mlx.core.arcsin — MLX 0.23.2 documentation + mlx.core.arcsin — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.arcsinh.html b/docs/build/html/python/_autosummary/mlx.core.arcsinh.html index f65da7d7d..7b91b88da 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arcsinh.html +++ b/docs/build/html/python/_autosummary/mlx.core.arcsinh.html @@ -8,7 +8,7 @@ - mlx.core.arcsinh — MLX 0.23.2 documentation + mlx.core.arcsinh — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.arctan.html b/docs/build/html/python/_autosummary/mlx.core.arctan.html index 6d29a9c38..5205480f7 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arctan.html +++ b/docs/build/html/python/_autosummary/mlx.core.arctan.html @@ -8,7 +8,7 @@ - mlx.core.arctan — MLX 0.23.2 documentation + mlx.core.arctan — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.arctan2.html b/docs/build/html/python/_autosummary/mlx.core.arctan2.html index 1028722af..ef6075c6d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arctan2.html +++ b/docs/build/html/python/_autosummary/mlx.core.arctan2.html @@ -8,7 +8,7 @@ - mlx.core.arctan2 — MLX 0.23.2 documentation + mlx.core.arctan2 — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.arctanh.html b/docs/build/html/python/_autosummary/mlx.core.arctanh.html index 46eb39f94..7e641afee 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arctanh.html +++ b/docs/build/html/python/_autosummary/mlx.core.arctanh.html @@ -8,7 +8,7 @@ - mlx.core.arctanh — MLX 0.23.2 documentation + mlx.core.arctanh — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.argmax.html b/docs/build/html/python/_autosummary/mlx.core.argmax.html index 5c71d8331..faaba223f 100644 --- a/docs/build/html/python/_autosummary/mlx.core.argmax.html +++ b/docs/build/html/python/_autosummary/mlx.core.argmax.html @@ -8,7 +8,7 @@ - mlx.core.argmax — MLX 0.23.2 documentation + mlx.core.argmax — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
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                  diff --git a/docs/build/html/python/_autosummary/mlx.core.array.round.html b/docs/build/html/python/_autosummary/mlx.core.array.round.html index c1927d5d2..eeda00a07 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.round.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.round.html @@ -8,7 +8,7 @@ - mlx.core.array.round — MLX 0.23.2 documentation + mlx.core.array.round — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
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                  diff --git a/docs/build/html/python/_autosummary/mlx.core.array.split.html b/docs/build/html/python/_autosummary/mlx.core.array.split.html index 41a7ed066..ffdc24e62 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.split.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.split.html @@ -8,7 +8,7 @@ - mlx.core.array.split — MLX 0.23.2 documentation + mlx.core.array.split — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.array.sqrt.html b/docs/build/html/python/_autosummary/mlx.core.array.sqrt.html index c91b143dc..63c9f73d6 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.sqrt.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.sqrt.html @@ -8,7 +8,7 @@ - mlx.core.array.sqrt — MLX 0.23.2 documentation + mlx.core.array.sqrt — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
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                  diff --git a/docs/build/html/python/_autosummary/mlx.core.array.std.html b/docs/build/html/python/_autosummary/mlx.core.array.std.html index 5fc683b58..256847f04 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.std.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.std.html @@ -8,7 +8,7 @@ - mlx.core.array.std — MLX 0.23.2 documentation + mlx.core.array.std — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
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mlx.core.distributed.recv_like — MLX 0.23.2 documentation + mlx.core.distributed.recv_like — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.distributed.send.html b/docs/build/html/python/_autosummary/mlx.core.distributed.send.html index e317f42b5..a055af88a 100644 --- a/docs/build/html/python/_autosummary/mlx.core.distributed.send.html +++ b/docs/build/html/python/_autosummary/mlx.core.distributed.send.html @@ -8,7 +8,7 @@ - mlx.core.distributed.send — MLX 0.23.2 documentation + mlx.core.distributed.send — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.divide.html b/docs/build/html/python/_autosummary/mlx.core.divide.html index 576dd8b31..4aab23533 100644 --- a/docs/build/html/python/_autosummary/mlx.core.divide.html +++ b/docs/build/html/python/_autosummary/mlx.core.divide.html @@ -8,7 +8,7 @@ - mlx.core.divide — MLX 0.23.2 documentation + mlx.core.divide — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.divmod.html b/docs/build/html/python/_autosummary/mlx.core.divmod.html index b51974d16..c25e81465 100644 --- a/docs/build/html/python/_autosummary/mlx.core.divmod.html +++ b/docs/build/html/python/_autosummary/mlx.core.divmod.html @@ -8,7 +8,7 @@ - mlx.core.divmod — MLX 0.23.2 documentation + mlx.core.divmod — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.einsum.html b/docs/build/html/python/_autosummary/mlx.core.einsum.html index 403ece84a..3228c9a54 100644 --- a/docs/build/html/python/_autosummary/mlx.core.einsum.html +++ b/docs/build/html/python/_autosummary/mlx.core.einsum.html @@ -8,7 +8,7 @@ - mlx.core.einsum — MLX 0.23.2 documentation + mlx.core.einsum — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.einsum_path.html b/docs/build/html/python/_autosummary/mlx.core.einsum_path.html index 130a10236..b867435cd 100644 --- a/docs/build/html/python/_autosummary/mlx.core.einsum_path.html +++ b/docs/build/html/python/_autosummary/mlx.core.einsum_path.html @@ -8,7 +8,7 @@ - mlx.core.einsum_path — MLX 0.23.2 documentation + mlx.core.einsum_path — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.enable_compile.html b/docs/build/html/python/_autosummary/mlx.core.enable_compile.html index 417b7dc66..361428cf8 100644 --- a/docs/build/html/python/_autosummary/mlx.core.enable_compile.html +++ b/docs/build/html/python/_autosummary/mlx.core.enable_compile.html @@ -8,7 +8,7 @@ - mlx.core.enable_compile — MLX 0.23.2 documentation + mlx.core.enable_compile — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.equal.html b/docs/build/html/python/_autosummary/mlx.core.equal.html index 6b4352e32..20ed55b66 100644 --- a/docs/build/html/python/_autosummary/mlx.core.equal.html +++ b/docs/build/html/python/_autosummary/mlx.core.equal.html @@ -8,7 +8,7 @@ - mlx.core.equal — MLX 0.23.2 documentation + mlx.core.equal — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.erf.html b/docs/build/html/python/_autosummary/mlx.core.erf.html index 47f25ca67..414fcb210 100644 --- a/docs/build/html/python/_autosummary/mlx.core.erf.html +++ b/docs/build/html/python/_autosummary/mlx.core.erf.html @@ -8,7 +8,7 @@ - mlx.core.erf — MLX 0.23.2 documentation + mlx.core.erf — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.erfinv.html b/docs/build/html/python/_autosummary/mlx.core.erfinv.html index cbc592325..c9a4c817d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.erfinv.html +++ b/docs/build/html/python/_autosummary/mlx.core.erfinv.html @@ -8,7 +8,7 @@ - mlx.core.erfinv — MLX 0.23.2 documentation + mlx.core.erfinv — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.eval.html b/docs/build/html/python/_autosummary/mlx.core.eval.html index b9dcbdb81..3c7caf087 100644 --- a/docs/build/html/python/_autosummary/mlx.core.eval.html +++ b/docs/build/html/python/_autosummary/mlx.core.eval.html @@ -8,7 +8,7 @@ - mlx.core.eval — MLX 0.23.2 documentation + mlx.core.eval — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.exp.html b/docs/build/html/python/_autosummary/mlx.core.exp.html index d82a3694f..7f11f4ff5 100644 --- a/docs/build/html/python/_autosummary/mlx.core.exp.html +++ b/docs/build/html/python/_autosummary/mlx.core.exp.html @@ -8,7 +8,7 @@ - mlx.core.exp — MLX 0.23.2 documentation + mlx.core.exp — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.expand_dims.html b/docs/build/html/python/_autosummary/mlx.core.expand_dims.html index fbd53d7b9..f37015cbb 100644 --- a/docs/build/html/python/_autosummary/mlx.core.expand_dims.html +++ b/docs/build/html/python/_autosummary/mlx.core.expand_dims.html @@ -8,7 +8,7 @@ - mlx.core.expand_dims — MLX 0.23.2 documentation + mlx.core.expand_dims — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.expm1.html b/docs/build/html/python/_autosummary/mlx.core.expm1.html index 6bd306327..0f0985305 100644 --- a/docs/build/html/python/_autosummary/mlx.core.expm1.html +++ b/docs/build/html/python/_autosummary/mlx.core.expm1.html @@ -8,7 +8,7 @@ - mlx.core.expm1 — MLX 0.23.2 documentation + mlx.core.expm1 — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.export_function.html b/docs/build/html/python/_autosummary/mlx.core.export_function.html index 20d91440d..c3eea6279 100644 --- a/docs/build/html/python/_autosummary/mlx.core.export_function.html +++ b/docs/build/html/python/_autosummary/mlx.core.export_function.html @@ -8,7 +8,7 @@ - mlx.core.export_function — MLX 0.23.2 documentation + mlx.core.export_function — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.export_to_dot.html b/docs/build/html/python/_autosummary/mlx.core.export_to_dot.html index b7e58262f..42e27987d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.export_to_dot.html +++ b/docs/build/html/python/_autosummary/mlx.core.export_to_dot.html @@ -8,7 +8,7 @@ - mlx.core.export_to_dot — MLX 0.23.2 documentation + mlx.core.export_to_dot — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.exporter.html b/docs/build/html/python/_autosummary/mlx.core.exporter.html index 13d4e2789..5650e2201 100644 --- a/docs/build/html/python/_autosummary/mlx.core.exporter.html +++ b/docs/build/html/python/_autosummary/mlx.core.exporter.html @@ -8,7 +8,7 @@ - mlx.core.exporter — MLX 0.23.2 documentation + mlx.core.exporter — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.eye.html b/docs/build/html/python/_autosummary/mlx.core.eye.html index f63a27b47..e89aed8b8 100644 --- a/docs/build/html/python/_autosummary/mlx.core.eye.html +++ b/docs/build/html/python/_autosummary/mlx.core.eye.html @@ -8,7 +8,7 @@ - mlx.core.eye — MLX 0.23.2 documentation + mlx.core.eye — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fast.layer_norm.html b/docs/build/html/python/_autosummary/mlx.core.fast.layer_norm.html index c6b09d817..979905d0e 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fast.layer_norm.html +++ b/docs/build/html/python/_autosummary/mlx.core.fast.layer_norm.html @@ -8,7 +8,7 @@ - mlx.core.fast.layer_norm — MLX 0.23.2 documentation + mlx.core.fast.layer_norm — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fast.metal_kernel.html b/docs/build/html/python/_autosummary/mlx.core.fast.metal_kernel.html index cf29019ab..ffe4c9311 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fast.metal_kernel.html +++ b/docs/build/html/python/_autosummary/mlx.core.fast.metal_kernel.html @@ -8,7 +8,7 @@ - mlx.core.fast.metal_kernel — MLX 0.23.2 documentation + mlx.core.fast.metal_kernel — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fast.rms_norm.html b/docs/build/html/python/_autosummary/mlx.core.fast.rms_norm.html index 837540aae..d94062363 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fast.rms_norm.html +++ b/docs/build/html/python/_autosummary/mlx.core.fast.rms_norm.html @@ -8,7 +8,7 @@ - mlx.core.fast.rms_norm — MLX 0.23.2 documentation + mlx.core.fast.rms_norm — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fast.rope.html b/docs/build/html/python/_autosummary/mlx.core.fast.rope.html index 71b9ca458..bf03ae351 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fast.rope.html +++ b/docs/build/html/python/_autosummary/mlx.core.fast.rope.html @@ -8,7 +8,7 @@ - mlx.core.fast.rope — MLX 0.23.2 documentation + mlx.core.fast.rope — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fast.scaled_dot_product_attention.html b/docs/build/html/python/_autosummary/mlx.core.fast.scaled_dot_product_attention.html index 77ac6adf2..3c4cefa3b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fast.scaled_dot_product_attention.html +++ b/docs/build/html/python/_autosummary/mlx.core.fast.scaled_dot_product_attention.html @@ -8,7 +8,7 @@ - mlx.core.fast.scaled_dot_product_attention — MLX 0.23.2 documentation + mlx.core.fast.scaled_dot_product_attention — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + @@ -905,7 +905,7 @@ document.write(`

                  mlx.core.fast.scaled_dot_product_attention#

                  -scaled_dot_product_attention(q: array, k: array, v: array, *, scale: float, mask: array | None = None, stream: None | Stream | Device = None) → array#
                  +scaled_dot_product_attention(q: array, k: array, v: array, *, scale: float, mask: None | str | array = None, stream: None | Stream | Device = None) → array#

                  A fast implementation of multi-head attention: O = softmax(Q @ K.T, dim=-1) @ V.

                  Supports:

                    @@ -933,11 +933,11 @@ and v

                  • k (array) – Keys with shape [B, N_kv, T_kv, D].

                  • v (array) – Values with shape [B, N_kv, T_kv, D].

                  • scale (float) – Scale for queries (typically 1.0 / sqrt(q.shape(-1))

                    • -

                  • mask (array, optional) – A boolean or additive mask to apply to the -query-key scores. The mask can have at most 4 dimensions and must -be broadcast-compatible with the shape [B, N, T_q, T_kv]. If an -additive mask is given its type must promote to the promoted -type of q, k, and v.

                    • +

                  • mask (Union[None, str, array], optional) – A causal, boolean or additive +mask to apply to the query-key scores. The mask can have at most 4 +dimensions and must be broadcast-compatible with the shape +[B, N, T_q, T_kv]. If an additive mask is given its type must +promote to the promoted type of q, k, and v.

                  Returns:
                  diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.fft.html b/docs/build/html/python/_autosummary/mlx.core.fft.fft.html index 738e72c29..3d207352d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.fft.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.fft.html @@ -8,7 +8,7 @@ - mlx.core.fft.fft — MLX 0.23.2 documentation + mlx.core.fft.fft — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.fft2.html b/docs/build/html/python/_autosummary/mlx.core.fft.fft2.html index 24d0c73cb..b25890c25 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.fft2.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.fft2.html @@ -8,7 +8,7 @@ - mlx.core.fft.fft2 — MLX 0.23.2 documentation + mlx.core.fft.fft2 — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.fftn.html b/docs/build/html/python/_autosummary/mlx.core.fft.fftn.html index 2ed41a748..151eef1b0 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.fftn.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.fftn.html @@ -8,7 +8,7 @@ - mlx.core.fft.fftn — MLX 0.23.2 documentation + mlx.core.fft.fftn — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.ifft.html b/docs/build/html/python/_autosummary/mlx.core.fft.ifft.html index bb15a78d9..9eaf22064 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.ifft.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.ifft.html @@ -8,7 +8,7 @@ - mlx.core.fft.ifft — MLX 0.23.2 documentation + mlx.core.fft.ifft — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.ifft2.html b/docs/build/html/python/_autosummary/mlx.core.fft.ifft2.html index dd33277df..d9be8fdc8 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.ifft2.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.ifft2.html @@ -8,7 +8,7 @@ - mlx.core.fft.ifft2 — MLX 0.23.2 documentation + mlx.core.fft.ifft2 — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.ifftn.html b/docs/build/html/python/_autosummary/mlx.core.fft.ifftn.html index e5c3312f2..4c8ab90df 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.ifftn.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.ifftn.html @@ -8,7 +8,7 @@ - mlx.core.fft.ifftn — MLX 0.23.2 documentation + mlx.core.fft.ifftn — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.irfft.html b/docs/build/html/python/_autosummary/mlx.core.fft.irfft.html index a04e6d8c9..d754bfa4c 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.irfft.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.irfft.html @@ -8,7 +8,7 @@ - mlx.core.fft.irfft — MLX 0.23.2 documentation + mlx.core.fft.irfft — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.irfft2.html b/docs/build/html/python/_autosummary/mlx.core.fft.irfft2.html index a6fe7f1cc..ec1e5e6ca 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.irfft2.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.irfft2.html @@ -8,7 +8,7 @@ - mlx.core.fft.irfft2 — MLX 0.23.2 documentation + mlx.core.fft.irfft2 — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.irfftn.html b/docs/build/html/python/_autosummary/mlx.core.fft.irfftn.html index acc3f9911..3bce23adb 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.irfftn.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.irfftn.html @@ -8,7 +8,7 @@ - mlx.core.fft.irfftn — MLX 0.23.2 documentation + mlx.core.fft.irfftn — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.rfft.html b/docs/build/html/python/_autosummary/mlx.core.fft.rfft.html index c2bc96733..4dc313cf5 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.rfft.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.rfft.html @@ -8,7 +8,7 @@ - mlx.core.fft.rfft — MLX 0.23.2 documentation + mlx.core.fft.rfft — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.rfft2.html b/docs/build/html/python/_autosummary/mlx.core.fft.rfft2.html index 9ac9e7e78..9b23a1091 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.rfft2.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.rfft2.html @@ -8,7 +8,7 @@ - mlx.core.fft.rfft2 — MLX 0.23.2 documentation + mlx.core.fft.rfft2 — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.rfftn.html b/docs/build/html/python/_autosummary/mlx.core.fft.rfftn.html index 1f8742bfb..c1743af65 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.rfftn.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.rfftn.html @@ -8,7 +8,7 @@ - mlx.core.fft.rfftn — MLX 0.23.2 documentation + mlx.core.fft.rfftn — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - 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mlx.core.linalg.svd — MLX 0.23.2 documentation + mlx.core.linalg.svd — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.linalg.tri_inv.html b/docs/build/html/python/_autosummary/mlx.core.linalg.tri_inv.html index e11d09653..16231f803 100644 --- a/docs/build/html/python/_autosummary/mlx.core.linalg.tri_inv.html +++ b/docs/build/html/python/_autosummary/mlx.core.linalg.tri_inv.html @@ -8,7 +8,7 @@ - mlx.core.linalg.tri_inv — MLX 0.23.2 documentation + mlx.core.linalg.tri_inv — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.linspace.html b/docs/build/html/python/_autosummary/mlx.core.linspace.html index ba7a5f9d9..471f1955b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.linspace.html +++ b/docs/build/html/python/_autosummary/mlx.core.linspace.html @@ -8,7 +8,7 @@ - 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mlx.core.metal.get_active_memory — MLX 0.23.2 documentation + mlx.core.metal.get_active_memory — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.get_cache_memory.html b/docs/build/html/python/_autosummary/mlx.core.metal.get_cache_memory.html index c01726f04..b3f6ebfdb 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.get_cache_memory.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.get_cache_memory.html @@ -8,7 +8,7 @@ - mlx.core.metal.get_cache_memory — MLX 0.23.2 documentation + mlx.core.metal.get_cache_memory — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.get_peak_memory.html b/docs/build/html/python/_autosummary/mlx.core.metal.get_peak_memory.html index c3e50ab6b..be86745a4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.get_peak_memory.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.get_peak_memory.html @@ -8,7 +8,7 @@ - mlx.core.metal.get_peak_memory — MLX 0.23.2 documentation + mlx.core.metal.get_peak_memory — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.is_available.html b/docs/build/html/python/_autosummary/mlx.core.metal.is_available.html index daf38d6eb..4895d900a 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.is_available.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.is_available.html @@ -8,7 +8,7 @@ - mlx.core.metal.is_available — MLX 0.23.2 documentation + mlx.core.metal.is_available — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.reset_peak_memory.html b/docs/build/html/python/_autosummary/mlx.core.metal.reset_peak_memory.html index c2938ca12..a59d53e2b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.reset_peak_memory.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.reset_peak_memory.html @@ -8,7 +8,7 @@ - mlx.core.metal.reset_peak_memory — MLX 0.23.2 documentation + mlx.core.metal.reset_peak_memory — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.set_cache_limit.html b/docs/build/html/python/_autosummary/mlx.core.metal.set_cache_limit.html index 5af7d195d..8305f2971 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.set_cache_limit.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.set_cache_limit.html @@ -8,7 +8,7 @@ - mlx.core.metal.set_cache_limit — MLX 0.23.2 documentation + mlx.core.metal.set_cache_limit — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.set_memory_limit.html b/docs/build/html/python/_autosummary/mlx.core.metal.set_memory_limit.html index e650c0232..3d1fc43ba 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.set_memory_limit.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.set_memory_limit.html @@ -8,7 +8,7 @@ - mlx.core.metal.set_memory_limit — MLX 0.23.2 documentation + mlx.core.metal.set_memory_limit — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.set_wired_limit.html b/docs/build/html/python/_autosummary/mlx.core.metal.set_wired_limit.html index d21110623..c11c42a9c 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.set_wired_limit.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.set_wired_limit.html @@ -8,7 +8,7 @@ - mlx.core.metal.set_wired_limit — MLX 0.23.2 documentation + mlx.core.metal.set_wired_limit — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.start_capture.html b/docs/build/html/python/_autosummary/mlx.core.metal.start_capture.html index 1494decd9..0f58ea50e 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.start_capture.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.start_capture.html @@ -8,7 +8,7 @@ - mlx.core.metal.start_capture — MLX 0.23.2 documentation + mlx.core.metal.start_capture — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.stop_capture.html b/docs/build/html/python/_autosummary/mlx.core.metal.stop_capture.html index ecd17c1b9..56c68a02b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.stop_capture.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.stop_capture.html @@ -8,7 +8,7 @@ - mlx.core.metal.stop_capture — MLX 0.23.2 documentation + mlx.core.metal.stop_capture — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.min.html b/docs/build/html/python/_autosummary/mlx.core.min.html index 72bcfb27e..209990857 100644 --- a/docs/build/html/python/_autosummary/mlx.core.min.html +++ b/docs/build/html/python/_autosummary/mlx.core.min.html @@ -8,7 +8,7 @@ - mlx.core.min — MLX 0.23.2 documentation + mlx.core.min — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.minimum.html b/docs/build/html/python/_autosummary/mlx.core.minimum.html index 93cc3b516..b910c51a8 100644 --- a/docs/build/html/python/_autosummary/mlx.core.minimum.html +++ b/docs/build/html/python/_autosummary/mlx.core.minimum.html @@ -8,7 +8,7 @@ - mlx.core.minimum — MLX 0.23.2 documentation + mlx.core.minimum — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.moveaxis.html b/docs/build/html/python/_autosummary/mlx.core.moveaxis.html index 1aeeb3c11..30761a2e8 100644 --- a/docs/build/html/python/_autosummary/mlx.core.moveaxis.html +++ b/docs/build/html/python/_autosummary/mlx.core.moveaxis.html @@ -8,7 +8,7 @@ - mlx.core.moveaxis — MLX 0.23.2 documentation + mlx.core.moveaxis — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.multiply.html b/docs/build/html/python/_autosummary/mlx.core.multiply.html index 25f398399..dcc7e55db 100644 --- a/docs/build/html/python/_autosummary/mlx.core.multiply.html +++ b/docs/build/html/python/_autosummary/mlx.core.multiply.html @@ -8,7 +8,7 @@ - mlx.core.multiply — MLX 0.23.2 documentation + mlx.core.multiply — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.nan_to_num.html b/docs/build/html/python/_autosummary/mlx.core.nan_to_num.html index c53d54897..db8763293 100644 --- a/docs/build/html/python/_autosummary/mlx.core.nan_to_num.html +++ b/docs/build/html/python/_autosummary/mlx.core.nan_to_num.html @@ -8,7 +8,7 @@ - mlx.core.nan_to_num — MLX 0.23.2 documentation + mlx.core.nan_to_num — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.negative.html b/docs/build/html/python/_autosummary/mlx.core.negative.html index 9e44745f7..3eacaef2a 100644 --- a/docs/build/html/python/_autosummary/mlx.core.negative.html +++ b/docs/build/html/python/_autosummary/mlx.core.negative.html @@ -8,7 +8,7 @@ - mlx.core.negative — MLX 0.23.2 documentation + mlx.core.negative — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.new_stream.html b/docs/build/html/python/_autosummary/mlx.core.new_stream.html index 442dbee78..d014b96e0 100644 --- a/docs/build/html/python/_autosummary/mlx.core.new_stream.html +++ b/docs/build/html/python/_autosummary/mlx.core.new_stream.html @@ -8,7 +8,7 @@ - mlx.core.new_stream — MLX 0.23.2 documentation + mlx.core.new_stream — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.not_equal.html b/docs/build/html/python/_autosummary/mlx.core.not_equal.html index af7aaac35..e46efced8 100644 --- a/docs/build/html/python/_autosummary/mlx.core.not_equal.html +++ b/docs/build/html/python/_autosummary/mlx.core.not_equal.html @@ -8,7 +8,7 @@ - mlx.core.not_equal — MLX 0.23.2 documentation + mlx.core.not_equal — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.ones.html b/docs/build/html/python/_autosummary/mlx.core.ones.html index d83485d58..c3d8501d6 100644 --- a/docs/build/html/python/_autosummary/mlx.core.ones.html +++ b/docs/build/html/python/_autosummary/mlx.core.ones.html @@ -8,7 +8,7 @@ - mlx.core.ones — MLX 0.23.2 documentation + mlx.core.ones — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.ones_like.html b/docs/build/html/python/_autosummary/mlx.core.ones_like.html index 8881aa9dd..3d5df1823 100644 --- a/docs/build/html/python/_autosummary/mlx.core.ones_like.html +++ b/docs/build/html/python/_autosummary/mlx.core.ones_like.html @@ -8,7 +8,7 @@ - mlx.core.ones_like — MLX 0.23.2 documentation + mlx.core.ones_like — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.outer.html b/docs/build/html/python/_autosummary/mlx.core.outer.html index 4598e4079..faa13d4c2 100644 --- a/docs/build/html/python/_autosummary/mlx.core.outer.html +++ b/docs/build/html/python/_autosummary/mlx.core.outer.html @@ -8,7 +8,7 @@ - mlx.core.outer — MLX 0.23.2 documentation + mlx.core.outer — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.pad.html b/docs/build/html/python/_autosummary/mlx.core.pad.html index e9cbcb852..9e97236c2 100644 --- a/docs/build/html/python/_autosummary/mlx.core.pad.html +++ b/docs/build/html/python/_autosummary/mlx.core.pad.html @@ -8,7 +8,7 @@ - mlx.core.pad — MLX 0.23.2 documentation + mlx.core.pad — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.partition.html b/docs/build/html/python/_autosummary/mlx.core.partition.html index 8a2a8ec71..562c24103 100644 --- a/docs/build/html/python/_autosummary/mlx.core.partition.html +++ b/docs/build/html/python/_autosummary/mlx.core.partition.html @@ -8,7 +8,7 @@ - mlx.core.partition — MLX 0.23.2 documentation + mlx.core.partition — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.power.html b/docs/build/html/python/_autosummary/mlx.core.power.html index 29b224a50..5b88e8bd4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.power.html +++ b/docs/build/html/python/_autosummary/mlx.core.power.html @@ -8,7 +8,7 @@ - mlx.core.power — MLX 0.23.2 documentation + mlx.core.power — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.prod.html b/docs/build/html/python/_autosummary/mlx.core.prod.html index c3fbcf37f..fbe7d630f 100644 --- a/docs/build/html/python/_autosummary/mlx.core.prod.html +++ b/docs/build/html/python/_autosummary/mlx.core.prod.html @@ -8,7 +8,7 @@ - mlx.core.prod — MLX 0.23.2 documentation + mlx.core.prod — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.put_along_axis.html b/docs/build/html/python/_autosummary/mlx.core.put_along_axis.html index c8ae0776c..2d08b8bda 100644 --- a/docs/build/html/python/_autosummary/mlx.core.put_along_axis.html +++ b/docs/build/html/python/_autosummary/mlx.core.put_along_axis.html @@ -8,7 +8,7 @@ - mlx.core.put_along_axis — MLX 0.23.2 documentation + mlx.core.put_along_axis — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.quantize.html b/docs/build/html/python/_autosummary/mlx.core.quantize.html index 35866a0f9..15b295de2 100644 --- a/docs/build/html/python/_autosummary/mlx.core.quantize.html +++ b/docs/build/html/python/_autosummary/mlx.core.quantize.html @@ -8,7 +8,7 @@ - mlx.core.quantize — MLX 0.23.2 documentation + mlx.core.quantize — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.quantized_matmul.html b/docs/build/html/python/_autosummary/mlx.core.quantized_matmul.html index 667146d71..5d508f482 100644 --- a/docs/build/html/python/_autosummary/mlx.core.quantized_matmul.html +++ b/docs/build/html/python/_autosummary/mlx.core.quantized_matmul.html @@ -8,7 +8,7 @@ - mlx.core.quantized_matmul — MLX 0.23.2 documentation + mlx.core.quantized_matmul — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.radians.html b/docs/build/html/python/_autosummary/mlx.core.radians.html index 72cf176ad..0e39d582e 100644 --- a/docs/build/html/python/_autosummary/mlx.core.radians.html +++ b/docs/build/html/python/_autosummary/mlx.core.radians.html @@ -8,7 +8,7 @@ - mlx.core.radians — MLX 0.23.2 documentation + mlx.core.radians — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.random.bernoulli.html b/docs/build/html/python/_autosummary/mlx.core.random.bernoulli.html index 887ffc66d..1c1558ed7 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.bernoulli.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.bernoulli.html @@ -8,7 +8,7 @@ - mlx.core.random.bernoulli — MLX 0.23.2 documentation + mlx.core.random.bernoulli — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.random.categorical.html b/docs/build/html/python/_autosummary/mlx.core.random.categorical.html index db29787cf..b52644812 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.categorical.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.categorical.html @@ -8,7 +8,7 @@ - mlx.core.random.categorical — MLX 0.23.2 documentation + mlx.core.random.categorical — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.random.gumbel.html b/docs/build/html/python/_autosummary/mlx.core.random.gumbel.html index 783a26f5e..69f53197b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.gumbel.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.gumbel.html @@ -8,7 +8,7 @@ - mlx.core.random.gumbel — MLX 0.23.2 documentation + mlx.core.random.gumbel — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.random.key.html b/docs/build/html/python/_autosummary/mlx.core.random.key.html index 9f12c0aca..cc4a6232b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.key.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.key.html @@ -8,7 +8,7 @@ - mlx.core.random.key — MLX 0.23.2 documentation + mlx.core.random.key — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.random.laplace.html b/docs/build/html/python/_autosummary/mlx.core.random.laplace.html index b164518e0..c4d9d0742 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.laplace.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.laplace.html @@ -8,7 +8,7 @@ - mlx.core.random.laplace — MLX 0.23.2 documentation + mlx.core.random.laplace — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.random.multivariate_normal.html b/docs/build/html/python/_autosummary/mlx.core.random.multivariate_normal.html index 802c8cb43..09e3ed411 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.multivariate_normal.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.multivariate_normal.html @@ -8,7 +8,7 @@ - mlx.core.random.multivariate_normal — MLX 0.23.2 documentation + mlx.core.random.multivariate_normal — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.random.normal.html b/docs/build/html/python/_autosummary/mlx.core.random.normal.html index a3e972461..821199fb8 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.normal.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.normal.html @@ -8,7 +8,7 @@ - mlx.core.random.normal — MLX 0.23.2 documentation + mlx.core.random.normal — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.random.permutation.html b/docs/build/html/python/_autosummary/mlx.core.random.permutation.html index ed5697ae1..5db2b6deb 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.permutation.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.permutation.html @@ -8,7 +8,7 @@ - mlx.core.random.permutation — MLX 0.23.2 documentation + mlx.core.random.permutation — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.random.randint.html b/docs/build/html/python/_autosummary/mlx.core.random.randint.html index 9bb65b607..4c451872a 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.randint.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.randint.html @@ -8,7 +8,7 @@ - mlx.core.random.randint — MLX 0.23.2 documentation + mlx.core.random.randint — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + @@ -909,7 +909,7 @@ document.write(`

                  Generate random integers from the given interval.

                  The values are sampled with equal probability from the integers in half-open interval [low, high). The lower and upper bound can be -scalars or arrays and must be roadcastable to shape.

                  +scalars or arrays and must be broadcastable to shape.

                  Parameters:
                    diff --git a/docs/build/html/python/_autosummary/mlx.core.random.seed.html b/docs/build/html/python/_autosummary/mlx.core.random.seed.html index 4dfe41b5a..e9ed28fd9 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.seed.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.seed.html @@ -8,7 +8,7 @@ - mlx.core.random.seed — MLX 0.23.2 documentation + mlx.core.random.seed — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.random.split.html b/docs/build/html/python/_autosummary/mlx.core.random.split.html index 679df8f57..da2453ef9 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.split.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.split.html @@ -8,7 +8,7 @@ - mlx.core.random.split — MLX 0.23.2 documentation + mlx.core.random.split — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.random.truncated_normal.html b/docs/build/html/python/_autosummary/mlx.core.random.truncated_normal.html index 30dea4575..733dcb674 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.truncated_normal.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.truncated_normal.html @@ -8,7 +8,7 @@ - mlx.core.random.truncated_normal — MLX 0.23.2 documentation + mlx.core.random.truncated_normal — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.random.uniform.html b/docs/build/html/python/_autosummary/mlx.core.random.uniform.html index e15bbf7e0..f4bab78e5 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.uniform.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.uniform.html @@ -8,7 +8,7 @@ - mlx.core.random.uniform — MLX 0.23.2 documentation + mlx.core.random.uniform — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.real.html b/docs/build/html/python/_autosummary/mlx.core.real.html index 4572aaafc..33eb9c51d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.real.html +++ b/docs/build/html/python/_autosummary/mlx.core.real.html @@ -8,7 +8,7 @@ - mlx.core.real — MLX 0.23.2 documentation + mlx.core.real — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.reciprocal.html b/docs/build/html/python/_autosummary/mlx.core.reciprocal.html index e64d141e9..abb433888 100644 --- a/docs/build/html/python/_autosummary/mlx.core.reciprocal.html +++ b/docs/build/html/python/_autosummary/mlx.core.reciprocal.html @@ -8,7 +8,7 @@ - mlx.core.reciprocal — MLX 0.23.2 documentation + mlx.core.reciprocal — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.remainder.html b/docs/build/html/python/_autosummary/mlx.core.remainder.html index b88831823..8d047e4b1 100644 --- a/docs/build/html/python/_autosummary/mlx.core.remainder.html +++ b/docs/build/html/python/_autosummary/mlx.core.remainder.html @@ -8,7 +8,7 @@ - mlx.core.remainder — MLX 0.23.2 documentation + mlx.core.remainder — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.repeat.html b/docs/build/html/python/_autosummary/mlx.core.repeat.html index 31e39aef0..89fb263ba 100644 --- a/docs/build/html/python/_autosummary/mlx.core.repeat.html +++ b/docs/build/html/python/_autosummary/mlx.core.repeat.html @@ -8,7 +8,7 @@ - mlx.core.repeat — MLX 0.23.2 documentation + mlx.core.repeat — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.reshape.html b/docs/build/html/python/_autosummary/mlx.core.reshape.html index 0d29f23db..f354f90c6 100644 --- a/docs/build/html/python/_autosummary/mlx.core.reshape.html +++ b/docs/build/html/python/_autosummary/mlx.core.reshape.html @@ -8,7 +8,7 @@ - mlx.core.reshape — MLX 0.23.2 documentation + mlx.core.reshape — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.right_shift.html b/docs/build/html/python/_autosummary/mlx.core.right_shift.html index 4d4eb9ea1..0b246163b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.right_shift.html +++ b/docs/build/html/python/_autosummary/mlx.core.right_shift.html @@ -8,7 +8,7 @@ - mlx.core.right_shift — MLX 0.23.2 documentation + mlx.core.right_shift — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.roll.html b/docs/build/html/python/_autosummary/mlx.core.roll.html index ff5e8c63f..0c8b9e8ef 100644 --- a/docs/build/html/python/_autosummary/mlx.core.roll.html +++ b/docs/build/html/python/_autosummary/mlx.core.roll.html @@ -8,7 +8,7 @@ - mlx.core.roll — MLX 0.23.2 documentation + mlx.core.roll — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.round.html b/docs/build/html/python/_autosummary/mlx.core.round.html index d1c095f8a..1149d0bf4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.round.html +++ b/docs/build/html/python/_autosummary/mlx.core.round.html @@ -8,7 +8,7 @@ - mlx.core.round — MLX 0.23.2 documentation + mlx.core.round — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.rsqrt.html b/docs/build/html/python/_autosummary/mlx.core.rsqrt.html index 29d10723e..d4511e0d6 100644 --- a/docs/build/html/python/_autosummary/mlx.core.rsqrt.html +++ b/docs/build/html/python/_autosummary/mlx.core.rsqrt.html @@ -8,7 +8,7 @@ - mlx.core.rsqrt — MLX 0.23.2 documentation + mlx.core.rsqrt — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.save.html b/docs/build/html/python/_autosummary/mlx.core.save.html index effd142c7..a3a9172fb 100644 --- a/docs/build/html/python/_autosummary/mlx.core.save.html +++ b/docs/build/html/python/_autosummary/mlx.core.save.html @@ -8,7 +8,7 @@ - mlx.core.save — MLX 0.23.2 documentation + mlx.core.save — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.save_gguf.html b/docs/build/html/python/_autosummary/mlx.core.save_gguf.html index 40b9513cd..45a02bdc7 100644 --- a/docs/build/html/python/_autosummary/mlx.core.save_gguf.html +++ b/docs/build/html/python/_autosummary/mlx.core.save_gguf.html @@ -8,7 +8,7 @@ - mlx.core.save_gguf — MLX 0.23.2 documentation + mlx.core.save_gguf — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.save_safetensors.html b/docs/build/html/python/_autosummary/mlx.core.save_safetensors.html index e0d37a325..8473400a7 100644 --- a/docs/build/html/python/_autosummary/mlx.core.save_safetensors.html +++ b/docs/build/html/python/_autosummary/mlx.core.save_safetensors.html @@ -8,7 +8,7 @@ - mlx.core.save_safetensors — MLX 0.23.2 documentation + mlx.core.save_safetensors — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.savez.html b/docs/build/html/python/_autosummary/mlx.core.savez.html index 1406a1160..d80125280 100644 --- a/docs/build/html/python/_autosummary/mlx.core.savez.html +++ b/docs/build/html/python/_autosummary/mlx.core.savez.html @@ -8,7 +8,7 @@ - mlx.core.savez — MLX 0.23.2 documentation + mlx.core.savez — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.savez_compressed.html b/docs/build/html/python/_autosummary/mlx.core.savez_compressed.html index d5be18cd5..a3df75113 100644 --- a/docs/build/html/python/_autosummary/mlx.core.savez_compressed.html +++ b/docs/build/html/python/_autosummary/mlx.core.savez_compressed.html @@ -8,7 +8,7 @@ - mlx.core.savez_compressed — MLX 0.23.2 documentation + mlx.core.savez_compressed — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.set_default_device.html b/docs/build/html/python/_autosummary/mlx.core.set_default_device.html index dc02b83d2..189a0979f 100644 --- a/docs/build/html/python/_autosummary/mlx.core.set_default_device.html +++ b/docs/build/html/python/_autosummary/mlx.core.set_default_device.html @@ -8,7 +8,7 @@ - mlx.core.set_default_device — MLX 0.23.2 documentation + mlx.core.set_default_device — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.set_default_stream.html b/docs/build/html/python/_autosummary/mlx.core.set_default_stream.html index 3b1804291..786aca454 100644 --- a/docs/build/html/python/_autosummary/mlx.core.set_default_stream.html +++ b/docs/build/html/python/_autosummary/mlx.core.set_default_stream.html @@ -8,7 +8,7 @@ - mlx.core.set_default_stream — MLX 0.23.2 documentation + mlx.core.set_default_stream — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.sigmoid.html b/docs/build/html/python/_autosummary/mlx.core.sigmoid.html index 0339fe8ee..9127b30d4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.sigmoid.html +++ b/docs/build/html/python/_autosummary/mlx.core.sigmoid.html @@ -8,7 +8,7 @@ - mlx.core.sigmoid — MLX 0.23.2 documentation + mlx.core.sigmoid — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.sign.html b/docs/build/html/python/_autosummary/mlx.core.sign.html index 10a6a86d9..6dee9fb91 100644 --- a/docs/build/html/python/_autosummary/mlx.core.sign.html +++ b/docs/build/html/python/_autosummary/mlx.core.sign.html @@ -8,7 +8,7 @@ - mlx.core.sign — MLX 0.23.2 documentation + mlx.core.sign — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.sin.html b/docs/build/html/python/_autosummary/mlx.core.sin.html index 4c9fad819..fff125452 100644 --- a/docs/build/html/python/_autosummary/mlx.core.sin.html +++ b/docs/build/html/python/_autosummary/mlx.core.sin.html @@ -8,7 +8,7 @@ - mlx.core.sin — MLX 0.23.2 documentation + mlx.core.sin — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.sinh.html b/docs/build/html/python/_autosummary/mlx.core.sinh.html index 853ddba19..c52a19196 100644 --- a/docs/build/html/python/_autosummary/mlx.core.sinh.html +++ b/docs/build/html/python/_autosummary/mlx.core.sinh.html @@ -8,7 +8,7 @@ - mlx.core.sinh — MLX 0.23.2 documentation + mlx.core.sinh — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.slice.html b/docs/build/html/python/_autosummary/mlx.core.slice.html index 445a43ec7..90f8f8235 100644 --- a/docs/build/html/python/_autosummary/mlx.core.slice.html +++ b/docs/build/html/python/_autosummary/mlx.core.slice.html @@ -8,7 +8,7 @@ - mlx.core.slice — MLX 0.23.2 documentation + mlx.core.slice — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.slice_update.html b/docs/build/html/python/_autosummary/mlx.core.slice_update.html index 7dc109880..7fb0ee78f 100644 --- a/docs/build/html/python/_autosummary/mlx.core.slice_update.html +++ b/docs/build/html/python/_autosummary/mlx.core.slice_update.html @@ -8,7 +8,7 @@ - mlx.core.slice_update — MLX 0.23.2 documentation + mlx.core.slice_update — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.softmax.html b/docs/build/html/python/_autosummary/mlx.core.softmax.html index 3fb10612b..f8cfa63b5 100644 --- a/docs/build/html/python/_autosummary/mlx.core.softmax.html +++ b/docs/build/html/python/_autosummary/mlx.core.softmax.html @@ -8,7 +8,7 @@ - mlx.core.softmax — MLX 0.23.2 documentation + mlx.core.softmax — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.sort.html b/docs/build/html/python/_autosummary/mlx.core.sort.html index c7aa90b17..38251e728 100644 --- a/docs/build/html/python/_autosummary/mlx.core.sort.html +++ b/docs/build/html/python/_autosummary/mlx.core.sort.html @@ -8,7 +8,7 @@ - mlx.core.sort — MLX 0.23.2 documentation + mlx.core.sort — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.split.html b/docs/build/html/python/_autosummary/mlx.core.split.html index ee5156e68..5642404d0 100644 --- a/docs/build/html/python/_autosummary/mlx.core.split.html +++ b/docs/build/html/python/_autosummary/mlx.core.split.html @@ -8,7 +8,7 @@ - mlx.core.split — MLX 0.23.2 documentation + mlx.core.split — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.sqrt.html b/docs/build/html/python/_autosummary/mlx.core.sqrt.html index b64de089c..7f2ca311c 100644 --- a/docs/build/html/python/_autosummary/mlx.core.sqrt.html +++ b/docs/build/html/python/_autosummary/mlx.core.sqrt.html @@ -8,7 +8,7 @@ - mlx.core.sqrt — MLX 0.23.2 documentation + mlx.core.sqrt — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.square.html b/docs/build/html/python/_autosummary/mlx.core.square.html index 5381f2bb8..f04bd0d5c 100644 --- a/docs/build/html/python/_autosummary/mlx.core.square.html +++ b/docs/build/html/python/_autosummary/mlx.core.square.html @@ -8,7 +8,7 @@ - mlx.core.square — MLX 0.23.2 documentation + mlx.core.square — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.squeeze.html b/docs/build/html/python/_autosummary/mlx.core.squeeze.html index cb2121fcb..0d50dfb5e 100644 --- a/docs/build/html/python/_autosummary/mlx.core.squeeze.html +++ b/docs/build/html/python/_autosummary/mlx.core.squeeze.html @@ -8,7 +8,7 @@ - mlx.core.squeeze — MLX 0.23.2 documentation + mlx.core.squeeze — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - 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MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.unflatten.html b/docs/build/html/python/_autosummary/mlx.core.unflatten.html index a92ea6ca0..6a201e289 100644 --- a/docs/build/html/python/_autosummary/mlx.core.unflatten.html +++ b/docs/build/html/python/_autosummary/mlx.core.unflatten.html @@ -8,7 +8,7 @@ - mlx.core.unflatten — MLX 0.23.2 documentation + mlx.core.unflatten — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.value_and_grad.html b/docs/build/html/python/_autosummary/mlx.core.value_and_grad.html index 57cd1cbd0..33d3e79f1 100644 --- a/docs/build/html/python/_autosummary/mlx.core.value_and_grad.html +++ b/docs/build/html/python/_autosummary/mlx.core.value_and_grad.html @@ -8,7 +8,7 @@ - mlx.core.value_and_grad — MLX 0.23.2 documentation + mlx.core.value_and_grad — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - 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Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.where.html b/docs/build/html/python/_autosummary/mlx.core.where.html index 8fe571ed5..873a85abd 100644 --- a/docs/build/html/python/_autosummary/mlx.core.where.html +++ b/docs/build/html/python/_autosummary/mlx.core.where.html @@ -8,7 +8,7 @@ - mlx.core.where — MLX 0.23.2 documentation + mlx.core.where — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.zeros.html b/docs/build/html/python/_autosummary/mlx.core.zeros.html index 5e4de1161..c93b3fcee 100644 --- a/docs/build/html/python/_autosummary/mlx.core.zeros.html +++ b/docs/build/html/python/_autosummary/mlx.core.zeros.html @@ -8,7 +8,7 @@ - mlx.core.zeros — MLX 0.23.2 documentation + mlx.core.zeros — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.core.zeros_like.html b/docs/build/html/python/_autosummary/mlx.core.zeros_like.html index 30689bd33..a5f38d6f5 100644 --- a/docs/build/html/python/_autosummary/mlx.core.zeros_like.html +++ b/docs/build/html/python/_autosummary/mlx.core.zeros_like.html @@ -8,7 +8,7 @@ - mlx.core.zeros_like — MLX 0.23.2 documentation + mlx.core.zeros_like — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.nn.average_gradients.html b/docs/build/html/python/_autosummary/mlx.nn.average_gradients.html index c699fd43c..b69c36c73 100644 --- a/docs/build/html/python/_autosummary/mlx.nn.average_gradients.html +++ b/docs/build/html/python/_autosummary/mlx.nn.average_gradients.html @@ -8,7 +8,7 @@ - mlx.nn.average_gradients — MLX 0.23.2 documentation + mlx.nn.average_gradients — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.nn.quantize.html b/docs/build/html/python/_autosummary/mlx.nn.quantize.html index 8ede66793..110b65876 100644 --- a/docs/build/html/python/_autosummary/mlx.nn.quantize.html +++ b/docs/build/html/python/_autosummary/mlx.nn.quantize.html @@ -8,7 +8,7 @@ - mlx.nn.quantize — MLX 0.23.2 documentation + mlx.nn.quantize — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.nn.value_and_grad.html b/docs/build/html/python/_autosummary/mlx.nn.value_and_grad.html index 8ae8a8fcc..db5c4ec07 100644 --- a/docs/build/html/python/_autosummary/mlx.nn.value_and_grad.html +++ b/docs/build/html/python/_autosummary/mlx.nn.value_and_grad.html @@ -8,7 +8,7 @@ - mlx.nn.value_and_grad — MLX 0.23.2 documentation + mlx.nn.value_and_grad — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.optimizers.clip_grad_norm.html b/docs/build/html/python/_autosummary/mlx.optimizers.clip_grad_norm.html index 0be6ada6a..da241eb29 100644 --- a/docs/build/html/python/_autosummary/mlx.optimizers.clip_grad_norm.html +++ b/docs/build/html/python/_autosummary/mlx.optimizers.clip_grad_norm.html @@ -8,7 +8,7 @@ - mlx.optimizers.clip_grad_norm — MLX 0.23.2 documentation + mlx.optimizers.clip_grad_norm — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.utils.tree_flatten.html b/docs/build/html/python/_autosummary/mlx.utils.tree_flatten.html index 1c0fa27c0..1553d7be3 100644 --- a/docs/build/html/python/_autosummary/mlx.utils.tree_flatten.html +++ b/docs/build/html/python/_autosummary/mlx.utils.tree_flatten.html @@ -8,7 +8,7 @@ - mlx.utils.tree_flatten — MLX 0.23.2 documentation + mlx.utils.tree_flatten — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.utils.tree_map.html b/docs/build/html/python/_autosummary/mlx.utils.tree_map.html index cf5799e37..1f4fac1ae 100644 --- a/docs/build/html/python/_autosummary/mlx.utils.tree_map.html +++ b/docs/build/html/python/_autosummary/mlx.utils.tree_map.html @@ -8,7 +8,7 @@ - mlx.utils.tree_map — MLX 0.23.2 documentation + mlx.utils.tree_map — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.utils.tree_map_with_path.html b/docs/build/html/python/_autosummary/mlx.utils.tree_map_with_path.html index 6a4ea101c..242c91895 100644 --- a/docs/build/html/python/_autosummary/mlx.utils.tree_map_with_path.html +++ b/docs/build/html/python/_autosummary/mlx.utils.tree_map_with_path.html @@ -8,7 +8,7 @@ - mlx.utils.tree_map_with_path — MLX 0.23.2 documentation + mlx.utils.tree_map_with_path — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + @@ -916,8 +916,9 @@ the first argument followed by the remaining tree nodes.

                  • fn (callable) – The function that processes the leaves of the tree.

                  • tree (Any) – The main Python tree that will be iterated upon.

                  • rest (tuple[Any]) – Extra trees to be iterated together with tree.

                    • -

                  • is_leaf (callable, optional) – An optional callable that returns True +

                  • is_leaf (Optional[Callable]) – An optional callable that returns True if the passed object is considered a leaf or False otherwise.

                    • +

                  • path (Optional[Any]) – Prefix will be added to the result.

                  Returns:
                  diff --git a/docs/build/html/python/_autosummary/mlx.utils.tree_reduce.html b/docs/build/html/python/_autosummary/mlx.utils.tree_reduce.html index bbdea4d9d..94077367a 100644 --- a/docs/build/html/python/_autosummary/mlx.utils.tree_reduce.html +++ b/docs/build/html/python/_autosummary/mlx.utils.tree_reduce.html @@ -8,7 +8,7 @@ - mlx.utils.tree_reduce — MLX 0.23.2 documentation + mlx.utils.tree_reduce — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/mlx.utils.tree_unflatten.html b/docs/build/html/python/_autosummary/mlx.utils.tree_unflatten.html index f40d4a5ef..53b21697b 100644 --- a/docs/build/html/python/_autosummary/mlx.utils.tree_unflatten.html +++ b/docs/build/html/python/_autosummary/mlx.utils.tree_unflatten.html @@ -8,7 +8,7 @@ - mlx.utils.tree_unflatten — MLX 0.23.2 documentation + mlx.utils.tree_unflatten — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/_autosummary/stream_class.html b/docs/build/html/python/_autosummary/stream_class.html index f9b7c83bd..4a4bb06d6 100644 --- a/docs/build/html/python/_autosummary/stream_class.html +++ b/docs/build/html/python/_autosummary/stream_class.html @@ -8,7 +8,7 @@ - mlx.core.Stream — MLX 0.23.2 documentation + mlx.core.Stream — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/array.html b/docs/build/html/python/array.html index 7ab24a58b..5f2466268 100644 --- a/docs/build/html/python/array.html +++ b/docs/build/html/python/array.html @@ -8,7 +8,7 @@ - Array — MLX 0.23.2 documentation + Array — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/data_types.html b/docs/build/html/python/data_types.html index 02899df97..3a6b8e1e7 100644 --- a/docs/build/html/python/data_types.html +++ b/docs/build/html/python/data_types.html @@ -8,7 +8,7 @@ - Data Types — MLX 0.23.2 documentation + Data Types — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/devices_and_streams.html b/docs/build/html/python/devices_and_streams.html index 8bcdf7493..05ada88e1 100644 --- a/docs/build/html/python/devices_and_streams.html +++ b/docs/build/html/python/devices_and_streams.html @@ -8,7 +8,7 @@ - Devices and Streams — MLX 0.23.2 documentation + Devices and Streams — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/distributed.html b/docs/build/html/python/distributed.html index efc7df08f..2b5bbc531 100644 --- a/docs/build/html/python/distributed.html +++ b/docs/build/html/python/distributed.html @@ -8,7 +8,7 @@ - Distributed Communication — MLX 0.23.2 documentation + Distributed Communication — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/export.html b/docs/build/html/python/export.html index abfc12166..4276a0376 100644 --- a/docs/build/html/python/export.html +++ b/docs/build/html/python/export.html @@ -8,7 +8,7 @@ - Export Functions — MLX 0.23.2 documentation + Export Functions — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/fast.html b/docs/build/html/python/fast.html index cc4b7357e..b84d62539 100644 --- a/docs/build/html/python/fast.html +++ b/docs/build/html/python/fast.html @@ -8,7 +8,7 @@ - Fast — MLX 0.23.2 documentation + Fast — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/fft.html b/docs/build/html/python/fft.html index 7ac811d0c..58e0a6eb2 100644 --- a/docs/build/html/python/fft.html +++ b/docs/build/html/python/fft.html @@ -8,7 +8,7 @@ - FFT — MLX 0.23.2 documentation + FFT — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/linalg.html b/docs/build/html/python/linalg.html index 92e51db81..3f7057c53 100644 --- a/docs/build/html/python/linalg.html +++ b/docs/build/html/python/linalg.html @@ -8,7 +8,7 @@ - Linear Algebra — MLX 0.23.2 documentation + Linear Algebra — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/metal.html b/docs/build/html/python/metal.html index 46b8efe8a..374494de3 100644 --- a/docs/build/html/python/metal.html +++ b/docs/build/html/python/metal.html @@ -8,7 +8,7 @@ - Metal — MLX 0.23.2 documentation + Metal — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn.html b/docs/build/html/python/nn.html index 0bc5601de..dfd7d2611 100644 --- a/docs/build/html/python/nn.html +++ b/docs/build/html/python/nn.html @@ -8,7 +8,7 @@ - Neural Networks — MLX 0.23.2 documentation + Neural Networks — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.ALiBi.html b/docs/build/html/python/nn/_autosummary/mlx.nn.ALiBi.html index 28cb1e331..3f0aa8f33 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.ALiBi.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.ALiBi.html @@ -8,7 +8,7 @@ - mlx.nn.ALiBi — MLX 0.23.2 documentation + mlx.nn.ALiBi — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool1d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool1d.html index b6a2dbfd0..789fb72c8 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool1d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool1d.html @@ -8,7 +8,7 @@ - mlx.nn.AvgPool1d — MLX 0.23.2 documentation + mlx.nn.AvgPool1d — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool2d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool2d.html index 62f1be3fb..a53b1f014 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool2d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool2d.html @@ -8,7 +8,7 @@ - mlx.nn.AvgPool2d — MLX 0.23.2 documentation + mlx.nn.AvgPool2d — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool3d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool3d.html index 0379ed66b..db4f7ff1d 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool3d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool3d.html @@ -8,7 +8,7 @@ - mlx.nn.AvgPool3d — MLX 0.23.2 documentation + mlx.nn.AvgPool3d — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.BatchNorm.html b/docs/build/html/python/nn/_autosummary/mlx.nn.BatchNorm.html index 0d1e36a02..432b214c7 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.BatchNorm.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.BatchNorm.html @@ -8,7 +8,7 @@ - mlx.nn.BatchNorm — MLX 0.23.2 documentation + mlx.nn.BatchNorm — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.CELU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.CELU.html index 2fe41d7ca..5b90275b5 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.CELU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.CELU.html @@ -8,7 +8,7 @@ - mlx.nn.CELU — MLX 0.23.2 documentation + mlx.nn.CELU — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Conv1d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Conv1d.html index 7e6190ab7..95629a835 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Conv1d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Conv1d.html @@ -8,7 +8,7 @@ - mlx.nn.Conv1d — MLX 0.23.2 documentation + mlx.nn.Conv1d — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Conv2d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Conv2d.html index 37bff3b72..b23238f20 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Conv2d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Conv2d.html @@ -8,7 +8,7 @@ - mlx.nn.Conv2d — MLX 0.23.2 documentation + mlx.nn.Conv2d — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Conv3d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Conv3d.html index 7ee760adc..6ec7158a0 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Conv3d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Conv3d.html @@ -8,7 +8,7 @@ - mlx.nn.Conv3d — MLX 0.23.2 documentation + mlx.nn.Conv3d — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose1d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose1d.html index 7d35691c1..0e77a0950 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose1d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose1d.html @@ -8,7 +8,7 @@ - mlx.nn.ConvTranspose1d — MLX 0.23.2 documentation + mlx.nn.ConvTranspose1d — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose2d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose2d.html index b13c3f870..0827388ec 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose2d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose2d.html @@ -8,7 +8,7 @@ - mlx.nn.ConvTranspose2d — MLX 0.23.2 documentation + mlx.nn.ConvTranspose2d — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose3d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose3d.html index 72c938eb9..b1b21413a 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose3d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose3d.html @@ -8,7 +8,7 @@ - mlx.nn.ConvTranspose3d — MLX 0.23.2 documentation + mlx.nn.ConvTranspose3d — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout.html index 0a3d27922..d87b5b1d5 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout.html @@ -8,7 +8,7 @@ - mlx.nn.Dropout — MLX 0.23.2 documentation + mlx.nn.Dropout — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout2d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout2d.html index 5b4364c0c..4a099d593 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout2d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout2d.html @@ -8,7 +8,7 @@ - mlx.nn.Dropout2d — MLX 0.23.2 documentation + mlx.nn.Dropout2d — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout3d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout3d.html index 8e6fdf52a..6ab732148 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout3d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout3d.html @@ -8,7 +8,7 @@ - mlx.nn.Dropout3d — MLX 0.23.2 documentation + mlx.nn.Dropout3d — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.ELU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.ELU.html index 4da40291f..47b8f987b 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.ELU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.ELU.html @@ -8,7 +8,7 @@ - mlx.nn.ELU — MLX 0.23.2 documentation + mlx.nn.ELU — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Embedding.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Embedding.html index 46f8562a5..b30bee9ca 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Embedding.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Embedding.html @@ -8,7 +8,7 @@ - mlx.nn.Embedding — MLX 0.23.2 documentation + mlx.nn.Embedding — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.GELU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.GELU.html index 9a9b4e939..993ed622a 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.GELU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.GELU.html @@ -8,7 +8,7 @@ - mlx.nn.GELU — MLX 0.23.2 documentation + mlx.nn.GELU — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.GLU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.GLU.html index d8436c33e..6ae2ef963 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.GLU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.GLU.html @@ -8,7 +8,7 @@ - mlx.nn.GLU — MLX 0.23.2 documentation + mlx.nn.GLU — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.GRU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.GRU.html index af8146b1e..b5dcc57c5 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.GRU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.GRU.html @@ -8,7 +8,7 @@ - mlx.nn.GRU — MLX 0.23.2 documentation + mlx.nn.GRU — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - 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mlx.nn.MultiHeadAttention — MLX 0.23.2 documentation + mlx.nn.MultiHeadAttention — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.PReLU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.PReLU.html index 8ff3269b4..a7be3bca3 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.PReLU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.PReLU.html @@ -8,7 +8,7 @@ - mlx.nn.PReLU — MLX 0.23.2 documentation + mlx.nn.PReLU — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.QuantizedEmbedding.html b/docs/build/html/python/nn/_autosummary/mlx.nn.QuantizedEmbedding.html index 1d6e00cd3..34d83e0c9 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.QuantizedEmbedding.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.QuantizedEmbedding.html @@ -8,7 +8,7 @@ - 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mlx.nn.Softmax — MLX 0.23.2 documentation + mlx.nn.Softmax — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Softmin.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Softmin.html index 491c9cb0a..f11764ccc 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Softmin.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Softmin.html @@ -8,7 +8,7 @@ - mlx.nn.Softmin — MLX 0.23.2 documentation + mlx.nn.Softmin — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Softplus.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Softplus.html index d73e3f7e1..e1c48caf2 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Softplus.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Softplus.html @@ -8,7 +8,7 @@ - mlx.nn.Softplus — MLX 0.23.2 documentation + mlx.nn.Softplus — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Softshrink.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Softshrink.html index 6308b12ed..e2448db46 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Softshrink.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Softshrink.html @@ -8,7 +8,7 @@ - mlx.nn.Softshrink — MLX 0.23.2 documentation + mlx.nn.Softshrink — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Softsign.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Softsign.html index 2aaf28172..8f79bfc45 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Softsign.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Softsign.html @@ -8,7 +8,7 @@ - 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mlx.nn.Tanh — MLX 0.23.2 documentation + mlx.nn.Tanh — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Transformer.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Transformer.html index d6771e3cc..c6a926f78 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Transformer.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Transformer.html @@ -8,7 +8,7 @@ - mlx.nn.Transformer — MLX 0.23.2 documentation + mlx.nn.Transformer — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Upsample.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Upsample.html index 9da936a12..14727e140 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Upsample.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Upsample.html @@ -8,7 +8,7 @@ - mlx.nn.Upsample — MLX 0.23.2 documentation + mlx.nn.Upsample — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.init.constant.html b/docs/build/html/python/nn/_autosummary/mlx.nn.init.constant.html index dcd4d820e..0c7ea1abf 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.init.constant.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.init.constant.html @@ -8,7 +8,7 @@ - mlx.nn.init.constant — MLX 0.23.2 documentation + mlx.nn.init.constant — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.init.glorot_normal.html b/docs/build/html/python/nn/_autosummary/mlx.nn.init.glorot_normal.html index cf666b5a2..9373d4de8 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.init.glorot_normal.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.init.glorot_normal.html @@ -8,7 +8,7 @@ - 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mlx.nn.init.identity — MLX 0.23.2 documentation + mlx.nn.init.identity — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.init.normal.html b/docs/build/html/python/nn/_autosummary/mlx.nn.init.normal.html index bb6e64cfb..c5ceae59f 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.init.normal.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.init.normal.html @@ -8,7 +8,7 @@ - mlx.nn.init.normal — MLX 0.23.2 documentation + mlx.nn.init.normal — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.init.uniform.html b/docs/build/html/python/nn/_autosummary/mlx.nn.init.uniform.html index 89f2d34a1..b0469de3c 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.init.uniform.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.init.uniform.html @@ -8,7 +8,7 @@ - mlx.nn.init.uniform — MLX 0.23.2 documentation + mlx.nn.init.uniform — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.celu.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.celu.html index c4cc22707..64dfec692 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.celu.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.celu.html @@ -8,7 +8,7 @@ - mlx.nn.celu — MLX 0.23.2 documentation + mlx.nn.celu — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.elu.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.elu.html index b12968060..1ac3cc1a2 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.elu.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.elu.html @@ -8,7 +8,7 @@ - mlx.nn.elu — MLX 0.23.2 documentation + mlx.nn.elu — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu.html index 58e1e32e0..b886eb192 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu.html @@ -8,7 +8,7 @@ - mlx.nn.gelu — MLX 0.23.2 documentation + mlx.nn.gelu — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_approx.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_approx.html index 0d40c6063..d9df26978 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_approx.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_approx.html @@ -8,7 +8,7 @@ - mlx.nn.gelu_approx — MLX 0.23.2 documentation + mlx.nn.gelu_approx — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_fast_approx.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_fast_approx.html index b56d4fe16..8c27c708d 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_fast_approx.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_fast_approx.html @@ -8,7 +8,7 @@ - mlx.nn.gelu_fast_approx — MLX 0.23.2 documentation + mlx.nn.gelu_fast_approx — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.glu.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.glu.html index 58b4c0b07..7d82e8b6b 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.glu.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.glu.html @@ -8,7 +8,7 @@ - mlx.nn.glu — MLX 0.23.2 documentation + mlx.nn.glu — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hard_shrink.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hard_shrink.html index d52d01a99..0ebc4756f 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hard_shrink.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hard_shrink.html @@ -8,7 +8,7 @@ - mlx.nn.hard_shrink — MLX 0.23.2 documentation + mlx.nn.hard_shrink — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hard_tanh.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hard_tanh.html index a02b9e2a5..1e3c4eef3 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hard_tanh.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hard_tanh.html @@ -8,7 +8,7 @@ - mlx.nn.hard_tanh — MLX 0.23.2 documentation + mlx.nn.hard_tanh — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hardswish.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hardswish.html index 05934c5a2..0fd000a15 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hardswish.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hardswish.html @@ -8,7 +8,7 @@ - mlx.nn.hardswish — MLX 0.23.2 documentation + mlx.nn.hardswish — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.leaky_relu.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.leaky_relu.html index 918bc91d0..414ecd5bd 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.leaky_relu.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.leaky_relu.html @@ -8,7 +8,7 @@ - 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Home + diff --git a/docs/build/html/python/optimizers.html b/docs/build/html/python/optimizers.html index 6afc8d3bd..7b6c00809 100644 --- a/docs/build/html/python/optimizers.html +++ b/docs/build/html/python/optimizers.html @@ -8,7 +8,7 @@ - Optimizers — MLX 0.23.2 documentation + Optimizers — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.AdaDelta.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.AdaDelta.html index d68f5149b..0211b3d73 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.AdaDelta.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.AdaDelta.html @@ -8,7 +8,7 @@ - mlx.optimizers.AdaDelta — MLX 0.23.2 documentation + mlx.optimizers.AdaDelta — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adafactor.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adafactor.html index 6b5897979..a3a3548fb 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adafactor.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adafactor.html @@ -8,7 +8,7 @@ - mlx.optimizers.Adafactor — MLX 0.23.2 documentation + mlx.optimizers.Adafactor — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adagrad.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adagrad.html index 0be13467c..9a8b7b3a7 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adagrad.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adagrad.html @@ -8,7 +8,7 @@ - mlx.optimizers.Adagrad — MLX 0.23.2 documentation + mlx.optimizers.Adagrad — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - 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mlx.optimizers.Lion — MLX 0.23.2 documentation + mlx.optimizers.Lion — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.apply_gradients.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.apply_gradients.html index a93f4a99f..b1a4a199f 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.apply_gradients.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.apply_gradients.html @@ -8,7 +8,7 @@ - mlx.optimizers.Optimizer.apply_gradients — MLX 0.23.2 documentation + mlx.optimizers.Optimizer.apply_gradients — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.init.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.init.html index d931fc6f9..f3f08aed3 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.init.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.init.html @@ -8,7 +8,7 @@ - mlx.optimizers.Optimizer.init — MLX 0.23.2 documentation + mlx.optimizers.Optimizer.init — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.state.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.state.html index 46d861c40..2cb4205ac 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.state.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.state.html @@ -8,7 +8,7 @@ - mlx.optimizers.Optimizer.state — MLX 0.23.2 documentation + mlx.optimizers.Optimizer.state — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.update.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.update.html index 2517d6bd9..fda351043 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.update.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.update.html @@ -8,7 +8,7 @@ - mlx.optimizers.Optimizer.update — MLX 0.23.2 documentation + mlx.optimizers.Optimizer.update — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.RMSprop.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.RMSprop.html index 9e3a47f3f..66570f379 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.RMSprop.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.RMSprop.html @@ -8,7 +8,7 @@ - mlx.optimizers.RMSprop — MLX 0.23.2 documentation + mlx.optimizers.RMSprop — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.SGD.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.SGD.html index 2e31c12e1..cc98a02e7 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.SGD.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.SGD.html @@ -8,7 +8,7 @@ - mlx.optimizers.SGD — MLX 0.23.2 documentation + mlx.optimizers.SGD — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.cosine_decay.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.cosine_decay.html index 89f21201f..440025c14 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.cosine_decay.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.cosine_decay.html @@ -8,7 +8,7 @@ - mlx.optimizers.cosine_decay — MLX 0.23.2 documentation + mlx.optimizers.cosine_decay — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.exponential_decay.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.exponential_decay.html index b82a39b2d..931cf192f 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.exponential_decay.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.exponential_decay.html @@ -8,7 +8,7 @@ - mlx.optimizers.exponential_decay — MLX 0.23.2 documentation + mlx.optimizers.exponential_decay — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.join_schedules.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.join_schedules.html index 1168b2543..2cf312735 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.join_schedules.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.join_schedules.html @@ -8,7 +8,7 @@ - mlx.optimizers.join_schedules — MLX 0.23.2 documentation + mlx.optimizers.join_schedules — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -138,8 +138,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + @@ -920,9 +920,9 @@ that indicates when to transition between schedules.

                  Example

                  -
                  >>> warmup = optim.linear_schedule(0, 1e-1, steps=10)
+
                  >>> linear = optim.linear_schedule(0, 1e-1, steps=10)
 >>> cosine = optim.cosine_decay(1e-1, 200)
->>> lr_schedule = optim.join_schedules([warmup, cosine], [10])
+>>> lr_schedule = optim.join_schedules([linear, cosine], [10])
 >>> optimizer = optim.Adam(learning_rate=lr_schedule)
 >>> optimizer.learning_rate
 array(0.0, dtype=float32)
diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.linear_schedule.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.linear_schedule.html
index 7ac34f388..af05533ae 100644
--- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.linear_schedule.html
+++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.linear_schedule.html
@@ -8,7 +8,7 @@
     
     
 
-    mlx.optimizers.linear_schedule — MLX 0.23.2 documentation
+    mlx.optimizers.linear_schedule — MLX 0.24.0 documentation
   
   
   
@@ -36,7 +36,7 @@
 
   
 
-    
+    
     
     
     
@@ -137,8 +137,8 @@
       
     
     
-    MLX 0.23.2 documentation - Home
-    
+    MLX 0.24.0 documentation - Home
+    
   
   
 
                  
@@ -918,8 +918,8 @@ document.write(`
 
 
 
                  Example
                  
-
                  >>> warmup = optim.linear_schedule(0, 1e-1, 100)
->>> optimizer = optim.Adam(learning_rate=warmup)
+
                  >>> lr_schedule = optim.linear_schedule(0, 1e-1, 100)
+>>> optimizer = optim.Adam(learning_rate=lr_schedule)
 >>> optimizer.learning_rate
 array(0.0, dtype=float32)
 >>> for _ in range(101): optimizer.update({}, {})
diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.step_decay.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.step_decay.html
index 11d5a4d84..d56b37aaf 100644
--- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.step_decay.html
+++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.step_decay.html
@@ -8,7 +8,7 @@
     
     
 
-    mlx.optimizers.step_decay — MLX 0.23.2 documentation
+    mlx.optimizers.step_decay — MLX 0.24.0 documentation
   
   
   
@@ -36,7 +36,7 @@
 
   
 
-    
+    
     
     
     
@@ -137,8 +137,8 @@
       
     
     
-    MLX 0.23.2 documentation - Home
-    
+    MLX 0.24.0 documentation - Home
+    
   
   
 
                  
diff --git a/docs/build/html/python/optimizers/common_optimizers.html b/docs/build/html/python/optimizers/common_optimizers.html
index c2afaeeaa..4a3487ff6 100644
--- a/docs/build/html/python/optimizers/common_optimizers.html
+++ b/docs/build/html/python/optimizers/common_optimizers.html
@@ -8,7 +8,7 @@
     
     
 
-    Common Optimizers — MLX 0.23.2 documentation
+    Common Optimizers — MLX 0.24.0 documentation
   
   
   
@@ -36,7 +36,7 @@
 
   
 
-    
+    
     
     
     
@@ -138,8 +138,8 @@
       
     
     
-    MLX 0.23.2 documentation - Home
-    
+    MLX 0.24.0 documentation - Home
+    
   
   
 
                  
diff --git a/docs/build/html/python/optimizers/optimizer.html b/docs/build/html/python/optimizers/optimizer.html
index 0f4647b2b..41d285b0e 100644
--- a/docs/build/html/python/optimizers/optimizer.html
+++ b/docs/build/html/python/optimizers/optimizer.html
@@ -8,7 +8,7 @@
     
     
 
-    Optimizer — MLX 0.23.2 documentation
+    Optimizer — MLX 0.24.0 documentation
   
   
   
@@ -36,7 +36,7 @@
 
   
 
-    
+    
     
     
     
@@ -137,8 +137,8 @@
       
     
     
-    MLX 0.23.2 documentation - Home
-    
+    MLX 0.24.0 documentation - Home
+    
   
   
 
                  
diff --git a/docs/build/html/python/optimizers/schedulers.html b/docs/build/html/python/optimizers/schedulers.html
index c19690572..400a07c45 100644
--- a/docs/build/html/python/optimizers/schedulers.html
+++ b/docs/build/html/python/optimizers/schedulers.html
@@ -8,7 +8,7 @@
     
     
 
-    Schedulers — MLX 0.23.2 documentation
+    Schedulers — MLX 0.24.0 documentation
   
   
   
@@ -36,7 +36,7 @@
 
   
 
-    
+    
     
     
     
@@ -138,8 +138,8 @@
       
     
     
-    MLX 0.23.2 documentation - Home
-    
+    MLX 0.24.0 documentation - Home
+    
   
   
 
                  
diff --git a/docs/build/html/python/random.html b/docs/build/html/python/random.html
index 77b7bbbe6..6d1117114 100644
--- a/docs/build/html/python/random.html
+++ b/docs/build/html/python/random.html
@@ -8,7 +8,7 @@
     
     
 
-    Random — MLX 0.23.2 documentation
+    Random — MLX 0.24.0 documentation
   
   
   
@@ -36,7 +36,7 @@
 
   
 
-    
+    
     
     
     
@@ -137,8 +137,8 @@
       
     
     
-    MLX 0.23.2 documentation - Home
-    
+    MLX 0.24.0 documentation - Home
+    
   
   
 
                  
diff --git a/docs/build/html/python/transforms.html b/docs/build/html/python/transforms.html
index fef901123..04f918472 100644
--- a/docs/build/html/python/transforms.html
+++ b/docs/build/html/python/transforms.html
@@ -8,7 +8,7 @@
     
     
 
-    Transforms — MLX 0.23.2 documentation
+    Transforms — MLX 0.24.0 documentation
   
   
   
@@ -36,7 +36,7 @@
 
   
 
-    
+    
     
     
     
@@ -137,8 +137,8 @@
       
     
     
-    MLX 0.23.2 documentation - Home
-    
+    MLX 0.24.0 documentation - Home
+
                  diff --git a/docs/build/html/python/tree_utils.html b/docs/build/html/python/tree_utils.html index c11d99694..5b07ee42d 100644 --- a/docs/build/html/python/tree_utils.html +++ b/docs/build/html/python/tree_utils.html @@ -8,7 +8,7 @@ - Tree Utils — MLX 0.23.2 documentation + Tree Utils — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/scheduler_8h_source.html b/docs/build/html/scheduler_8h_source.html index b77031461..5948eed86 100644 --- a/docs/build/html/scheduler_8h_source.html +++ b/docs/build/html/scheduler_8h_source.html @@ -124,92 +124,90 @@ $(function(){initNavTree('scheduler_8h_source.html',''); initResizable(true); })
                  16namespace mlx::core::scheduler {
                  17
                  -
                  18struct StreamThread {
                  +
                  18struct StreamThread {
                  19 std::mutex mtx;
                  20 std::queue<std::function<void()>> q;
                  21 std::condition_variable cond;
                  22 bool stop;
                  -
                  23 Stream stream;
                  -
                  24 std::thread thread;
                  -
                  25
                  -
                  -
                  26 StreamThread(Stream stream)
                  -
                  27 : stop(false), stream(stream), thread(&StreamThread::thread_fn, this) {
                  -
                  28 metal::new_stream(stream);
                  -
                  29 }
                  +
                  23 std::thread thread;
                  +
                  24
                  +
                  25 StreamThread() : stop(false), thread(&StreamThread::thread_fn, this) {}
                  +
                  26
                  +
                  +
                  27 ~StreamThread() {
                  +
                  28 {
                  +
                  29 std::lock_guard<std::mutex> lk(mtx);
                  +
                  30 stop = true;
                  +
                  31 }
                  +
                  32 cond.notify_one();
                  +
                  33 thread.join();
                  +
                  34 }
                  -
                  30
                  -
                  -
                  31 ~StreamThread() {
                  -
                  32 synchronize(stream);
                  -
                  33 {
                  -
                  34 std::lock_guard<std::mutex> lk(mtx);
                  -
                  35 stop = true;
                  -
                  36 }
                  -
                  37 cond.notify_one();
                  -
                  38 thread.join();
                  -
                  39 }
                  +
                  35
                  +
                  +
                  36 void thread_fn() {
                  +
                  37 while (true) {
                  +
                  38 std::function<void()> task;
                  +
                  39 {
                  +
                  40 std::unique_lock<std::mutex> lk(mtx);
                  +
                  41 cond.wait(lk, [this] { return !this->q.empty() || this->stop; });
                  +
                  42 if (q.empty() && stop) {
                  +
                  43 return;
                  +
                  44 }
                  +
                  45 task = std::move(q.front());
                  +
                  46 q.pop();
                  +
                  47 }
                  +
                  48
                  +
                  49 task();
                  +
                  50 }
                  +
                  51 }
                  -
                  40
                  -
                  -
                  41 void thread_fn() {
                  -
                  42 while (true) {
                  -
                  43 std::function<void()> task;
                  -
                  44 {
                  -
                  45 std::unique_lock<std::mutex> lk(mtx);
                  -
                  46 cond.wait(lk, [this] { return !this->q.empty() || this->stop; });
                  -
                  47 if (q.empty() && stop) {
                  -
                  48 return;
                  -
                  49 }
                  -
                  50 task = std::move(q.front());
                  -
                  51 q.pop();
                  -
                  52 }
                  -
                  53
                  -
                  54 task();
                  -
                  55 }
                  -
                  56 }
                  +
                  52
                  +
                  53 template <typename F>
                  +
                  +
                  54 void enqueue(F&& f) {
                  +
                  55 {
                  +
                  56 std::lock_guard<std::mutex> lk(mtx);
                  +
                  57 if (stop) {
                  +
                  58 throw std::runtime_error(
                  +
                  59 "Cannot enqueue work after stream is stopped.");
                  +
                  60 }
                  +
                  61 q.emplace(std::forward<F>(f));
                  +
                  62 }
                  +
                  63 cond.notify_one();
                  +
                  64 }
                  -
                  57
                  -
                  58 template <typename F>
                  -
                  -
                  59 void enqueue(F&& f) {
                  -
                  60 {
                  -
                  61 std::lock_guard<std::mutex> lk(mtx);
                  -
                  62 if (stop) {
                  -
                  63 throw std::runtime_error(
                  -
                  64 "Cannot enqueue work after stream is stopped.");
                  -
                  65 }
                  -
                  66 q.emplace(std::forward<F>(f));
                  -
                  67 }
                  -
                  68 cond.notify_one();
                  -
                  69 }
                  +
                  65};
                  -
                  70};
                  +
                  66
                  +
                  +
                  67class Scheduler {
                  +
                  68 public:
                  +
                  +
                  69 Scheduler() : n_active_tasks_(0) {
                  +
                  70 if (metal::is_available()) {
                  +
                  71 default_streams_.insert({Device::gpu, new_stream(Device::gpu)});
                  +
                  72 }
                  +
                  73 default_streams_.insert({Device::cpu, new_stream(Device::cpu)});
                  +
                  74 }
                  -
                  71
                  -
                  -
                  72class Scheduler {
                  -
                  73 public:
                  -
                  -
                  74 Scheduler() : n_active_tasks_(0) {
                  -
                  75 if (metal::is_available()) {
                  -
                  76 default_streams_.insert({Device::gpu, new_stream(Device::gpu)});
                  -
                  77 }
                  -
                  78 default_streams_.insert({Device::cpu, new_stream(Device::cpu)});
                  -
                  79 }
                  -
                  -
                  80
                  -
                  81 // Not copyable or moveable
                  -
                  82 Scheduler(const Scheduler&) = delete;
                  -
                  83 Scheduler(Scheduler&&) = delete;
                  -
                  84 Scheduler& operator=(const Scheduler&) = delete;
                  -
                  85 Scheduler& operator=(Scheduler&&) = delete;
                  -
                  86
                  -
                  -
                  87 Stream new_stream(const Device& d) {
                  -
                  88 auto stream = Stream(streams_.size(), d);
                  -
                  89 streams_.push_back(new StreamThread{stream});
                  -
                  90 return stream;
                  +
                  75
                  +
                  76 // Not copyable or moveable
                  +
                  77 Scheduler(const Scheduler&) = delete;
                  +
                  78 Scheduler(Scheduler&&) = delete;
                  +
                  79 Scheduler& operator=(const Scheduler&) = delete;
                  +
                  80 Scheduler& operator=(Scheduler&&) = delete;
                  +
                  81
                  +
                  +
                  82 Stream new_stream(const Device& d) {
                  +
                  83 streams_.emplace_back(streams_.size(), d);
                  +
                  84 if (d == Device::gpu) {
                  +
                  85 threads_.push_back(nullptr);
                  +
                  86 metal::new_stream(streams_.back());
                  +
                  87 } else {
                  +
                  88 threads_.push_back(new StreamThread{});
                  +
                  89 }
                  +
                  90 return streams_.back();
                  91 }
                  92
                  @@ -223,7 +221,7 @@ $(function(){initNavTree('scheduler_8h_source.html',''); initResizable(true); })
                  99 Stream get_stream(int index) const {
                  -
                  100 return streams_.at(index)->stream;
                  +
                  100 return streams_.at(index);
                  101 }
                  102
                  @@ -274,69 +272,75 @@ $(function(){initNavTree('scheduler_8h_source.html',''); initResizable(true); })
                  137 ~Scheduler() {
                  138 for (auto s : streams_) {
                  -
                  139 delete s;
                  +
                  139 synchronize(s);
                  140 }
                  -
                  141 }
                  +
                  141 for (auto t : threads_) {
                  +
                  142 if (t != nullptr) {
                  +
                  143 delete t;
                  +
                  144 }
                  +
                  145 }
                  +
                  146 }
                  -
                  142
                  -
                  143 private:
                  -
                  144 int n_active_tasks_;
                  -
                  145 std::vector<StreamThread*> streams_;
                  -
                  146 std::unordered_map<Device::DeviceType, Stream> default_streams_;
                  -
                  147 std::condition_variable completion_cv;
                  -
                  148 std::mutex mtx;
                  -
                  149};
                  +
                  147
                  +
                  148 private:
                  +
                  149 int n_active_tasks_;
                  +
                  150 std::vector<StreamThread*> threads_;
                  +
                  151 std::vector<Stream> streams_;
                  +
                  152 std::unordered_map<Device::DeviceType, Stream> default_streams_;
                  +
                  153 std::condition_variable completion_cv;
                  +
                  154 std::mutex mtx;
                  +
                  155};
                  -
                  150
                  -
                  151template <typename F>
                  -
                  -
                  152void Scheduler::enqueue(const Stream& stream, F&& f) {
                  -
                  153 streams_[stream.index]->enqueue(std::forward<F>(f));
                  -
                  154}
                  +
                  156
                  +
                  157template <typename F>
                  +
                  +
                  158void Scheduler::enqueue(const Stream& stream, F&& f) {
                  +
                  159 threads_[stream.index]->enqueue(std::forward<F>(f));
                  +
                  160}
                  -
                  155
                  -
                  156Scheduler& scheduler();
                  -
                  157
                  -
                  158template <typename F>
                  -
                  -
                  159void enqueue(const Stream& stream, F&& f) {
                  -
                  160 scheduler().enqueue(stream, std::forward<F>(f));
                  -
                  161}
                  +
                  161
                  +
                  162Scheduler& scheduler();
                  +
                  163
                  +
                  164template <typename F>
                  +
                  +
                  165void enqueue(const Stream& stream, F&& f) {
                  +
                  166 scheduler().enqueue(stream, std::forward<F>(f));
                  +
                  167}
                  -
                  162
                  -
                  -
                  163inline int n_active_tasks() {
                  -
                  164 return scheduler().n_active_tasks();
                  -
                  165}
                  +
                  168
                  +
                  +
                  169inline int n_active_tasks() {
                  +
                  170 return scheduler().n_active_tasks();
                  +
                  171}
                  -
                  166
                  -
                  -
                  167inline void notify_new_task(const Stream& stream) {
                  -
                  168 scheduler().notify_new_task(stream);
                  -
                  169}
                  +
                  172
                  +
                  +
                  173inline void notify_new_task(const Stream& stream) {
                  +
                  174 scheduler().notify_new_task(stream);
                  +
                  175}
                  -
                  170
                  -
                  -
                  171inline void notify_task_completion(const Stream& stream) {
                  -
                  172 scheduler().notify_task_completion(stream);
                  -
                  173}
                  +
                  176
                  +
                  +
                  177inline void notify_task_completion(const Stream& stream) {
                  +
                  178 scheduler().notify_task_completion(stream);
                  +
                  179}
                  -
                  174
                  -
                  -
                  175inline void wait_for_one() {
                  -
                  176 scheduler().wait_for_one();
                  -
                  177}
                  +
                  180
                  +
                  +
                  181inline void wait_for_one() {
                  +
                  182 scheduler().wait_for_one();
                  +
                  183}
                  -
                  178
                  -
                  179} // namespace mlx::core::scheduler
                  +
                  184
                  +
                  185} // namespace mlx::core::scheduler
                  -
                  mlx::core::scheduler::Scheduler
                  Definition scheduler.h:72
                  +
                  mlx::core::scheduler::Scheduler
                  Definition scheduler.h:67
                  mlx::core::scheduler::Scheduler::wait_for_one
                  void wait_for_one()
                  Definition scheduler.h:127
                  mlx::core::scheduler::Scheduler::operator=
                  Scheduler & operator=(Scheduler &&)=delete
                  -
                  mlx::core::scheduler::Scheduler::enqueue
                  void enqueue(const Stream &stream, F &&f)
                  Definition scheduler.h:152
                  -
                  mlx::core::scheduler::Scheduler::new_stream
                  Stream new_stream(const Device &d)
                  Definition scheduler.h:87
                  +
                  mlx::core::scheduler::Scheduler::enqueue
                  void enqueue(const Stream &stream, F &&f)
                  Definition scheduler.h:158
                  +
                  mlx::core::scheduler::Scheduler::new_stream
                  Stream new_stream(const Device &d)
                  Definition scheduler.h:82
                  mlx::core::scheduler::Scheduler::get_default_stream
                  Stream get_default_stream(const Device &d) const
                  Definition scheduler.h:96
                  -
                  mlx::core::scheduler::Scheduler::Scheduler
                  Scheduler()
                  Definition scheduler.h:74
                  +
                  mlx::core::scheduler::Scheduler::Scheduler
                  Scheduler()
                  Definition scheduler.h:69
                  mlx::core::scheduler::Scheduler::n_active_tasks
                  int n_active_tasks() const
                  Definition scheduler.h:123
                  mlx::core::scheduler::Scheduler::Scheduler
                  Scheduler(const Scheduler &)=delete
                  mlx::core::scheduler::Scheduler::~Scheduler
                  ~Scheduler()
                  Definition scheduler.h:137
                  @@ -352,11 +356,11 @@ $(function(){initNavTree('scheduler_8h_source.html',''); initResizable(true); })
                  mlx::core::metal::new_stream
                  void new_stream(Stream stream)
                  mlx::core::scheduler
                  Definition scheduler.h:16
                  -
                  mlx::core::scheduler::notify_task_completion
                  void notify_task_completion(const Stream &stream)
                  Definition scheduler.h:171
                  -
                  mlx::core::scheduler::notify_new_task
                  void notify_new_task(const Stream &stream)
                  Definition scheduler.h:167
                  -
                  mlx::core::scheduler::wait_for_one
                  void wait_for_one()
                  Definition scheduler.h:175
                  -
                  mlx::core::scheduler::n_active_tasks
                  int n_active_tasks()
                  Definition scheduler.h:163
                  -
                  mlx::core::scheduler::enqueue
                  void enqueue(const Stream &stream, F &&f)
                  Definition scheduler.h:159
                  +
                  mlx::core::scheduler::notify_task_completion
                  void notify_task_completion(const Stream &stream)
                  Definition scheduler.h:177
                  +
                  mlx::core::scheduler::notify_new_task
                  void notify_new_task(const Stream &stream)
                  Definition scheduler.h:173
                  +
                  mlx::core::scheduler::wait_for_one
                  void wait_for_one()
                  Definition scheduler.h:181
                  +
                  mlx::core::scheduler::n_active_tasks
                  int n_active_tasks()
                  Definition scheduler.h:169
                  +
                  mlx::core::scheduler::enqueue
                  void enqueue(const Stream &stream, F &&f)
                  Definition scheduler.h:165
                  mlx::core::scheduler::scheduler
                  Scheduler & scheduler()
                  mlx::core::synchronize
                  void synchronize()
                  @@ -368,15 +372,14 @@ $(function(){initNavTree('scheduler_8h_source.html',''); initResizable(true); })
                  mlx::core::Stream::device
                  Device device
                  Definition stream.h:11
                  mlx::core::Stream::index
                  int index
                  Definition stream.h:10
                  mlx::core::scheduler::StreamThread
                  Definition scheduler.h:18
                  -
                  mlx::core::scheduler::StreamThread::thread_fn
                  void thread_fn()
                  Definition scheduler.h:41
                  -
                  mlx::core::scheduler::StreamThread::thread
                  std::thread thread
                  Definition scheduler.h:24
                  +
                  mlx::core::scheduler::StreamThread::thread_fn
                  void thread_fn()
                  Definition scheduler.h:36
                  +
                  mlx::core::scheduler::StreamThread::StreamThread
                  StreamThread()
                  Definition scheduler.h:25
                  +
                  mlx::core::scheduler::StreamThread::thread
                  std::thread thread
                  Definition scheduler.h:23
                  mlx::core::scheduler::StreamThread::stop
                  bool stop
                  Definition scheduler.h:22
                  -
                  mlx::core::scheduler::StreamThread::enqueue
                  void enqueue(F &&f)
                  Definition scheduler.h:59
                  +
                  mlx::core::scheduler::StreamThread::enqueue
                  void enqueue(F &&f)
                  Definition scheduler.h:54
                  mlx::core::scheduler::StreamThread::cond
                  std::condition_variable cond
                  Definition scheduler.h:21
                  mlx::core::scheduler::StreamThread::mtx
                  std::mutex mtx
                  Definition scheduler.h:19
                  -
                  mlx::core::scheduler::StreamThread::~StreamThread
                  ~StreamThread()
                  Definition scheduler.h:31
                  -
                  mlx::core::scheduler::StreamThread::stream
                  Stream stream
                  Definition scheduler.h:23
                  -
                  mlx::core::scheduler::StreamThread::StreamThread
                  StreamThread(Stream stream)
                  Definition scheduler.h:26
                  +
                  mlx::core::scheduler::StreamThread::~StreamThread
                  ~StreamThread()
                  Definition scheduler.h:27
                  mlx::core::scheduler::StreamThread::q
                  std::queue< std::function< void()> > q
                  Definition scheduler.h:20
                  diff --git a/docs/build/html/sdpa__vector_8h.html b/docs/build/html/sdpa__vector_8h.html index 132b203a6..8c598a88c 100644 --- a/docs/build/html/sdpa__vector_8h.html +++ b/docs/build/html/sdpa__vector_8h.html @@ -114,12 +114,12 @@ $(function(){initNavTree('sdpa__vector_8h.html',''); initResizable(true); }); - - - - - - + + + + + + @@ -132,8 +132,8 @@ Variables

                  Functions

                  template<typename T, int D, int V = D>
                  void sdpa_vector (const device T *queries, const device T *keys, const device T *values, device T *out, const constant int &gqa_factor, const constant int &N, const constant size_t &k_stride, const constant size_t &v_stride, const constant float &scale, const device bool *mask, const constant int &mask_kv_seq_stride, const constant int &mask_q_seq_stride, const constant int &mask_head_stride, uint3 tid, uint3 tpg, uint simd_gid, uint simd_lid)
                   
                  template<typename T, int D, int V = D>
                  void sdpa_vector_2pass_1 (const device T *queries, const device T *keys, const device T *values, device float *out, device float *sums, device float *maxs, const constant int &gqa_factor, const constant int &N, const constant size_t &k_stride, const constant size_t &v_stride, const constant float &scale, const device bool *mask, const constant int &mask_kv_seq_stride, const constant int &mask_q_seq_stride, const constant int &mask_head_stride, uint3 tid, uint3 tpg, uint simd_gid, uint simd_lid)
                   
                  template<typename T, int D, int V = D>
                  void sdpa_vector (const device T *queries, const device T *keys, const device T *values, device T *out, const constant int &gqa_factor, const constant int &N, const constant size_t &k_head_stride, const constant size_t &k_seq_stride, const constant size_t &v_head_stride, const constant size_t &v_seq_stride, const constant float &scale, const device bool *mask, const constant int &mask_kv_seq_stride, const constant int &mask_q_seq_stride, const constant int &mask_head_stride, uint3 tid, uint3 tpg, uint simd_gid, uint simd_lid)
                   
                  template<typename T, int D, int V = D>
                  void sdpa_vector_2pass_1 (const device T *queries, const device T *keys, const device T *values, device float *out, device float *sums, device float *maxs, const constant int &gqa_factor, const constant int &N, const constant size_t &k_head_stride, const constant size_t &k_seq_stride, const constant size_t &v_head_stride, const constant size_t &v_seq_stride, const constant float &scale, const device bool *mask, const constant int &mask_kv_seq_stride, const constant int &mask_q_seq_stride, const constant int &mask_head_stride, uint3 tid, uint3 tpg, uint simd_gid, uint simd_lid)
                   
                  template<typename T, int D>
                  void sdpa_vector_2pass_2 (const device float *partials, const device float *sums, const device float *maxs, device T *out, uint3 tid, uint3 tpg, uint simd_gid, uint simd_lid)
                   
                   

                  Function Documentation

                  - -

                  ◆ sdpa_vector()

                  + +

                  ◆ sdpa_vector()

                  @@ -173,12 +173,22 @@ template<typename T, int D, int V = D>
                  - const constant size_t & k_stride, + const constant size_t & k_head_stride, - const constant size_t & v_stride, + const constant size_t & k_seq_stride, + + + + + const constant size_t & v_head_stride, + + + + + const constant size_t & v_seq_stride, @@ -230,8 +240,8 @@ template<typename T, int D, int V = D>
                  - -

                  ◆ sdpa_vector_2pass_1()

                  + +

                  ◆ sdpa_vector_2pass_1()

                  @@ -281,12 +291,22 @@ template<typename T, int D, int V = D>
                  - const constant size_t & k_stride, + const constant size_t & k_head_stride, - const constant size_t & v_stride, + const constant size_t & k_seq_stride, + + + + + const constant size_t & v_head_stride, + + + + + const constant size_t & v_seq_stride, diff --git a/docs/build/html/sdpa__vector_8h.js b/docs/build/html/sdpa__vector_8h.js index cde0ce547..95f78905f 100644 --- a/docs/build/html/sdpa__vector_8h.js +++ b/docs/build/html/sdpa__vector_8h.js @@ -1,7 +1,7 @@ var sdpa__vector_8h = [ - [ "sdpa_vector", "sdpa__vector_8h.html#aa83885125881230b6c4657dd3d0eba18", null ], - [ "sdpa_vector_2pass_1", "sdpa__vector_8h.html#ae2a4a8d17e571578ed529f4d4afe93ac", null ], + [ "sdpa_vector", "sdpa__vector_8h.html#a3289383906473a108e6aee1993a72816", null ], + [ "sdpa_vector_2pass_1", "sdpa__vector_8h.html#a1cdf4f03898ffe2800519892f7f6e0ad", null ], [ "sdpa_vector_2pass_2", "sdpa__vector_8h.html#ae1be83816bf9332277dab185aa1b58c2", null ], [ "has_mask", "sdpa__vector_8h.html#a6ed0dd113fe7d471fc0b869b8c028c81", null ], [ "query_transposed", "sdpa__vector_8h.html#a0c2c54bcc20cc4783a5040d47fa3ba81", null ] diff --git a/docs/build/html/sdpa__vector_8h_source.html b/docs/build/html/sdpa__vector_8h_source.html index dd1d152b4..8d32c8a2e 100644 --- a/docs/build/html/sdpa__vector_8h_source.html +++ b/docs/build/html/sdpa__vector_8h_source.html @@ -116,342 +116,348 @@ $(function(){initNavTree('sdpa__vector_8h_source.html',''); initResizable(true);
                  9
                  10template <typename T, int D, int V = D>
                  -
                  11[[kernel]] void sdpa_vector(
                  +
                  11[[kernel]] void sdpa_vector(
                  12 const device T* queries [[buffer(0)]],
                  13 const device T* keys [[buffer(1)]],
                  14 const device T* values [[buffer(2)]],
                  15 device T* out [[buffer(3)]],
                  16 const constant int& gqa_factor,
                  17 const constant int& N,
                  -
                  18 const constant size_t& k_stride,
                  -
                  19 const constant size_t& v_stride,
                  -
                  20 const constant float& scale,
                  -
                  21 const device bool* mask [[function_constant(has_mask)]],
                  -
                  22 const constant int& mask_kv_seq_stride [[function_constant(has_mask)]],
                  -
                  23 const constant int& mask_q_seq_stride [[function_constant(has_mask)]],
                  -
                  24 const constant int& mask_head_stride [[function_constant(has_mask)]],
                  -
                  25 uint3 tid [[threadgroup_position_in_grid]],
                  -
                  26 uint3 tpg [[threadgroups_per_grid]],
                  -
                  27 uint simd_gid [[simdgroup_index_in_threadgroup]],
                  -
                  28 uint simd_lid [[thread_index_in_simdgroup]]) {
                  -
                  29 constexpr int BN = 32;
                  -
                  30 constexpr int BD = 32;
                  -
                  31 constexpr int qk_per_thread = D / BD;
                  -
                  32 constexpr int v_per_thread = V / BD;
                  -
                  33 constexpr int inner_k_stride = BN * D;
                  -
                  34 constexpr int inner_v_stride = BN * V;
                  -
                  35
                  -
                  36 typedef float U;
                  +
                  18 const constant size_t& k_head_stride,
                  +
                  19 const constant size_t& k_seq_stride,
                  +
                  20 const constant size_t& v_head_stride,
                  +
                  21 const constant size_t& v_seq_stride,
                  +
                  22 const constant float& scale,
                  +
                  23 const device bool* mask [[function_constant(has_mask)]],
                  +
                  24 const constant int& mask_kv_seq_stride [[function_constant(has_mask)]],
                  +
                  25 const constant int& mask_q_seq_stride [[function_constant(has_mask)]],
                  +
                  26 const constant int& mask_head_stride [[function_constant(has_mask)]],
                  +
                  27 uint3 tid [[threadgroup_position_in_grid]],
                  +
                  28 uint3 tpg [[threadgroups_per_grid]],
                  +
                  29 uint simd_gid [[simdgroup_index_in_threadgroup]],
                  +
                  30 uint simd_lid [[thread_index_in_simdgroup]]) {
                  +
                  31 constexpr int BN = 32;
                  +
                  32 constexpr int BD = 32;
                  +
                  33 constexpr int qk_per_thread = D / BD;
                  +
                  34 constexpr int v_per_thread = V / BD;
                  +
                  35 int inner_k_stride = BN * int(k_seq_stride);
                  +
                  36 int inner_v_stride = BN * int(v_seq_stride);
                  37
                  -
                  38 thread U q[qk_per_thread];
                  -
                  39 thread U k[qk_per_thread];
                  -
                  40 thread U o[v_per_thread];
                  -
                  41
                  -
                  42 threadgroup U outputs[BN * BD];
                  -
                  43 threadgroup U max_scores[BN];
                  -
                  44 threadgroup U sum_exp_scores[BN];
                  -
                  45
                  -
                  46 // Adjust positions
                  -
                  47 const int head_idx = tid.x;
                  -
                  48 const int q_seq_idx = tid.y;
                  -
                  49 const int kv_head_idx = head_idx / gqa_factor;
                  -
                  50 const int o_offset = tpg.x * q_seq_idx + head_idx;
                  -
                  51 const int q_offset =
                  -
                  52 query_transposed ? o_offset : head_idx * tpg.y + q_seq_idx;
                  -
                  53 queries += q_offset * D + simd_lid * qk_per_thread;
                  -
                  54 keys += kv_head_idx * k_stride + simd_gid * D + simd_lid * qk_per_thread;
                  -
                  55 values += kv_head_idx * v_stride + simd_gid * V + simd_lid * v_per_thread;
                  -
                  56 if (has_mask) {
                  -
                  57 mask += head_idx * mask_head_stride + simd_gid * mask_kv_seq_stride +
                  -
                  58 q_seq_idx * mask_q_seq_stride;
                  -
                  59 }
                  -
                  60
                  -
                  61 out += o_offset * V + simd_gid * v_per_thread;
                  -
                  62
                  -
                  63 // Read the query and 0 the output accumulator
                  -
                  64 for (int i = 0; i < qk_per_thread; i++) {
                  -
                  65 q[i] = static_cast<U>(scale) * queries[i];
                  -
                  66 }
                  -
                  67 for (int i = 0; i < v_per_thread; i++) {
                  -
                  68 o[i] = 0;
                  -
                  69 }
                  -
                  70
                  -
                  71 U max_score = -INFINITY;
                  -
                  72 U sum_exp_score = 0;
                  -
                  73
                  -
                  74 // For each key
                  -
                  75 for (int i = simd_gid; i < N; i += BN) {
                  -
                  76 if (!has_mask || mask[0]) {
                  -
                  77 // Read the key
                  -
                  78 for (int j = 0; j < qk_per_thread; j++) {
                  -
                  79 k[j] = keys[j];
                  -
                  80 }
                  -
                  81
                  -
                  82 // Compute the i-th score
                  -
                  83 U score = 0;
                  -
                  84 for (int j = 0; j < qk_per_thread; j++) {
                  -
                  85 score += q[j] * k[j];
                  -
                  86 }
                  -
                  87 score = simd_sum(score);
                  -
                  88
                  -
                  89 // Update the accumulators
                  -
                  90 U new_max = max(max_score, score);
                  -
                  91 U factor = fast::exp(max_score - new_max);
                  -
                  92 U exp_score = fast::exp(score - new_max);
                  -
                  93
                  -
                  94 max_score = new_max;
                  -
                  95 sum_exp_score = sum_exp_score * factor + exp_score;
                  -
                  96
                  -
                  97 // Update the output accumulator
                  -
                  98 for (int j = 0; j < v_per_thread; j++) {
                  -
                  99 o[j] = o[j] * factor + exp_score * values[j];
                  -
                  100 }
                  -
                  101 }
                  -
                  102
                  -
                  103 // Move the pointers to the next kv
                  -
                  104 keys += inner_k_stride;
                  -
                  105 values += inner_v_stride;
                  -
                  106 if (has_mask) {
                  -
                  107 mask += BN * mask_kv_seq_stride;
                  -
                  108 }
                  -
                  109 }
                  -
                  110
                  -
                  111 // Each thread has a partial part of the output so we need to combine them.
                  -
                  112
                  -
                  113 // First let's communicate the max and sum_exp
                  -
                  114 if (simd_lid == 0) {
                  -
                  115 max_scores[simd_gid] = max_score;
                  -
                  116 sum_exp_scores[simd_gid] = sum_exp_score;
                  -
                  117 }
                  -
                  118 threadgroup_barrier(mem_flags::mem_threadgroup);
                  -
                  119 max_score = max_scores[simd_lid];
                  -
                  120 U new_max = simd_max(max_score);
                  -
                  121 U factor = fast::exp(max_score - new_max);
                  -
                  122 sum_exp_score = simd_sum(sum_exp_scores[simd_lid] * factor);
                  -
                  123
                  -
                  124 // Now we need to aggregate all the outputs
                  -
                  125 for (int i = 0; i < v_per_thread; i++) {
                  -
                  126 outputs[simd_lid * BD + simd_gid] = o[i];
                  -
                  127 threadgroup_barrier(mem_flags::mem_threadgroup);
                  -
                  128 o[i] = simd_sum(outputs[simd_gid * BD + simd_lid] * factor) / sum_exp_score;
                  -
                  129 threadgroup_barrier(mem_flags::mem_threadgroup);
                  -
                  130 }
                  -
                  131
                  -
                  132 // And write the output
                  -
                  133 if (simd_lid == 0) {
                  -
                  134 for (int i = 0; i < v_per_thread; i++) {
                  -
                  135 out[i] = static_cast<T>(o[i]);
                  -
                  136 }
                  -
                  137 }
                  -
                  138}
                  +
                  38 typedef float U;
                  +
                  39
                  +
                  40 thread U q[qk_per_thread];
                  +
                  41 thread U k[qk_per_thread];
                  +
                  42 thread U o[v_per_thread];
                  +
                  43
                  +
                  44 threadgroup U outputs[BN * BD];
                  +
                  45 threadgroup U max_scores[BN];
                  +
                  46 threadgroup U sum_exp_scores[BN];
                  +
                  47
                  +
                  48 // Adjust positions
                  +
                  49 const int head_idx = tid.x;
                  +
                  50 const int q_seq_idx = tid.y;
                  +
                  51 const int kv_head_idx = head_idx / gqa_factor;
                  +
                  52 const int o_offset = tpg.x * q_seq_idx + head_idx;
                  +
                  53 const int q_offset =
                  +
                  54 query_transposed ? o_offset : head_idx * tpg.y + q_seq_idx;
                  +
                  55 queries += q_offset * D + simd_lid * qk_per_thread;
                  +
                  56 keys += kv_head_idx * k_head_stride + simd_gid * k_seq_stride +
                  +
                  57 simd_lid * qk_per_thread;
                  +
                  58 values += kv_head_idx * v_head_stride + simd_gid * v_seq_stride +
                  +
                  59 simd_lid * v_per_thread;
                  +
                  60 if (has_mask) {
                  +
                  61 mask += head_idx * mask_head_stride + simd_gid * mask_kv_seq_stride +
                  +
                  62 q_seq_idx * mask_q_seq_stride;
                  +
                  63 }
                  +
                  64
                  +
                  65 out += o_offset * V + simd_gid * v_per_thread;
                  +
                  66
                  +
                  67 // Read the query and 0 the output accumulator
                  +
                  68 for (int i = 0; i < qk_per_thread; i++) {
                  +
                  69 q[i] = static_cast<U>(scale) * queries[i];
                  +
                  70 }
                  +
                  71 for (int i = 0; i < v_per_thread; i++) {
                  +
                  72 o[i] = 0;
                  +
                  73 }
                  +
                  74
                  +
                  75 U max_score = -INFINITY;
                  +
                  76 U sum_exp_score = 0;
                  +
                  77
                  +
                  78 // For each key
                  +
                  79 for (int i = simd_gid; i < N; i += BN) {
                  +
                  80 if (!has_mask || mask[0]) {
                  +
                  81 // Read the key
                  +
                  82 for (int j = 0; j < qk_per_thread; j++) {
                  +
                  83 k[j] = keys[j];
                  +
                  84 }
                  +
                  85
                  +
                  86 // Compute the i-th score
                  +
                  87 U score = 0;
                  +
                  88 for (int j = 0; j < qk_per_thread; j++) {
                  +
                  89 score += q[j] * k[j];
                  +
                  90 }
                  +
                  91 score = simd_sum(score);
                  +
                  92
                  +
                  93 // Update the accumulators
                  +
                  94 U new_max = max(max_score, score);
                  +
                  95 U factor = fast::exp(max_score - new_max);
                  +
                  96 U exp_score = fast::exp(score - new_max);
                  +
                  97
                  +
                  98 max_score = new_max;
                  +
                  99 sum_exp_score = sum_exp_score * factor + exp_score;
                  +
                  100
                  +
                  101 // Update the output accumulator
                  +
                  102 for (int j = 0; j < v_per_thread; j++) {
                  +
                  103 o[j] = o[j] * factor + exp_score * values[j];
                  +
                  104 }
                  +
                  105 }
                  +
                  106
                  +
                  107 // Move the pointers to the next kv
                  +
                  108 keys += inner_k_stride;
                  +
                  109 values += inner_v_stride;
                  +
                  110 if (has_mask) {
                  +
                  111 mask += BN * mask_kv_seq_stride;
                  +
                  112 }
                  +
                  113 }
                  +
                  114
                  +
                  115 // Each thread has a partial part of the output so we need to combine them.
                  +
                  116
                  +
                  117 // First let's communicate the max and sum_exp
                  +
                  118 if (simd_lid == 0) {
                  +
                  119 max_scores[simd_gid] = max_score;
                  +
                  120 sum_exp_scores[simd_gid] = sum_exp_score;
                  +
                  121 }
                  +
                  122 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  123 max_score = max_scores[simd_lid];
                  +
                  124 U new_max = simd_max(max_score);
                  +
                  125 U factor = fast::exp(max_score - new_max);
                  +
                  126 sum_exp_score = simd_sum(sum_exp_scores[simd_lid] * factor);
                  +
                  127
                  +
                  128 // Now we need to aggregate all the outputs
                  +
                  129 for (int i = 0; i < v_per_thread; i++) {
                  +
                  130 outputs[simd_lid * BD + simd_gid] = o[i];
                  +
                  131 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  132 o[i] = simd_sum(outputs[simd_gid * BD + simd_lid] * factor) / sum_exp_score;
                  +
                  133 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  134 }
                  +
                  135
                  +
                  136 // And write the output
                  +
                  137 if (simd_lid == 0) {
                  +
                  138 for (int i = 0; i < v_per_thread; i++) {
                  +
                  139 out[i] = static_cast<T>(o[i]);
                  +
                  140 }
                  +
                  141 }
                  +
                  142}
                  -
                  139
                  -
                  140template <typename T, int D, int V = D>
                  -
                  -
                  141[[kernel]] void sdpa_vector_2pass_1(
                  -
                  142 const device T* queries [[buffer(0)]],
                  -
                  143 const device T* keys [[buffer(1)]],
                  -
                  144 const device T* values [[buffer(2)]],
                  -
                  145 device float* out [[buffer(3)]],
                  -
                  146 device float* sums [[buffer(4)]],
                  -
                  147 device float* maxs [[buffer(5)]],
                  -
                  148 const constant int& gqa_factor,
                  -
                  149 const constant int& N,
                  -
                  150 const constant size_t& k_stride,
                  -
                  151 const constant size_t& v_stride,
                  -
                  152 const constant float& scale,
                  -
                  153 const device bool* mask [[function_constant(has_mask)]],
                  -
                  154 const constant int& mask_kv_seq_stride [[function_constant(has_mask)]],
                  -
                  155 const constant int& mask_q_seq_stride [[function_constant(has_mask)]],
                  -
                  156 const constant int& mask_head_stride [[function_constant(has_mask)]],
                  -
                  157 uint3 tid [[threadgroup_position_in_grid]],
                  -
                  158 uint3 tpg [[threadgroups_per_grid]],
                  -
                  159 uint simd_gid [[simdgroup_index_in_threadgroup]],
                  -
                  160 uint simd_lid [[thread_index_in_simdgroup]]) {
                  -
                  161 constexpr int BN = 8;
                  -
                  162 constexpr int BD = 32;
                  -
                  163 constexpr int qk_per_thread = D / BD;
                  -
                  164 constexpr int v_per_thread = V / BD;
                  -
                  165 constexpr int inner_k_stride = BN * D;
                  -
                  166 constexpr int inner_v_stride = BN * V;
                  -
                  167 constexpr int blocks = 32;
                  -
                  168
                  -
                  169 typedef float U;
                  -
                  170
                  -
                  171 thread U q[qk_per_thread];
                  -
                  172 thread U k[qk_per_thread];
                  -
                  173 thread U o[v_per_thread];
                  +
                  143
                  +
                  144template <typename T, int D, int V = D>
                  +
                  +
                  145[[kernel]] void sdpa_vector_2pass_1(
                  +
                  146 const device T* queries [[buffer(0)]],
                  +
                  147 const device T* keys [[buffer(1)]],
                  +
                  148 const device T* values [[buffer(2)]],
                  +
                  149 device float* out [[buffer(3)]],
                  +
                  150 device float* sums [[buffer(4)]],
                  +
                  151 device float* maxs [[buffer(5)]],
                  +
                  152 const constant int& gqa_factor,
                  +
                  153 const constant int& N,
                  +
                  154 const constant size_t& k_head_stride,
                  +
                  155 const constant size_t& k_seq_stride,
                  +
                  156 const constant size_t& v_head_stride,
                  +
                  157 const constant size_t& v_seq_stride,
                  +
                  158 const constant float& scale,
                  +
                  159 const device bool* mask [[function_constant(has_mask)]],
                  +
                  160 const constant int& mask_kv_seq_stride [[function_constant(has_mask)]],
                  +
                  161 const constant int& mask_q_seq_stride [[function_constant(has_mask)]],
                  +
                  162 const constant int& mask_head_stride [[function_constant(has_mask)]],
                  +
                  163 uint3 tid [[threadgroup_position_in_grid]],
                  +
                  164 uint3 tpg [[threadgroups_per_grid]],
                  +
                  165 uint simd_gid [[simdgroup_index_in_threadgroup]],
                  +
                  166 uint simd_lid [[thread_index_in_simdgroup]]) {
                  +
                  167 constexpr int BN = 8;
                  +
                  168 constexpr int BD = 32;
                  +
                  169 constexpr int qk_per_thread = D / BD;
                  +
                  170 constexpr int v_per_thread = V / BD;
                  +
                  171 int inner_k_stride = BN * int(k_seq_stride);
                  +
                  172 int inner_v_stride = BN * int(v_seq_stride);
                  +
                  173 constexpr int blocks = 32;
                  174
                  -
                  175 threadgroup U outputs[BN * BD];
                  -
                  176 threadgroup U max_scores[BN];
                  -
                  177 threadgroup U sum_exp_scores[BN];
                  -
                  178
                  -
                  179 // Adjust positions
                  -
                  180 const int block_idx = tid.z;
                  -
                  181 const int head_idx = tid.x;
                  -
                  182 const int q_seq_idx = tid.y;
                  -
                  183 const int o_offset = tpg.x * q_seq_idx + head_idx;
                  -
                  184 const int q_offset =
                  -
                  185 query_transposed ? o_offset : head_idx * tpg.y + q_seq_idx;
                  -
                  186 const int kv_head_idx = head_idx / gqa_factor;
                  -
                  187
                  -
                  188 queries += q_offset * D + simd_lid * qk_per_thread;
                  -
                  189 keys += kv_head_idx * k_stride + (block_idx * BN + simd_gid) * D +
                  -
                  190 simd_lid * qk_per_thread;
                  -
                  191 values += kv_head_idx * v_stride + (block_idx * BN + simd_gid) * V +
                  -
                  192 simd_lid * v_per_thread;
                  -
                  193 out += o_offset * blocks * V + block_idx * V + simd_lid * v_per_thread;
                  -
                  194 if (has_mask) {
                  -
                  195 mask += head_idx * mask_head_stride +
                  -
                  196 (block_idx * BN + simd_gid) * mask_kv_seq_stride +
                  -
                  197 q_seq_idx * mask_q_seq_stride;
                  -
                  198 }
                  -
                  199 sums += o_offset * blocks + block_idx;
                  -
                  200 maxs += o_offset * blocks + block_idx;
                  -
                  201
                  -
                  202 // Read the query and 0 the output accumulator
                  -
                  203 for (int i = 0; i < qk_per_thread; i++) {
                  -
                  204 q[i] = static_cast<U>(scale) * queries[i];
                  -
                  205 }
                  -
                  206 for (int i = 0; i < v_per_thread; i++) {
                  -
                  207 o[i] = 0;
                  -
                  208 }
                  -
                  209
                  -
                  210 U max_score = -1e9;
                  -
                  211 U sum_exp_score = 0;
                  -
                  212
                  -
                  213 // For each key
                  -
                  214 for (int i = block_idx * BN + simd_gid; i < N; i += blocks * BN) {
                  -
                  215 if (!has_mask || mask[0]) {
                  -
                  216 // Read the key
                  -
                  217 for (int i = 0; i < qk_per_thread; i++) {
                  -
                  218 k[i] = keys[i];
                  -
                  219 }
                  -
                  220
                  -
                  221 // Compute the i-th score
                  -
                  222 U score = 0;
                  +
                  175 typedef float U;
                  +
                  176
                  +
                  177 thread U q[qk_per_thread];
                  +
                  178 thread U k[qk_per_thread];
                  +
                  179 thread U o[v_per_thread];
                  +
                  180
                  +
                  181 threadgroup U outputs[BN * BD];
                  +
                  182 threadgroup U max_scores[BN];
                  +
                  183 threadgroup U sum_exp_scores[BN];
                  +
                  184
                  +
                  185 // Adjust positions
                  +
                  186 const int block_idx = tid.z;
                  +
                  187 const int head_idx = tid.x;
                  +
                  188 const int q_seq_idx = tid.y;
                  +
                  189 const int o_offset = tpg.x * q_seq_idx + head_idx;
                  +
                  190 const int q_offset =
                  +
                  191 query_transposed ? o_offset : head_idx * tpg.y + q_seq_idx;
                  +
                  192 const int kv_head_idx = head_idx / gqa_factor;
                  +
                  193
                  +
                  194 queries += q_offset * D + simd_lid * qk_per_thread;
                  +
                  195 keys += kv_head_idx * k_head_stride +
                  +
                  196 (block_idx * BN + simd_gid) * k_seq_stride + simd_lid * qk_per_thread;
                  +
                  197 values += kv_head_idx * v_head_stride +
                  +
                  198 (block_idx * BN + simd_gid) * v_seq_stride + simd_lid * v_per_thread;
                  +
                  199 out += o_offset * blocks * V + block_idx * V + simd_lid * v_per_thread;
                  +
                  200 if (has_mask) {
                  +
                  201 mask += head_idx * mask_head_stride +
                  +
                  202 (block_idx * BN + simd_gid) * mask_kv_seq_stride +
                  +
                  203 q_seq_idx * mask_q_seq_stride;
                  +
                  204 }
                  +
                  205 sums += o_offset * blocks + block_idx;
                  +
                  206 maxs += o_offset * blocks + block_idx;
                  +
                  207
                  +
                  208 // Read the query and 0 the output accumulator
                  +
                  209 for (int i = 0; i < qk_per_thread; i++) {
                  +
                  210 q[i] = static_cast<U>(scale) * queries[i];
                  +
                  211 }
                  +
                  212 for (int i = 0; i < v_per_thread; i++) {
                  +
                  213 o[i] = 0;
                  +
                  214 }
                  +
                  215
                  +
                  216 U max_score = -1e9;
                  +
                  217 U sum_exp_score = 0;
                  +
                  218
                  +
                  219 // For each key
                  +
                  220 for (int i = block_idx * BN + simd_gid; i < N; i += blocks * BN) {
                  +
                  221 if (!has_mask || mask[0]) {
                  +
                  222 // Read the key
                  223 for (int i = 0; i < qk_per_thread; i++) {
                  -
                  224 score += q[i] * k[i];
                  +
                  224 k[i] = keys[i];
                  225 }
                  -
                  226 score = simd_sum(score);
                  -
                  227
                  -
                  228 // Update the accumulators
                  -
                  229 U new_max = max(max_score, score);
                  -
                  230 U factor = fast::exp(max_score - new_max);
                  -
                  231 U exp_score = fast::exp(score - new_max);
                  -
                  232
                  -
                  233 max_score = new_max;
                  -
                  234 sum_exp_score = sum_exp_score * factor + exp_score;
                  -
                  235
                  -
                  236 // Update the output accumulator
                  -
                  237 for (int i = 0; i < v_per_thread; i++) {
                  -
                  238 o[i] = o[i] * factor + exp_score * values[i];
                  -
                  239 }
                  -
                  240 }
                  +
                  226
                  +
                  227 // Compute the i-th score
                  +
                  228 U score = 0;
                  +
                  229 for (int i = 0; i < qk_per_thread; i++) {
                  +
                  230 score += q[i] * k[i];
                  +
                  231 }
                  +
                  232 score = simd_sum(score);
                  +
                  233
                  +
                  234 // Update the accumulators
                  +
                  235 U new_max = max(max_score, score);
                  +
                  236 U factor = fast::exp(max_score - new_max);
                  +
                  237 U exp_score = fast::exp(score - new_max);
                  +
                  238
                  +
                  239 max_score = new_max;
                  +
                  240 sum_exp_score = sum_exp_score * factor + exp_score;
                  241
                  -
                  242 // Move the pointers to the next kv
                  -
                  243 keys += blocks * inner_k_stride;
                  -
                  244 values += blocks * inner_v_stride;
                  -
                  245 if (has_mask) {
                  -
                  246 mask += BN * blocks * mask_kv_seq_stride;
                  -
                  247 }
                  -
                  248 }
                  -
                  249
                  -
                  250 // Each thread has a partial part of the output so we need to combine them.
                  -
                  251
                  -
                  252 // First let's communicate the max and sum_exp
                  -
                  253 if (simd_lid == 0) {
                  -
                  254 max_scores[simd_gid] = max_score;
                  -
                  255 sum_exp_scores[simd_gid] = sum_exp_score;
                  -
                  256 }
                  -
                  257 threadgroup_barrier(mem_flags::mem_threadgroup);
                  -
                  258 max_score = (simd_lid < BN) ? max_scores[simd_lid] : -1e9;
                  -
                  259 U new_max = simd_max(max_score);
                  -
                  260 U factor = fast::exp(max_score - new_max);
                  -
                  261 sum_exp_score = (simd_lid < BN) ? sum_exp_scores[simd_lid] : 0;
                  -
                  262 sum_exp_score = simd_sum(sum_exp_score * factor);
                  -
                  263
                  -
                  264 // Write the sum and new max
                  -
                  265 if (simd_gid == 0) {
                  -
                  266 sums[0] = sum_exp_score;
                  -
                  267 maxs[0] = new_max;
                  -
                  268 }
                  +
                  242 // Update the output accumulator
                  +
                  243 for (int i = 0; i < v_per_thread; i++) {
                  +
                  244 o[i] = o[i] * factor + exp_score * values[i];
                  +
                  245 }
                  +
                  246 }
                  +
                  247
                  +
                  248 // Move the pointers to the next kv
                  +
                  249 keys += blocks * inner_k_stride;
                  +
                  250 values += blocks * inner_v_stride;
                  +
                  251 if (has_mask) {
                  +
                  252 mask += BN * blocks * mask_kv_seq_stride;
                  +
                  253 }
                  +
                  254 }
                  +
                  255
                  +
                  256 // Each thread has a partial part of the output so we need to combine them.
                  +
                  257
                  +
                  258 // First let's communicate the max and sum_exp
                  +
                  259 if (simd_lid == 0) {
                  +
                  260 max_scores[simd_gid] = max_score;
                  +
                  261 sum_exp_scores[simd_gid] = sum_exp_score;
                  +
                  262 }
                  +
                  263 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  264 max_score = (simd_lid < BN) ? max_scores[simd_lid] : -1e9;
                  +
                  265 U new_max = simd_max(max_score);
                  +
                  266 U factor = fast::exp(max_score - new_max);
                  +
                  267 sum_exp_score = (simd_lid < BN) ? sum_exp_scores[simd_lid] : 0;
                  +
                  268 sum_exp_score = simd_sum(sum_exp_score * factor);
                  269
                  -
                  270 // Now we need to aggregate all the outputs
                  -
                  271 for (int i = 0; i < v_per_thread; i++) {
                  -
                  272 outputs[simd_lid * BN + simd_gid] =
                  -
                  273 o[i] * fast::exp(max_scores[simd_gid] - new_max);
                  -
                  274 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  270 // Write the sum and new max
                  +
                  271 if (simd_gid == 0) {
                  +
                  272 sums[0] = sum_exp_score;
                  +
                  273 maxs[0] = new_max;
                  +
                  274 }
                  275
                  -
                  276 // And write the output
                  -
                  277 if (simd_gid == 0) {
                  -
                  278 U output = outputs[simd_lid * BN];
                  -
                  279 for (int j = 1; j < BN; j++) {
                  -
                  280 output += outputs[simd_lid * BN + j];
                  -
                  281 }
                  -
                  282 out[i] = static_cast<T>(output);
                  -
                  283 }
                  -
                  284 threadgroup_barrier(mem_flags::mem_threadgroup);
                  -
                  285 }
                  -
                  286}
                  +
                  276 // Now we need to aggregate all the outputs
                  +
                  277 for (int i = 0; i < v_per_thread; i++) {
                  +
                  278 outputs[simd_lid * BN + simd_gid] =
                  +
                  279 o[i] * fast::exp(max_scores[simd_gid] - new_max);
                  +
                  280 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  281
                  +
                  282 // And write the output
                  +
                  283 if (simd_gid == 0) {
                  +
                  284 U output = outputs[simd_lid * BN];
                  +
                  285 for (int j = 1; j < BN; j++) {
                  +
                  286 output += outputs[simd_lid * BN + j];
                  +
                  287 }
                  +
                  288 out[i] = static_cast<T>(output);
                  +
                  289 }
                  +
                  290 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  291 }
                  +
                  292}
                  -
                  287
                  -
                  288template <typename T, int D>
                  -
                  -
                  289[[kernel]] void sdpa_vector_2pass_2(
                  -
                  290 const device float* partials [[buffer(0)]],
                  -
                  291 const device float* sums [[buffer(1)]],
                  -
                  292 const device float* maxs [[buffer(2)]],
                  -
                  293 device T* out [[buffer(3)]],
                  -
                  294 uint3 tid [[threadgroup_position_in_grid]],
                  -
                  295 uint3 tpg [[threadgroups_per_grid]],
                  -
                  296 uint simd_gid [[simdgroup_index_in_threadgroup]],
                  -
                  297 uint simd_lid [[thread_index_in_simdgroup]]) {
                  -
                  298 constexpr int BN = 32;
                  -
                  299 constexpr int BD = 32;
                  -
                  300 constexpr int elem_per_thread = D / BD;
                  -
                  301 constexpr int blocks = 32;
                  -
                  302
                  -
                  303 typedef float U;
                  -
                  304
                  -
                  305 thread U o[elem_per_thread];
                  -
                  306 threadgroup U outputs[BN * BD];
                  -
                  307
                  -
                  308 // Adjust positions
                  -
                  309 const int head_idx = tid.x;
                  -
                  310 const int q_seq_idx = tid.y;
                  -
                  311 const int n_heads = tpg.x;
                  -
                  312 const int q_offset = n_heads * q_seq_idx + head_idx;
                  -
                  313 partials += q_offset * blocks * D + simd_gid * D + simd_lid * elem_per_thread;
                  -
                  314 sums += q_offset * blocks;
                  -
                  315 maxs += q_offset * blocks;
                  -
                  316 out += q_offset * D + simd_gid * elem_per_thread;
                  -
                  317
                  -
                  318 // First everybody reads the max and sum_exp
                  -
                  319 U max_score = maxs[simd_lid];
                  -
                  320 U new_max = simd_max(max_score);
                  -
                  321 U factor = fast::exp(max_score - new_max);
                  -
                  322 U sum_exp_score = simd_sum(sums[simd_lid] * factor);
                  +
                  293
                  +
                  294template <typename T, int D>
                  +
                  +
                  295[[kernel]] void sdpa_vector_2pass_2(
                  +
                  296 const device float* partials [[buffer(0)]],
                  +
                  297 const device float* sums [[buffer(1)]],
                  +
                  298 const device float* maxs [[buffer(2)]],
                  +
                  299 device T* out [[buffer(3)]],
                  +
                  300 uint3 tid [[threadgroup_position_in_grid]],
                  +
                  301 uint3 tpg [[threadgroups_per_grid]],
                  +
                  302 uint simd_gid [[simdgroup_index_in_threadgroup]],
                  +
                  303 uint simd_lid [[thread_index_in_simdgroup]]) {
                  +
                  304 constexpr int BN = 32;
                  +
                  305 constexpr int BD = 32;
                  +
                  306 constexpr int elem_per_thread = D / BD;
                  +
                  307 constexpr int blocks = 32;
                  +
                  308
                  +
                  309 typedef float U;
                  +
                  310
                  +
                  311 thread U o[elem_per_thread];
                  +
                  312 threadgroup U outputs[BN * BD];
                  +
                  313
                  +
                  314 // Adjust positions
                  +
                  315 const int head_idx = tid.x;
                  +
                  316 const int q_seq_idx = tid.y;
                  +
                  317 const int n_heads = tpg.x;
                  +
                  318 const int q_offset = n_heads * q_seq_idx + head_idx;
                  +
                  319 partials += q_offset * blocks * D + simd_gid * D + simd_lid * elem_per_thread;
                  +
                  320 sums += q_offset * blocks;
                  +
                  321 maxs += q_offset * blocks;
                  +
                  322 out += q_offset * D + simd_gid * elem_per_thread;
                  323
                  -
                  324 // Now read the block into registers and then use shared memory to transpose
                  -
                  325 // it
                  -
                  326 for (int i = 0; i < elem_per_thread; i++) {
                  -
                  327 o[i] = partials[i];
                  -
                  328 }
                  -
                  329 for (int i = 0; i < elem_per_thread; i++) {
                  -
                  330 outputs[simd_lid * BD + simd_gid] = o[i];
                  -
                  331 threadgroup_barrier(mem_flags::mem_threadgroup);
                  -
                  332 o[i] = simd_sum(outputs[simd_gid * BD + simd_lid] * factor) / sum_exp_score;
                  -
                  333 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  324 // First everybody reads the max and sum_exp
                  +
                  325 U max_score = maxs[simd_lid];
                  +
                  326 U new_max = simd_max(max_score);
                  +
                  327 U factor = fast::exp(max_score - new_max);
                  +
                  328 U sum_exp_score = simd_sum(sums[simd_lid] * factor);
                  +
                  329
                  +
                  330 // Now read the block into registers and then use shared memory to transpose
                  +
                  331 // it
                  +
                  332 for (int i = 0; i < elem_per_thread; i++) {
                  +
                  333 o[i] = partials[i];
                  334 }
                  -
                  335
                  -
                  336 // And write the output
                  -
                  337 if (simd_lid == 0) {
                  -
                  338 for (int i = 0; i < elem_per_thread; i++) {
                  -
                  339 out[i] = static_cast<T>(o[i]);
                  -
                  340 }
                  -
                  341 }
                  -
                  342}
                  +
                  335 for (int i = 0; i < elem_per_thread; i++) {
                  +
                  336 outputs[simd_lid * BD + simd_gid] = o[i];
                  +
                  337 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  338 o[i] = simd_sum(outputs[simd_gid * BD + simd_lid] * factor) / sum_exp_score;
                  +
                  339 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  340 }
                  +
                  341
                  +
                  342 // And write the output
                  +
                  343 if (simd_lid == 0) {
                  +
                  344 for (int i = 0; i < elem_per_thread; i++) {
                  +
                  345 out[i] = static_cast<T>(o[i]);
                  +
                  346 }
                  +
                  347 }
                  +
                  348}
                  metal::fast::exp
                  METAL_FUNC bfloat16_t exp(bfloat16_t x)
                  Definition bf16_math.h:240
                  metal
                  Definition bf16_math.h:226
                  @@ -459,10 +465,10 @@ $(function(){initNavTree('sdpa__vector_8h_source.html',''); initResizable(true);
                  metal::simd_sum
                  METAL_FUNC bfloat16_t simd_sum(bfloat16_t data)
                  Definition bf16_math.h:378
                  metal::max
                  METAL_FUNC bfloat16_t max(bfloat16_t x, bfloat16_t y)
                  Definition bf16_math.h:232
                  query_transposed
                  constant bool query_transposed
                  Definition sdpa_vector.h:8
                  +
                  sdpa_vector_2pass_1
                  void sdpa_vector_2pass_1(const device T *queries, const device T *keys, const device T *values, device float *out, device float *sums, device float *maxs, const constant int &gqa_factor, const constant int &N, const constant size_t &k_head_stride, const constant size_t &k_seq_stride, const constant size_t &v_head_stride, const constant size_t &v_seq_stride, const constant float &scale, const device bool *mask, const constant int &mask_kv_seq_stride, const constant int &mask_q_seq_stride, const constant int &mask_head_stride, uint3 tid, uint3 tpg, uint simd_gid, uint simd_lid)
                  Definition sdpa_vector.h:145
                  +
                  sdpa_vector
                  void sdpa_vector(const device T *queries, const device T *keys, const device T *values, device T *out, const constant int &gqa_factor, const constant int &N, const constant size_t &k_head_stride, const constant size_t &k_seq_stride, const constant size_t &v_head_stride, const constant size_t &v_seq_stride, const constant float &scale, const device bool *mask, const constant int &mask_kv_seq_stride, const constant int &mask_q_seq_stride, const constant int &mask_head_stride, uint3 tid, uint3 tpg, uint simd_gid, uint simd_lid)
                  Definition sdpa_vector.h:11
                  has_mask
                  constant bool has_mask
                  Definition sdpa_vector.h:7
                  -
                  sdpa_vector
                  void sdpa_vector(const device T *queries, const device T *keys, const device T *values, device T *out, const constant int &gqa_factor, const constant int &N, const constant size_t &k_stride, const constant size_t &v_stride, const constant float &scale, const device bool *mask, const constant int &mask_kv_seq_stride, const constant int &mask_q_seq_stride, const constant int &mask_head_stride, uint3 tid, uint3 tpg, uint simd_gid, uint simd_lid)
                  Definition sdpa_vector.h:11
                  -
                  sdpa_vector_2pass_2
                  void sdpa_vector_2pass_2(const device float *partials, const device float *sums, const device float *maxs, device T *out, uint3 tid, uint3 tpg, uint simd_gid, uint simd_lid)
                  Definition sdpa_vector.h:289
                  -
                  sdpa_vector_2pass_1
                  void sdpa_vector_2pass_1(const device T *queries, const device T *keys, const device T *values, device float *out, device float *sums, device float *maxs, const constant int &gqa_factor, const constant int &N, const constant size_t &k_stride, const constant size_t &v_stride, const constant float &scale, const device bool *mask, const constant int &mask_kv_seq_stride, const constant int &mask_q_seq_stride, const constant int &mask_head_stride, uint3 tid, uint3 tpg, uint simd_gid, uint simd_lid)
                  Definition sdpa_vector.h:141
                  +
                  sdpa_vector_2pass_2
                  void sdpa_vector_2pass_2(const device float *partials, const device float *sums, const device float *maxs, device T *out, uint3 tid, uint3 tpg, uint simd_gid, uint simd_lid)
                  Definition sdpa_vector.h:295
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"sum": [77, 297], "support": 332, "svd": 202, "swapax": [78, 298], "synchron": 299, "t": 32, "take": 300, "take_along_axi": 301, "tan": 302, "tanh": [303, 416, 465], "tensordot": 304, "tensorflow": 504, "thunderbolt": 498, "tile": 305, "togeth": 6, "tolist": 79, "topk": 306, "trace": [307, 499], "train": [390, 392, 497, 498], "trainable_paramet": 391, "transform": [2, 417, 495, 497, 499, 500, 503, 505], "transpos": [80, 308], "tree": 496, "tree_flatten": 325, "tree_map": 326, "tree_map_with_path": 327, "tree_reduc": 328, "tree_unflatten": 329, "tri": 309, "tri_inv": 203, "tril": 310, "triplet_loss": 452, "triu": 311, "troubleshoot": 9, "truncated_norm": 262, "tune": 498, "type": 332, "unflatten": 312, "unfreez": 393, "unifi": 507, "uniform": [263, 426], "up": [498, 502], "updat": [340, 394, 483, 501], "update_modul": 395, "upsampl": 418, "us": [1, 2, 4, 503, 508], "usag": [2, 8, 502], "util": [325, 326, 327, 328, 329, 496, 498], "valu": 340, "value_and_grad": [313, 323], "var": [81, 314], "variabl": 4, "vector": 500, "view": [82, 315], "vjp": [1, 316], "vmap": 317, "weight": 6, "what": 503, "when": 503, "where": 318, "why": 503, "workflow": 3, "x86": 9, "xcode": 3, "you": 503, "zero": 319, "zeros_lik": 320}}) \ No newline at end of file diff --git a/docs/build/html/steel__attention_8h.html b/docs/build/html/steel__attention_8h.html index 2c984550c..06f4c56ec 100644 --- a/docs/build/html/steel__attention_8h.html +++ b/docs/build/html/steel__attention_8h.html @@ -131,9 +131,9 @@ Classes - - - + + +

                  Functions

                  template<typename T, int BQ, int BK, int BD, int WM, int WN, typename AccumType = float>
                  void attention (const device T *Q, const device T *K, const device T *V, device T *O, const constant AttnParams *params, uint simd_lane_id, uint simd_group_id, uint3 tid, uint3 lid)
                   
                  template<typename T, int BQ, int BK, int BD, int WM, int WN, typename MaskType = float, typename AccumType = float>
                  void attention (const device T *Q, const device T *K, const device T *V, device T *O, const constant AttnParams *params, const constant AttnMaskParams *mask_params, const device MaskType *mask, uint simd_lane_id, uint simd_group_id, uint3 tid, uint3 lid)
                   
                  @@ -141,15 +141,19 @@ Variables + + + +

                  Variables

                   
                  constant bool align_K
                   
                  constant bool has_mask
                   
                  constant bool do_causal
                   

                  Function Documentation

                  - -

                  ◆ attention()

                  + +

                  ◆ attention()

                  -template<typename T, int BQ, int BK, int BD, int WM, int WN, typename AccumType = float>
                  +template<typename T, int BQ, int BK, int BD, int WM, int WN, typename MaskType = float, typename AccumType = float>
                  @@ -176,6 +180,16 @@ template<typename T, int BQ, int BK, int BD, int WM, int WN, typename AccumTy + + + + + + + + + + @@ -228,6 +242,34 @@ template<typename T, int BQ, int BK, int BD, int WM, int WN, typename AccumTy
                  void attention const constant AttnParams * params,
                  const constant AttnMaskParams * mask_params,
                  const device MaskType * mask,
                  +
                  +
                  + +

                  ◆ do_causal

                  + +
                  +
                  + + + + +
                  constant bool do_causal
                  +
                  + +
                  +
                  + +

                  ◆ has_mask

                  + +
                  +
                  + + + + +
                  constant bool has_mask
                  +
                  +
                  diff --git a/docs/build/html/steel__attention_8h.js b/docs/build/html/steel__attention_8h.js index 89e1b75d7..31ff1ca78 100644 --- a/docs/build/html/steel__attention_8h.js +++ b/docs/build/html/steel__attention_8h.js @@ -7,7 +7,9 @@ var steel__attention_8h = [ "SubOp", "struct_sub_op.html", "struct_sub_op" ], [ "ExpSubOp", "struct_exp_sub_op.html", "struct_exp_sub_op" ], [ "DivOp", "struct_div_op.html", "struct_div_op" ], - [ "attention", "steel__attention_8h.html#a5423b2a414f5e3c14166d568dedfbd33", null ], + [ "attention", "steel__attention_8h.html#a835f90451dd42ce2d52352d5cce0722a", null ], [ "align_K", "steel__attention_8h.html#a8bdd2cecf97aa5b033152b1d0f0d2416", null ], - [ "align_Q", "steel__attention_8h.html#a171fdea1b23976453f5dc5e6b3161982", null ] + [ "align_Q", "steel__attention_8h.html#a171fdea1b23976453f5dc5e6b3161982", null ], + [ "do_causal", "steel__attention_8h.html#abfa50278ba59a90e0acb7e5d94500741", null ], + [ "has_mask", "steel__attention_8h.html#a6ed0dd113fe7d471fc0b869b8c028c81", null ] ]; \ No newline at end of file diff --git a/docs/build/html/steel__attention_8h_source.html b/docs/build/html/steel__attention_8h_source.html index 61ae7b649..91c01163a 100644 --- a/docs/build/html/steel__attention_8h_source.html +++ b/docs/build/html/steel__attention_8h_source.html @@ -105,7 +105,7 @@ $(function(){initNavTree('steel__attention_8h_source.html',''); initResizable(tr
                  steel_attention.h
                  -Go to the documentation of this file.
                  1// Copyright © 2024 Apple Inc.
                  +Go to the documentation of this file.
                  1// Copyright © 2024-25 Apple Inc.
                  2
                  3using namespace mlx::steel;
                  4
                  @@ -114,429 +114,516 @@ $(function(){initNavTree('steel__attention_8h_source.html',''); initResizable(tr
                  9constant bool align_Q [[function_constant(200)]];
                  10constant bool align_K [[function_constant(201)]];
                  11
                  -
                  12template <typename T>
                  -
                  -
                  13struct TransformScale {
                  -
                  14 T scale;
                  -
                  15 METAL_FUNC TransformScale(T scale_) : scale(scale_) {}
                  -
                  16
                  -
                  -
                  17 METAL_FUNC T apply(T x) const {
                  -
                  18 return scale * x;
                  -
                  19 }
                  +
                  12constant bool has_mask [[function_constant(300)]];
                  +
                  13constant bool do_causal [[function_constant(301)]];
                  +
                  14
                  +
                  15template <typename T>
                  +
                  +
                  16struct TransformScale {
                  +
                  17 T scale;
                  +
                  18 METAL_FUNC TransformScale(T scale_) : scale(scale_) {}
                  +
                  19
                  +
                  +
                  20 METAL_FUNC T apply(T x) const {
                  +
                  21 return scale * x;
                  +
                  22 }
                  -
                  20};
                  +
                  23};
                  -
                  21
                  -
                  -
                  22struct MaxOp {
                  -
                  23 template <typename T>
                  -
                  -
                  24 METAL_FUNC static constexpr T apply(T x, T y) {
                  -
                  25 return metal::max(x, y);
                  -
                  26 }
                  +
                  24
                  +
                  +
                  25struct MaxOp {
                  +
                  26 template <typename T>
                  +
                  +
                  27 METAL_FUNC static constexpr T apply(T x, T y) {
                  +
                  28 return metal::max(x, y);
                  +
                  29 }
                  -
                  27};
                  +
                  30};
                  -
                  28
                  -
                  -
                  29struct SumOp {
                  -
                  30 template <typename T>
                  -
                  -
                  31 METAL_FUNC static constexpr T apply(T x, T y) {
                  -
                  32 return x + y;
                  -
                  33 }
                  +
                  31
                  +
                  +
                  32struct SumOp {
                  +
                  33 template <typename T>
                  +
                  +
                  34 METAL_FUNC static constexpr T apply(T x, T y) {
                  +
                  35 return x + y;
                  +
                  36 }
                  -
                  34};
                  +
                  37};
                  -
                  35
                  -
                  -
                  36struct MulOp {
                  -
                  37 template <typename T>
                  -
                  -
                  38 METAL_FUNC static constexpr T apply(T x, T y) {
                  -
                  39 return x * y;
                  -
                  40 }
                  +
                  38
                  +
                  +
                  39struct MulOp {
                  +
                  40 template <typename T>
                  +
                  +
                  41 METAL_FUNC static constexpr T apply(T x, T y) {
                  +
                  42 return x * y;
                  +
                  43 }
                  -
                  41};
                  +
                  44};
                  -
                  42
                  -
                  -
                  43struct SubOp {
                  -
                  44 template <typename T>
                  -
                  -
                  45 METAL_FUNC static constexpr T apply(T x, T y) {
                  -
                  46 return x - y;
                  -
                  47 }
                  +
                  45
                  +
                  +
                  46struct SubOp {
                  +
                  47 template <typename T>
                  +
                  +
                  48 METAL_FUNC static constexpr T apply(T x, T y) {
                  +
                  49 return x - y;
                  +
                  50 }
                  -
                  48};
                  +
                  51};
                  -
                  49
                  -
                  -
                  50struct ExpSubOp {
                  -
                  51 template <typename T>
                  -
                  -
                  52 METAL_FUNC static constexpr T apply(T x, T y) {
                  -
                  53 return fast::exp2(x - y);
                  -
                  54 }
                  +
                  52
                  +
                  +
                  53struct ExpSubOp {
                  +
                  54 template <typename T>
                  +
                  +
                  55 METAL_FUNC static constexpr T apply(T x, T y) {
                  +
                  56 return fast::exp2(x - y);
                  +
                  57 }
                  -
                  55};
                  +
                  58};
                  -
                  56
                  -
                  -
                  57struct DivOp {
                  -
                  58 template <typename T>
                  -
                  -
                  59 METAL_FUNC static constexpr T apply(T x, T y) {
                  -
                  60 return x / y;
                  -
                  61 }
                  +
                  59
                  +
                  +
                  60struct DivOp {
                  +
                  61 template <typename T>
                  +
                  +
                  62 METAL_FUNC static constexpr T apply(T x, T y) {
                  +
                  63 return x / y;
                  +
                  64 }
                  -
                  62};
                  +
                  65};
                  -
                  63
                  -
                  64// clang-format off
                  -
                  65template <
                  -
                  66 typename T,
                  -
                  67 int BQ,
                  -
                  68 int BK,
                  -
                  69 int BD,
                  -
                  70 int WM,
                  -
                  71 int WN,
                  -
                  72 typename AccumType = float>
                  -
                  -
                  73[[kernel, max_total_threads_per_threadgroup(WM * WN * 32)]] void attention(
                  -
                  74 const device T* Q [[buffer(0)]],
                  -
                  75 const device T* K [[buffer(1)]],
                  -
                  76 const device T* V [[buffer(2)]],
                  -
                  77 device T* O [[buffer(3)]],
                  -
                  78 const constant AttnParams* params [[buffer(4)]],
                  -
                  79 uint simd_lane_id [[thread_index_in_simdgroup]],
                  -
                  80 uint simd_group_id [[simdgroup_index_in_threadgroup]],
                  -
                  81 uint3 tid [[threadgroup_position_in_grid]],
                  -
                  82 uint3 lid [[thread_position_in_threadgroup]]) { // clang-format on
                  -
                  83
                  -
                  84 // Pacifying compiler
                  -
                  85 (void)lid;
                  -
                  86
                  -
                  87 // Move to correct block
                  -
                  88 ulong3 tidl{tid.x, tid.y, tid.z};
                  +
                  66
                  +
                  67// clang-format off
                  +
                  68template <
                  +
                  69 typename T,
                  +
                  70 int BQ,
                  +
                  71 int BK,
                  +
                  72 int BD,
                  +
                  73 int WM,
                  +
                  74 int WN,
                  +
                  75 typename MaskType = float,
                  +
                  76 typename AccumType = float>
                  +
                  +
                  77[[kernel, max_total_threads_per_threadgroup(WM * WN * 32)]] void attention(
                  +
                  78 const device T* Q [[buffer(0)]],
                  +
                  79 const device T* K [[buffer(1)]],
                  +
                  80 const device T* V [[buffer(2)]],
                  +
                  81 device T* O [[buffer(3)]],
                  +
                  82 const constant AttnParams* params [[buffer(4)]],
                  +
                  83 const constant AttnMaskParams* mask_params [[buffer(5), function_constant(has_mask)]],
                  +
                  84 const device MaskType* mask [[buffer(6), function_constant(has_mask)]],
                  +
                  85 uint simd_lane_id [[thread_index_in_simdgroup]],
                  +
                  86 uint simd_group_id [[simdgroup_index_in_threadgroup]],
                  +
                  87 uint3 tid [[threadgroup_position_in_grid]],
                  +
                  88 uint3 lid [[thread_position_in_threadgroup]]) { // clang-format on
                  89
                  -
                  90 Q += tidl.z * params->Q_strides[0] + // Batch
                  -
                  91 tidl.y * params->Q_strides[1] + // Head
                  -
                  92 tidl.x * BQ * params->Q_strides[2]; // Seqeunce
                  -
                  93
                  -
                  94 ulong kv_head_idx = int(tid.y) / params->gqa_factor;
                  -
                  95 K += tidl.z * params->K_strides[0] + // Batch
                  -
                  96 kv_head_idx * params->K_strides[1]; // Head
                  -
                  97
                  -
                  98 V += tidl.z * params->V_strides[0] + // Batch
                  -
                  99 kv_head_idx * params->V_strides[1]; // Head
                  -
                  100
                  -
                  101 O += tidl.z * params->O_strides[0] + // Batch
                  -
                  102 tidl.y * params->O_strides[1] + // Head
                  -
                  103 tidl.x * BQ * params->O_strides[2]; // Seqeunce
                  -
                  104
                  -
                  105 // Prepare threadgroup memory
                  -
                  106 constexpr short padQ = 16 / sizeof(T);
                  -
                  107 constexpr short padK = 16 / sizeof(T);
                  -
                  108 constexpr short padV = 16 / sizeof(T);
                  -
                  109
                  -
                  110 constexpr short LDQ_tgp = BD + padQ;
                  -
                  111 constexpr short LDK_tgp = BK + padK;
                  -
                  112 constexpr short LDV_tgp = BD + padV;
                  -
                  113
                  -
                  114 constexpr short tgp_mem_0 = (BK + padK) * (BD);
                  -
                  115 constexpr short tgp_mem_1 = BK * (BD + padV);
                  -
                  116 constexpr short tgp_mem_s = tgp_mem_0 > tgp_mem_1 ? tgp_mem_0 : tgp_mem_1;
                  -
                  117
                  -
                  118 threadgroup T Q_smem[BQ * (BD + padQ)];
                  -
                  119 threadgroup T KV_smem[tgp_mem_s];
                  +
                  90 // Pacifying compiler
                  +
                  91 (void)lid;
                  +
                  92
                  +
                  93 // Move to correct block
                  +
                  94 ulong3 tidl{tid.x, tid.y, tid.z};
                  +
                  95
                  +
                  96 Q += tidl.z * params->Q_strides[0] + // Batch
                  +
                  97 tidl.y * params->Q_strides[1] + // Head
                  +
                  98 tidl.x * BQ * params->Q_strides[2]; // Seqeunce
                  +
                  99
                  +
                  100 ulong kv_head_idx = int(tid.y) / params->gqa_factor;
                  +
                  101 K += tidl.z * params->K_strides[0] + // Batch
                  +
                  102 kv_head_idx * params->K_strides[1]; // Head
                  +
                  103
                  +
                  104 V += tidl.z * params->V_strides[0] + // Batch
                  +
                  105 kv_head_idx * params->V_strides[1]; // Head
                  +
                  106
                  +
                  107 O += tidl.z * params->O_strides[0] + // Batch
                  +
                  108 tidl.y * params->O_strides[1] + // Head
                  +
                  109 tidl.x * BQ * params->O_strides[2]; // Seqeunce
                  +
                  110
                  +
                  111 if (has_mask) {
                  +
                  112 mask += tidl.z * mask_params->M_strides[0] + // Batch
                  +
                  113 tidl.y * mask_params->M_strides[1]; // Head
                  +
                  114 }
                  +
                  115
                  +
                  116 // Prepare threadgroup memory
                  +
                  117 constexpr short padQ = 16 / sizeof(T);
                  +
                  118 constexpr short padK = 16 / sizeof(T);
                  +
                  119 constexpr short padV = 16 / sizeof(T);
                  120
                  -
                  121 threadgroup T* Qs = Q_smem;
                  -
                  122 threadgroup T* Ks = KV_smem;
                  -
                  123 threadgroup T* Vs = KV_smem;
                  +
                  121 constexpr short LDQ_tgp = BD + padQ;
                  +
                  122 constexpr short LDK_tgp = BK + padK;
                  +
                  123 constexpr short LDV_tgp = BD + padV;
                  124
                  -
                  125 // Prepare block loaders
                  -
                  126 using QBlockLoader = BlockLoaderT<
                  -
                  127 /* typename T = */ T,
                  -
                  128 /* short BROWS = */ BQ,
                  -
                  129 /* short BCOLS = */ BD,
                  -
                  130 /* short kDstStrRow = */ LDQ_tgp,
                  -
                  131 /* short kDstStrCol = */ 1,
                  -
                  132 /* short reduction_dim = */ 1,
                  -
                  133 /* short tgp_size = */ WM * WN * 32>;
                  -
                  134
                  -
                  135 // K is loaded in transposed
                  -
                  136 using KBlockLoader = BlockLoaderT<
                  -
                  137 /* typename T = */ T,
                  -
                  138 /* short BROWS = */ BK,
                  -
                  139 /* short BCOLS = */ BD,
                  -
                  140 /* short kDstStrRow = */ 1,
                  -
                  141 /* short kDstStrCol = */ LDK_tgp,
                  -
                  142 /* short reduction_dim = */ 0,
                  -
                  143 /* short tgp_size = */ WM * WN * 32>;
                  -
                  144
                  -
                  145 using VBlockLoader = BlockLoaderT<
                  -
                  146 /* typename T = */ T,
                  -
                  147 /* short BROWS = */ BK,
                  -
                  148 /* short BCOLS = */ BD,
                  -
                  149 /* short kDstStrRow = */ LDV_tgp,
                  -
                  150 /* short kDstStrCol = */ 1,
                  -
                  151 /* short reduction_dim = */ 0,
                  -
                  152 /* short tgp_size = */ WM * WN * 32>;
                  -
                  153
                  -
                  154 QBlockLoader loader_q(
                  -
                  155 Q, params->Q_strides[2], Qs, simd_group_id, simd_lane_id);
                  -
                  156 KBlockLoader loader_k(
                  -
                  157 K, params->K_strides[2], Ks, simd_group_id, simd_lane_id);
                  -
                  158 VBlockLoader loader_v(
                  -
                  159 V, params->V_strides[2], Vs, simd_group_id, simd_lane_id);
                  -
                  160
                  -
                  161 TransformScale<T> ts(static_cast<T>(params->scale * 1.44269504089));
                  -
                  162
                  -
                  163 // Prepare MMA tiles
                  -
                  164 constexpr short kFragSize = 8; // MMAFrag size
                  -
                  165 using MMAFrag_acc_t = BaseMMAFrag<AccumType, kFragSize, kFragSize>;
                  -
                  166
                  -
                  167 constexpr int kNWarps = WM * WN;
                  -
                  168 static_assert(
                  -
                  169 BQ >= (kNWarps * kFragSize) && BQ % (kNWarps * kFragSize) == 0,
                  -
                  170 "Each simdgroup must host atleast 1 simdgroup matrix along Q sequence.");
                  +
                  125 constexpr short tgp_mem_0 = (BK + padK) * (BD);
                  +
                  126 constexpr short tgp_mem_1 = BK * (BD + padV);
                  +
                  127 constexpr short tgp_mem_s = tgp_mem_0 > tgp_mem_1 ? tgp_mem_0 : tgp_mem_1;
                  +
                  128
                  +
                  129 threadgroup T Q_smem[BQ * (BD + padQ)];
                  +
                  130 threadgroup T KV_smem[tgp_mem_s];
                  +
                  131
                  +
                  132 threadgroup T* Qs = Q_smem;
                  +
                  133 threadgroup T* Ks = KV_smem;
                  +
                  134 threadgroup T* Vs = KV_smem;
                  +
                  135
                  +
                  136 // Prepare block loaders
                  +
                  137 using QBlockLoader = BlockLoaderT<
                  +
                  138 /* typename T = */ T,
                  +
                  139 /* short BROWS = */ BQ,
                  +
                  140 /* short BCOLS = */ BD,
                  +
                  141 /* short kDstStrRow = */ LDQ_tgp,
                  +
                  142 /* short kDstStrCol = */ 1,
                  +
                  143 /* short reduction_dim = */ 1,
                  +
                  144 /* short tgp_size = */ WM * WN * 32>;
                  +
                  145
                  +
                  146 // K is loaded in transposed
                  +
                  147 using KBlockLoader = BlockLoaderT<
                  +
                  148 /* typename T = */ T,
                  +
                  149 /* short BROWS = */ BK,
                  +
                  150 /* short BCOLS = */ BD,
                  +
                  151 /* short kDstStrRow = */ 1,
                  +
                  152 /* short kDstStrCol = */ LDK_tgp,
                  +
                  153 /* short reduction_dim = */ 0,
                  +
                  154 /* short tgp_size = */ WM * WN * 32>;
                  +
                  155
                  +
                  156 using VBlockLoader = BlockLoaderT<
                  +
                  157 /* typename T = */ T,
                  +
                  158 /* short BROWS = */ BK,
                  +
                  159 /* short BCOLS = */ BD,
                  +
                  160 /* short kDstStrRow = */ LDV_tgp,
                  +
                  161 /* short kDstStrCol = */ 1,
                  +
                  162 /* short reduction_dim = */ 0,
                  +
                  163 /* short tgp_size = */ WM * WN * 32>;
                  +
                  164
                  +
                  165 QBlockLoader loader_q(
                  +
                  166 Q, params->Q_strides[2], Qs, simd_group_id, simd_lane_id);
                  +
                  167 KBlockLoader loader_k(
                  +
                  168 K, params->K_strides[2], Ks, simd_group_id, simd_lane_id);
                  +
                  169 VBlockLoader loader_v(
                  +
                  170 V, params->V_strides[2], Vs, simd_group_id, simd_lane_id);
                  171
                  -
                  172 // Q seq frags per warp
                  -
                  173 constexpr int TQ = BQ / (kNWarps * kFragSize);
                  -
                  174 // KV sequence frags (all warps load the same frags)
                  -
                  175 constexpr int TK = BK / kFragSize;
                  -
                  176 // HeadDim frags (all warps load the same frags)
                  -
                  177 constexpr int TD = BD / kFragSize;
                  -
                  178
                  -
                  179 static_assert(TQ == 1, "Check TQ");
                  -
                  180
                  -
                  181 MMATile<AccumType, TQ, 1, MMAFrag_acc_t> Qtile;
                  -
                  182 MMATile<AccumType, 1, TK, MMAFrag_acc_t> Ktile;
                  -
                  183 MMATile<AccumType, TQ, TK, MMAFrag_acc_t> Stile;
                  -
                  184 MMATile<AccumType, 1, 1, MMAFrag_acc_t> Vtile;
                  -
                  185 MMATile<AccumType, TQ, TD, MMAFrag_acc_t> Otile;
                  -
                  186
                  -
                  187 Otile.clear();
                  -
                  188
                  -
                  189 // Prepare mma tile offsets
                  -
                  190 const short2 simd_coord = MMAFrag_acc_t::get_coord(simd_lane_id);
                  -
                  191 const short sm = simd_coord.y;
                  -
                  192 const short sn = simd_coord.x;
                  -
                  193 const short tm = kFragSize * TQ * simd_group_id;
                  -
                  194
                  -
                  195 const short Qs_offset = (tm + sm) * LDQ_tgp + sn;
                  -
                  196 const short Ks_offset = sm * LDK_tgp + sn;
                  -
                  197 const short Vs_offset = sm * LDV_tgp + sn;
                  -
                  198
                  -
                  199 constexpr short Qs_tile_stride = kFragSize;
                  -
                  200 constexpr short Ks_tile_stride = kFragSize * LDK_tgp;
                  -
                  201
                  -
                  202 threadgroup_barrier(mem_flags::mem_threadgroup);
                  -
                  203
                  -
                  204 // Load Q blocks apply scale
                  -
                  205 if (!align_Q && int(tid.x) == (params->NQ_aligned)) {
                  -
                  206 loader_q.load_safe(short2(BD, params->qL - params->NQ_aligned * BQ));
                  -
                  207 } else {
                  -
                  208 loader_q.load_unsafe();
                  -
                  209 }
                  -
                  210 loader_q.apply_inplace_op(ts);
                  -
                  211
                  -
                  212 // Init row reduction variables
                  -
                  213 constexpr short kRowsPT = decltype(Stile)::kRowsPerThread;
                  +
                  172 TransformScale<T> ts(static_cast<T>(params->scale * 1.44269504089));
                  +
                  173
                  +
                  174 // Prepare MMA tiles
                  +
                  175 constexpr short kFragSize = 8; // MMAFrag size
                  +
                  176 using MMAFrag_acc_t = BaseMMAFrag<AccumType, kFragSize, kFragSize>;
                  +
                  177
                  +
                  178 constexpr int kNWarps = WM * WN;
                  +
                  179 static_assert(
                  +
                  180 BQ >= (kNWarps * kFragSize) && BQ % (kNWarps * kFragSize) == 0,
                  +
                  181 "Each simdgroup must host atleast 1 simdgroup matrix along Q sequence.");
                  +
                  182
                  +
                  183 // Q seq frags per warp
                  +
                  184 constexpr int TQ = BQ / (kNWarps * kFragSize);
                  +
                  185 // KV sequence frags (all warps load the same frags)
                  +
                  186 constexpr int TK = BK / kFragSize;
                  +
                  187 // HeadDim frags (all warps load the same frags)
                  +
                  188 constexpr int TD = BD / kFragSize;
                  +
                  189
                  +
                  190 static_assert(TQ == 1, "Check TQ");
                  +
                  191
                  +
                  192 MMATile<AccumType, TQ, 1, MMAFrag_acc_t> Qtile;
                  +
                  193 MMATile<AccumType, 1, TK, MMAFrag_acc_t> Ktile;
                  +
                  194 MMATile<AccumType, TQ, TK, MMAFrag_acc_t> Stile;
                  +
                  195 MMATile<AccumType, 1, 1, MMAFrag_acc_t> Vtile;
                  +
                  196 MMATile<AccumType, TQ, TD, MMAFrag_acc_t> Otile;
                  +
                  197
                  +
                  198 Otile.clear();
                  +
                  199
                  +
                  200 // Prepare mma tile offsets
                  +
                  201 const short2 simd_coord = MMAFrag_acc_t::get_coord(simd_lane_id);
                  +
                  202 const short sm = simd_coord.y;
                  +
                  203 const short sn = simd_coord.x;
                  +
                  204 const short tm = kFragSize * TQ * simd_group_id;
                  +
                  205
                  +
                  206 const short Qs_offset = (tm + sm) * LDQ_tgp + sn;
                  +
                  207 const short Ks_offset = sm * LDK_tgp + sn;
                  +
                  208 const short Vs_offset = sm * LDV_tgp + sn;
                  +
                  209
                  +
                  210 constexpr short Qs_tile_stride = kFragSize;
                  +
                  211 constexpr short Ks_tile_stride = kFragSize * LDK_tgp;
                  +
                  212
                  +
                  213 threadgroup_barrier(mem_flags::mem_threadgroup);
                  214
                  -
                  215 AccumType max_score[kRowsPT];
                  -
                  216 AccumType sum_score[kRowsPT] = {0};
                  -
                  217
                  -
                  218 // Init to -Inf
                  -
                  219 STEEL_PRAGMA_UNROLL
                  -
                  220 for (short i = 0; i < kRowsPT; ++i) {
                  -
                  221 max_score[i] = Limits<AccumType>::min;
                  -
                  222 }
                  -
                  223
                  -
                  224 // Loop over KV seq length
                  -
                  225 for (int kb = 0; kb < params->NK; kb++) {
                  -
                  226 // Load K block and apply scale
                  -
                  227 threadgroup_barrier(mem_flags::mem_threadgroup);
                  -
                  228 if (!align_K && kb == (params->NK_aligned)) {
                  -
                  229 loader_k.load_safe(short2(BD, params->kL - params->NK_aligned * BK));
                  -
                  230 } else {
                  -
                  231 loader_k.load_unsafe();
                  -
                  232 }
                  -
                  233
                  -
                  234 // Do S = Q @ K.T
                  -
                  235 Stile.clear();
                  +
                  215 // Load Q blocks apply scale
                  +
                  216 if (!align_Q && int(tid.x) == (params->NQ_aligned)) {
                  +
                  217 loader_q.load_safe(short2(BD, params->qL_rem));
                  +
                  218 } else {
                  +
                  219 loader_q.load_unsafe();
                  +
                  220 }
                  +
                  221 loader_q.apply_inplace_op(ts);
                  +
                  222
                  +
                  223 // Init row reduction variables
                  +
                  224 constexpr short kRowsPT = decltype(Stile)::kRowsPerThread;
                  +
                  225
                  +
                  226 AccumType max_score[kRowsPT];
                  +
                  227 AccumType sum_score[kRowsPT] = {0};
                  +
                  228
                  +
                  229 // Init to -Inf
                  +
                  230 STEEL_PRAGMA_UNROLL
                  +
                  231 for (short i = 0; i < kRowsPT; ++i) {
                  +
                  232 max_score[i] = Limits<AccumType>::min;
                  +
                  233 }
                  +
                  234
                  +
                  235 int kb_lim = params->NK;
                  236
                  -
                  237 threadgroup_barrier(mem_flags::mem_threadgroup);
                  -
                  238
                  -
                  239 STEEL_PRAGMA_UNROLL
                  -
                  240 for (short dd = 0; dd < TD; dd++) {
                  -
                  241 simdgroup_barrier(mem_flags::mem_none);
                  -
                  242
                  -
                  243 Qtile.template load<T, 1, 1, LDQ_tgp, 1>(
                  -
                  244 &Qs[Qs_offset + dd * Qs_tile_stride]);
                  -
                  245 Ktile.template load<T, 1, 1, LDK_tgp, 1>(
                  -
                  246 &Ks[Ks_offset + dd * Ks_tile_stride]);
                  -
                  247
                  -
                  248 simdgroup_barrier(mem_flags::mem_none);
                  -
                  249
                  -
                  250 tile_matmad(Stile, Qtile, Ktile, Stile);
                  -
                  251 }
                  -
                  252
                  -
                  253 // Mask out of length sequence
                  -
                  254 if (!align_K && kb == (params->NK_aligned)) {
                  -
                  255 using stile_t = decltype(Stile);
                  -
                  256 using selem_t = typename stile_t::elem_type;
                  -
                  257 constexpr auto neg_inf = -metal::numeric_limits<selem_t>::infinity();
                  -
                  258 const short lim = params->kL - params->NK_aligned * BK;
                  -
                  259
                  -
                  260 STEEL_PRAGMA_UNROLL
                  -
                  261 for (short i = 0; i < stile_t::kTileRows; i++) {
                  -
                  262 STEEL_PRAGMA_UNROLL
                  -
                  263 for (short j = 0; j < stile_t::kTileCols; j++) {
                  -
                  264 short col_pos = sn + (j * stile_t::kFragCols);
                  -
                  265 STEEL_PRAGMA_UNROLL
                  -
                  266 for (short jj = 0; jj < stile_t::MMAFrag_t::kElemCols; jj++) {
                  -
                  267 if ((col_pos + jj) >= lim) {
                  -
                  268 Stile.frag_at(i, j)[jj] = neg_inf;
                  -
                  269 }
                  -
                  270 }
                  -
                  271 }
                  -
                  272 }
                  -
                  273 }
                  -
                  274
                  -
                  275 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  237 if (do_causal) {
                  +
                  238 int q_max = (tid.x + 1) * BQ + params->qL_off;
                  +
                  239 kb_lim = (q_max + BK - 1) / BK;
                  +
                  240 }
                  +
                  241
                  +
                  242 // Loop over KV seq length
                  +
                  243 for (int kb = 0; kb < kb_lim; kb++) {
                  +
                  244 // Load K block and apply scale
                  +
                  245 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  246 if (!align_K && kb == (params->NK_aligned)) {
                  +
                  247 loader_k.load_safe(short2(BD, params->kL_rem));
                  +
                  248 } else {
                  +
                  249 loader_k.load_unsafe();
                  +
                  250 }
                  +
                  251
                  +
                  252 // Do S = Q @ K.T
                  +
                  253 Stile.clear();
                  +
                  254
                  +
                  255 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  256
                  +
                  257 STEEL_PRAGMA_UNROLL
                  +
                  258 for (short dd = 0; dd < TD; dd++) {
                  +
                  259 simdgroup_barrier(mem_flags::mem_none);
                  +
                  260
                  +
                  261 Qtile.template load<T, 1, 1, LDQ_tgp, 1>(
                  +
                  262 &Qs[Qs_offset + dd * Qs_tile_stride]);
                  +
                  263 Ktile.template load<T, 1, 1, LDK_tgp, 1>(
                  +
                  264 &Ks[Ks_offset + dd * Ks_tile_stride]);
                  +
                  265
                  +
                  266 simdgroup_barrier(mem_flags::mem_none);
                  +
                  267
                  +
                  268 tile_matmad(Stile, Qtile, Ktile, Stile);
                  +
                  269 }
                  +
                  270
                  +
                  271 // Mask out length sequence
                  +
                  272 if (!align_K && kb == (params->NK_aligned)) {
                  +
                  273 using stile_t = decltype(Stile);
                  +
                  274 using selem_t = typename stile_t::elem_type;
                  +
                  275 constexpr auto neg_inf = -metal::numeric_limits<selem_t>::infinity();
                  276
                  -
                  277 // Load V blocks
                  -
                  278 if (!align_K && kb == (params->NK_aligned)) {
                  -
                  279 loader_v.load_safe(short2(BD, params->kL - params->NK_aligned * BK));
                  -
                  280 } else {
                  -
                  281 loader_v.load_unsafe();
                  -
                  282 }
                  -
                  283
                  -
                  284 // Do softmax
                  -
                  285
                  -
                  286 // Temp variables
                  -
                  287 AccumType new_max[kRowsPT];
                  -
                  288 AccumType factor[kRowsPT];
                  -
                  289 STEEL_PRAGMA_UNROLL
                  -
                  290 for (short i = 0; i < kRowsPT; ++i) {
                  -
                  291 new_max[i] = max_score[i];
                  -
                  292 }
                  -
                  293
                  -
                  294 // Row max
                  -
                  295 Stile.template row_reduce<MaxOp>(new_max);
                  -
                  296
                  -
                  297 // exp(Si - rowmax(Si))
                  -
                  298 Stile.template row_bin_op<ExpSubOp>(new_max);
                  -
                  299
                  -
                  300 // Factor exp(rowmax(Si) - rowmax(Si-1))
                  -
                  301 STEEL_PRAGMA_UNROLL
                  -
                  302 for (short i = 0; i < kRowsPT; ++i) {
                  -
                  303 factor[i] = fast::exp2(max_score[i] - new_max[i]);
                  -
                  304 }
                  -
                  305
                  -
                  306 // Save max for next iteration
                  -
                  307 STEEL_PRAGMA_UNROLL
                  -
                  308 for (short i = 0; i < kRowsPT; ++i) {
                  -
                  309 max_score[i] = new_max[i];
                  -
                  310 }
                  -
                  311
                  -
                  312 // Row Sum
                  -
                  313 AccumType sum_score_tmp[kRowsPT] = {0};
                  -
                  314 Stile.template row_reduce<SumOp>(sum_score_tmp);
                  -
                  315
                  -
                  316 // Update norm
                  -
                  317 STEEL_PRAGMA_UNROLL
                  -
                  318 for (short i = 0; i < kRowsPT; ++i) {
                  -
                  319 sum_score[i] = sum_score[i] * factor[i] + sum_score_tmp[i];
                  -
                  320 }
                  -
                  321
                  -
                  322 // Update O
                  -
                  323 Otile.template row_bin_op<MulOp>(factor);
                  -
                  324
                  -
                  325 // Load V into registers
                  -
                  326 threadgroup_barrier(mem_flags::mem_threadgroup);
                  -
                  327
                  -
                  328 STEEL_PRAGMA_UNROLL
                  -
                  329 for (short iq = 0; iq < TQ; iq++) {
                  -
                  330 STEEL_PRAGMA_UNROLL
                  -
                  331 for (short id = 0; id < TD; id++) {
                  -
                  332 STEEL_PRAGMA_UNROLL
                  -
                  333 for (short ik = 0; ik < TK; ik++) {
                  -
                  334 if constexpr (BD == 128) {
                  -
                  335 simdgroup_barrier(mem_flags::mem_none);
                  -
                  336 }
                  -
                  337
                  -
                  338 const short kk = ik * kFragSize;
                  -
                  339 const short dd = id * kFragSize;
                  -
                  340
                  -
                  341 Vtile.template load<T, 1, 1, LDV_tgp, 1>(
                  -
                  342 &Vs[Vs_offset + kk * LDV_tgp + dd]);
                  -
                  343
                  -
                  344 if constexpr (BD == 128) {
                  -
                  345 simdgroup_barrier(mem_flags::mem_none);
                  -
                  346 }
                  -
                  347
                  -
                  348 MMAFrag_acc_t::mma(
                  -
                  349 Otile.frag_at(iq, id),
                  -
                  350 Stile.frag_at(iq, ik),
                  -
                  351 Vtile.frag_at(0, 0),
                  -
                  352 Otile.frag_at(iq, id));
                  -
                  353 }
                  -
                  354 }
                  -
                  355 }
                  -
                  356
                  -
                  357 // Prepare for next iteration
                  -
                  358 loader_k.next();
                  -
                  359 loader_v.next();
                  -
                  360 }
                  -
                  361
                  -
                  362 // Normalize output
                  -
                  363 Otile.template row_bin_op<DivOp>(sum_score);
                  -
                  364 threadgroup_barrier(mem_flags::mem_none);
                  -
                  365
                  -
                  366 // Store results
                  -
                  367 O += (tm + sm) * params->O_strides[2] + sn;
                  -
                  368
                  -
                  369 if (!align_Q && int(tid.x) == (params->NQ_aligned)) {
                  -
                  370 auto dst_tile_dims =
                  -
                  371 short2(BD - sn, params->qL - BQ * params->NQ_aligned - (tm + sm));
                  -
                  372
                  -
                  373 if (dst_tile_dims.x <= 0 || dst_tile_dims.y <= 0)
                  -
                  374 return;
                  -
                  375
                  -
                  376 Otile.template store_safe<T, 1, 1>(O, params->O_strides[2], dst_tile_dims);
                  -
                  377 } else {
                  -
                  378 Otile.template store<T, 1, 1>(O, params->O_strides[2]);
                  -
                  379 }
                  -
                  380}
                  +
                  277 STEEL_PRAGMA_UNROLL
                  +
                  278 for (short i = 0; i < stile_t::kTileRows; i++) {
                  +
                  279 STEEL_PRAGMA_UNROLL
                  +
                  280 for (short j = 0; j < stile_t::kTileCols; j++) {
                  +
                  281 short col_pos = sn + (j * stile_t::kFragCols);
                  +
                  282 STEEL_PRAGMA_UNROLL
                  +
                  283 for (short jj = 0; jj < stile_t::MMAFrag_t::kElemCols; jj++) {
                  +
                  284 if ((col_pos + jj) >= params->kL_rem) {
                  +
                  285 Stile.frag_at(i, j)[jj] = neg_inf;
                  +
                  286 }
                  +
                  287 }
                  +
                  288 }
                  +
                  289 }
                  +
                  290 }
                  +
                  291
                  +
                  292 // Mask out if causal
                  +
                  293 if (do_causal && kb >= (kb_lim - (BQ + BK - 1) / BK - int(!align_K))) {
                  +
                  294 using stile_t = decltype(Stile);
                  +
                  295 using selem_t = typename stile_t::elem_type;
                  +
                  296 constexpr auto neg_inf = -metal::numeric_limits<selem_t>::infinity();
                  +
                  297
                  +
                  298 STEEL_PRAGMA_UNROLL
                  +
                  299 for (short i = 0; i < stile_t::kTileRows; i++) {
                  +
                  300 const int row_pos =
                  +
                  301 tid.x * BQ + params->qL_off + tm + sm + (i * stile_t::kFragRows);
                  +
                  302 STEEL_PRAGMA_UNROLL
                  +
                  303 for (short j = 0; j < stile_t::kTileCols; j++) {
                  +
                  304 const int col_pos = kb * BK + sn + (j * stile_t::kFragCols);
                  +
                  305 STEEL_PRAGMA_UNROLL
                  +
                  306 for (short jj = 0; jj < stile_t::MMAFrag_t::kElemCols; jj++) {
                  +
                  307 if (row_pos < (col_pos + jj)) {
                  +
                  308 Stile.frag_at(i, j)[jj] = neg_inf;
                  +
                  309 }
                  +
                  310 }
                  +
                  311 }
                  +
                  312 }
                  +
                  313 }
                  +
                  314
                  +
                  315 // Other masking as needed
                  +
                  316 if (has_mask) {
                  +
                  317 using stile_t = decltype(Stile);
                  +
                  318 using selem_t = typename stile_t::elem_type;
                  +
                  319 constexpr auto neg_inf = -metal::numeric_limits<selem_t>::infinity();
                  +
                  320
                  +
                  321 constexpr bool is_bool = is_same_v<MaskType, bool>;
                  +
                  322 using melem_t = typename metal::conditional_t<is_bool, bool, selem_t>;
                  +
                  323
                  +
                  324 using MMAFrag_mask_t = BaseMMAFrag<melem_t, kFragSize, kFragSize>;
                  +
                  325 using frag_t = typename MMAFrag_mask_t::frag_type;
                  +
                  326
                  +
                  327 STEEL_PRAGMA_UNROLL
                  +
                  328 for (short i = 0; i < stile_t::kTileRows; i++) {
                  +
                  329 const int row_pos = tid.x * BQ + tm + sm + (i * stile_t::kFragRows);
                  +
                  330 STEEL_PRAGMA_UNROLL
                  +
                  331 for (short j = 0; j < stile_t::kTileCols; j++) {
                  +
                  332 const int col_pos = kb * BK + sn + (j * stile_t::kFragCols);
                  +
                  333
                  +
                  334 frag_t mfrag;
                  +
                  335
                  +
                  336 MMAFrag_mask_t::load_safe(
                  +
                  337 mfrag,
                  +
                  338 mask,
                  +
                  339 int(mask_params->M_strides[2]),
                  +
                  340 Int<1>{},
                  +
                  341 params->qL,
                  +
                  342 params->kL,
                  +
                  343 row_pos,
                  +
                  344 col_pos);
                  +
                  345
                  +
                  346 STEEL_PRAGMA_UNROLL
                  +
                  347 for (short jj = 0; jj < stile_t::MMAFrag_t::kElemsPerFrag; jj++) {
                  +
                  348 if constexpr (is_bool) {
                  +
                  349 Stile.frag_at(i, j)[jj] =
                  +
                  350 mfrag[jj] ? Stile.frag_at(i, j)[jj] : neg_inf;
                  +
                  351 } else {
                  +
                  352 Stile.frag_at(i, j)[jj] += 1.44269504089 * selem_t(mfrag[jj]);
                  +
                  353 }
                  +
                  354 }
                  +
                  355 }
                  +
                  356 }
                  +
                  357 }
                  +
                  358
                  +
                  359 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  360
                  +
                  361 // Load V blocks
                  +
                  362 if (!align_K && kb == (params->NK_aligned)) {
                  +
                  363 loader_v.load_safe(short2(BD, params->kL_rem));
                  +
                  364 } else {
                  +
                  365 loader_v.load_unsafe();
                  +
                  366 }
                  +
                  367
                  +
                  368 // Do softmax
                  +
                  369
                  +
                  370 // Temp variables
                  +
                  371 AccumType new_max[kRowsPT];
                  +
                  372 AccumType factor[kRowsPT];
                  +
                  373 STEEL_PRAGMA_UNROLL
                  +
                  374 for (short i = 0; i < kRowsPT; ++i) {
                  +
                  375 new_max[i] = max_score[i];
                  +
                  376 }
                  +
                  377
                  +
                  378 // Row max
                  +
                  379 Stile.template row_reduce<MaxOp>(new_max);
                  +
                  380
                  +
                  381 // exp(Si - rowmax(Si))
                  +
                  382 Stile.template row_bin_op<ExpSubOp>(new_max);
                  +
                  383
                  +
                  384 // Factor exp(rowmax(Si) - rowmax(Si-1))
                  +
                  385 STEEL_PRAGMA_UNROLL
                  +
                  386 for (short i = 0; i < kRowsPT; ++i) {
                  +
                  387 factor[i] = fast::exp2(max_score[i] - new_max[i]);
                  +
                  388 }
                  +
                  389
                  +
                  390 // Save max for next iteration
                  +
                  391 STEEL_PRAGMA_UNROLL
                  +
                  392 for (short i = 0; i < kRowsPT; ++i) {
                  +
                  393 max_score[i] = new_max[i];
                  +
                  394 }
                  +
                  395
                  +
                  396 // Row Sum
                  +
                  397 AccumType sum_score_tmp[kRowsPT] = {0};
                  +
                  398 Stile.template row_reduce<SumOp>(sum_score_tmp);
                  +
                  399
                  +
                  400 // Update norm
                  +
                  401 STEEL_PRAGMA_UNROLL
                  +
                  402 for (short i = 0; i < kRowsPT; ++i) {
                  +
                  403 sum_score[i] = sum_score[i] * factor[i] + sum_score_tmp[i];
                  +
                  404 }
                  +
                  405
                  +
                  406 // Update O
                  +
                  407 Otile.template row_bin_op<MulOp>(factor);
                  +
                  408
                  +
                  409 // Load V into registers
                  +
                  410 threadgroup_barrier(mem_flags::mem_threadgroup);
                  +
                  411
                  +
                  412 STEEL_PRAGMA_UNROLL
                  +
                  413 for (short iq = 0; iq < TQ; iq++) {
                  +
                  414 STEEL_PRAGMA_UNROLL
                  +
                  415 for (short id = 0; id < TD; id++) {
                  +
                  416 STEEL_PRAGMA_UNROLL
                  +
                  417 for (short ik = 0; ik < TK; ik++) {
                  +
                  418 if constexpr (BD == 128) {
                  +
                  419 simdgroup_barrier(mem_flags::mem_none);
                  +
                  420 }
                  +
                  421
                  +
                  422 const short kk = ik * kFragSize;
                  +
                  423 const short dd = id * kFragSize;
                  +
                  424
                  +
                  425 Vtile.template load<T, 1, 1, LDV_tgp, 1>(
                  +
                  426 &Vs[Vs_offset + kk * LDV_tgp + dd]);
                  +
                  427
                  +
                  428 if constexpr (BD == 128) {
                  +
                  429 simdgroup_barrier(mem_flags::mem_none);
                  +
                  430 }
                  +
                  431
                  +
                  432 MMAFrag_acc_t::mma(
                  +
                  433 Otile.frag_at(iq, id),
                  +
                  434 Stile.frag_at(iq, ik),
                  +
                  435 Vtile.frag_at(0, 0),
                  +
                  436 Otile.frag_at(iq, id));
                  +
                  437 }
                  +
                  438 }
                  +
                  439 }
                  +
                  440
                  +
                  441 // Prepare for next iteration
                  +
                  442 loader_k.next();
                  +
                  443 loader_v.next();
                  +
                  444 }
                  +
                  445
                  +
                  446 // Normalize output
                  +
                  447 Otile.template row_bin_op<DivOp>(sum_score);
                  +
                  448 threadgroup_barrier(mem_flags::mem_none);
                  +
                  449
                  +
                  450 // Store results
                  +
                  451 O += (tm + sm) * params->O_strides[2] + sn;
                  +
                  452
                  +
                  453 if (!align_Q && int(tid.x) == (params->NQ_aligned)) {
                  +
                  454 auto dst_tile_dims = short2(BD - sn, params->qL_rem - (tm + sm));
                  +
                  455
                  +
                  456 if (dst_tile_dims.x <= 0 || dst_tile_dims.y <= 0)
                  +
                  457 return;
                  +
                  458
                  +
                  459 Otile.template store_safe<T, 1, 1>(O, params->O_strides[2], dst_tile_dims);
                  +
                  460 } else {
                  +
                  461 Otile.template store<T, 1, 1>(O, params->O_strides[2]);
                  +
                  462 }
                  +
                  463}
                  metal::max
                  METAL_FUNC bfloat16_t max(bfloat16_t x, bfloat16_t y)
                  Definition bf16_math.h:232
                  mlx::steel
                  Definition attn.h:19
                  mlx::steel::tile_matmad
                  METAL_FUNC void tile_matmad(thread MMATile< Dtype, M, N, MMAFragD > &D, thread MMATile< Atype, M, K, MMAFragA > &A, thread MMATile< Btype, K, N, MMAFragB > &B, thread MMATile< Ctype, M, N, MMAFragC > &C)
                  Definition mma.h:432
                  +
                  mlx::steel::Int
                  integral_constant< int, val > Int
                  Definition integral_constant.h:48
                  +
                  has_mask
                  constant bool has_mask
                  Definition sdpa_vector.h:7
                  STEEL_PRAGMA_UNROLL
                  #define STEEL_PRAGMA_UNROLL
                  Definition defines.h:4
                  align_Q
                  constant bool align_Q
                  Definition steel_attention.h:9
                  -
                  attention
                  void attention(const device T *Q, const device T *K, const device T *V, device T *O, const constant AttnParams *params, uint simd_lane_id, uint simd_group_id, uint3 tid, uint3 lid)
                  Definition steel_attention.h:73
                  +
                  attention
                  void attention(const device T *Q, const device T *K, const device T *V, device T *O, const constant AttnParams *params, const constant AttnMaskParams *mask_params, const device MaskType *mask, uint simd_lane_id, uint simd_group_id, uint3 tid, uint3 lid)
                  Definition steel_attention.h:77
                  align_K
                  constant bool align_K
                  Definition steel_attention.h:10
                  -
                  DivOp
                  Definition steel_attention.h:57
                  -
                  DivOp::apply
                  static METAL_FUNC constexpr T apply(T x, T y)
                  Definition steel_attention.h:59
                  -
                  ExpSubOp
                  Definition steel_attention.h:50
                  -
                  ExpSubOp::apply
                  static METAL_FUNC constexpr T apply(T x, T y)
                  Definition steel_attention.h:52
                  +
                  do_causal
                  constant bool do_causal
                  Definition steel_attention.h:13
                  +
                  DivOp
                  Definition steel_attention.h:60
                  +
                  DivOp::apply
                  static METAL_FUNC constexpr T apply(T x, T y)
                  Definition steel_attention.h:62
                  +
                  ExpSubOp
                  Definition steel_attention.h:53
                  +
                  ExpSubOp::apply
                  static METAL_FUNC constexpr T apply(T x, T y)
                  Definition steel_attention.h:55
                  Limits::min
                  static const constant U min
                  Definition utils.h:25
                  -
                  MaxOp
                  Definition steel_attention.h:22
                  -
                  MaxOp::apply
                  static METAL_FUNC constexpr T apply(T x, T y)
                  Definition steel_attention.h:24
                  -
                  MulOp
                  Definition steel_attention.h:36
                  -
                  MulOp::apply
                  static METAL_FUNC constexpr T apply(T x, T y)
                  Definition steel_attention.h:38
                  -
                  SubOp
                  Definition steel_attention.h:43
                  -
                  SubOp::apply
                  static METAL_FUNC constexpr T apply(T x, T y)
                  Definition steel_attention.h:45
                  -
                  SumOp
                  Definition steel_attention.h:29
                  -
                  SumOp::apply
                  static METAL_FUNC constexpr T apply(T x, T y)
                  Definition steel_attention.h:31
                  -
                  TransformScale
                  Definition steel_attention.h:13
                  -
                  TransformScale::apply
                  METAL_FUNC T apply(T x) const
                  Definition steel_attention.h:17
                  -
                  TransformScale::scale
                  T scale
                  Definition steel_attention.h:14
                  -
                  TransformScale::TransformScale
                  METAL_FUNC TransformScale(T scale_)
                  Definition steel_attention.h:15
                  +
                  MaxOp
                  Definition steel_attention.h:25
                  +
                  MaxOp::apply
                  static METAL_FUNC constexpr T apply(T x, T y)
                  Definition steel_attention.h:27
                  +
                  MulOp
                  Definition steel_attention.h:39
                  +
                  MulOp::apply
                  static METAL_FUNC constexpr T apply(T x, T y)
                  Definition steel_attention.h:41
                  +
                  SubOp
                  Definition steel_attention.h:46
                  +
                  SubOp::apply
                  static METAL_FUNC constexpr T apply(T x, T y)
                  Definition steel_attention.h:48
                  +
                  SumOp
                  Definition steel_attention.h:32
                  +
                  SumOp::apply
                  static METAL_FUNC constexpr T apply(T x, T y)
                  Definition steel_attention.h:34
                  +
                  TransformScale
                  Definition steel_attention.h:16
                  +
                  TransformScale::apply
                  METAL_FUNC T apply(T x) const
                  Definition steel_attention.h:20
                  +
                  TransformScale::scale
                  T scale
                  Definition steel_attention.h:17
                  +
                  TransformScale::TransformScale
                  METAL_FUNC TransformScale(T scale_)
                  Definition steel_attention.h:18
                  +
                  mlx::steel::AttnMaskParams
                  Definition params.h:39
                  mlx::steel::AttnParams
                  Definition params.h:12
                  mlx::steel::BaseMMAFrag
                  Definition mma.h:37
                  mlx::steel::BlockLoaderT
                  Definition loader.h:153
                  diff --git a/docs/build/html/struct_g_e_m_v_kernel-members.html b/docs/build/html/struct_g_e_m_v_kernel-members.html index 6c41f3fd2..c2dfdc460 100644 --- a/docs/build/html/struct_g_e_m_v_kernel-members.html +++ b/docs/build/html/struct_g_e_m_v_kernel-members.html @@ -102,25 +102,25 @@ $(function(){initNavTree('struct_g_e_m_v_kernel.html',''); initResizable(true);
                  -
                  GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN > Member List
                  +
                  GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT > Member List
                  -

                  This is the complete list of members for GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, including all inherited members.

                  +

                  This is the complete list of members for GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, including all inherited members.

                  - - - - - - - - - - - - - + + + + + + + + + + + + +
                  blockMGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  blockNGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  has_mul_operand_maskGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  has_mul_output_maskGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  has_operand_maskGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  has_output_maskGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  load_safe(const device T *src, thread T dst[TN], const int src_offset=0, const int src_size=TN)GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >inlinestatic
                  load_unsafe(const device T *src, thread T dst[TN], const int src_offset=0)GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >inlinestatic
                  needs_tgp_reductionGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  run(const device T *mat, const device T *in_vec, device T *out_vec, const constant int &in_vec_size, const constant int &out_vec_size, const constant int &matrix_ld, const device out_mask_t *out_mask, const device op_mask_t *mat_mask, const device op_mask_t *vec_mask, const constant int *mask_strides, threadgroup T *tgp_memory, uint3 tid, uint3 lid, uint simd_gid, uint simd_lid)GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >inlinestatic
                  tgp_mem_sizeGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  threadsMGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  threadsNGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  blockMGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  blockNGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  has_mul_operand_maskGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  has_mul_output_maskGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  has_operand_maskGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  has_output_maskGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  load_safe(const device T *src, thread U dst[TN], const int src_offset=0, const int src_size=TN)GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >inlinestatic
                  load_unsafe(const device T *src, thread U dst[TN], const int src_offset=0)GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >inlinestatic
                  needs_tgp_reductionGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  run(const device T *mat, const device T *in_vec, device T *out_vec, const constant int &in_vec_size, const constant int &out_vec_size, const constant int &matrix_ld, const device out_mask_t *out_mask, const device op_mask_t *mat_mask, const device op_mask_t *vec_mask, const constant int *mask_strides, threadgroup AccT *tgp_memory, uint3 tid, uint3 lid, uint simd_gid, uint simd_lid)GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >inlinestatic
                  tgp_mem_sizeGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  threadsMGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  threadsNGEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  diff --git a/docs/build/html/struct_g_e_m_v_kernel.html b/docs/build/html/struct_g_e_m_v_kernel.html index bab4163ea..038f15a29 100644 --- a/docs/build/html/struct_g_e_m_v_kernel.html +++ b/docs/build/html/struct_g_e_m_v_kernel.html @@ -5,7 +5,7 @@ -MLX: GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN > Struct Template Reference +MLX: GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT > Struct Template Reference @@ -106,7 +106,7 @@ $(function(){initNavTree('struct_g_e_m_v_kernel.html',''); initResizable(true); Static Public Member Functions | Static Public Attributes | List of all members
                  -
                  GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN > Struct Template Reference
                  +
                  GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT > Struct Template Reference
                  @@ -114,57 +114,61 @@ $(function(){initNavTree('struct_g_e_m_v_kernel.html',''); initResizable(true); - - - - - - + + + + + + + +

                  Static Public Member Functions

                  static METAL_FUNC void load_unsafe (const device T *src, thread T dst[TN], const int src_offset=0)
                   
                  static METAL_FUNC void load_safe (const device T *src, thread T dst[TN], const int src_offset=0, const int src_size=TN)
                   
                  static METAL_FUNC void run (const device T *mat, const device T *in_vec, device T *out_vec, const constant int &in_vec_size, const constant int &out_vec_size, const constant int &matrix_ld, const device out_mask_t *out_mask, const device op_mask_t *mat_mask, const device op_mask_t *vec_mask, const constant int *mask_strides, threadgroup T *tgp_memory, uint3 tid, uint3 lid, uint simd_gid, uint simd_lid)
                   
                  template<typename U = T>
                  static METAL_FUNC void load_unsafe (const device T *src, thread U dst[TN], const int src_offset=0)
                   
                  template<typename U = T>
                  static METAL_FUNC void load_safe (const device T *src, thread U dst[TN], const int src_offset=0, const int src_size=TN)
                   
                  static METAL_FUNC void run (const device T *mat, const device T *in_vec, device T *out_vec, const constant int &in_vec_size, const constant int &out_vec_size, const constant int &matrix_ld, const device out_mask_t *out_mask, const device op_mask_t *mat_mask, const device op_mask_t *vec_mask, const constant int *mask_strides, threadgroup AccT *tgp_memory, uint3 tid, uint3 lid, uint simd_gid, uint simd_lid)
                   
                  - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + +

                  Static Public Attributes

                  static constant constexpr const int threadsM = BM * SM
                   
                  static constant constexpr const int threadsN = BN * SN
                   
                  static constant constexpr const int blockM = threadsM * TM
                   
                  static constant constexpr const int blockN = threadsN * TN
                   
                  static constant constexpr const bool has_operand_mask = !metal::is_same_v<op_mask_t, nomask_t>
                   
                  static constant constexpr const bool has_output_mask = !metal::is_same_v<out_mask_t, nomask_t>
                   
                  static constant constexpr const bool has_mul_operand_mask
                   
                  static constant constexpr const bool has_mul_output_mask
                   
                  static constant constexpr const short tgp_mem_size = BN > 1 ? BN*(blockM + TM) : 0
                   
                  static constant constexpr const bool needs_tgp_reduction = BN > 1
                   
                  static constant constexpr const int threadsM = BM * SM
                   
                  static constant constexpr const int threadsN = BN * SN
                   
                  static constant constexpr const int blockM = threadsM * TM
                   
                  static constant constexpr const int blockN = threadsN * TN
                   
                  static constant constexpr const bool has_operand_mask = !metal::is_same_v<op_mask_t, nomask_t>
                   
                  static constant constexpr const bool has_output_mask = !metal::is_same_v<out_mask_t, nomask_t>
                   
                  static constant constexpr const bool has_mul_operand_mask
                   
                  static constant constexpr const bool has_mul_output_mask
                   
                  static constant constexpr const short tgp_mem_size = BN > 1 ? BN*(blockM + TM) : 0
                   
                  static constant constexpr const bool needs_tgp_reduction = BN > 1
                   

                  Member Function Documentation

                  - -

                  ◆ load_safe()

                  + +

                  ◆ load_safe()

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  +
                  +template<typename U = T>
                  - + diff --git a/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.html b/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.html index 569cd530d..fbc8f6011 100644 --- a/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.html +++ b/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.html @@ -129,8 +129,8 @@ Public Member Functions - - + + @@ -388,8 +388,8 @@ Public Member Functions - -

                  ◆ register_output_array()

                  + +

                  ◆ register_output_array()

                  @@ -397,7 +397,7 @@ Public Member Functions
                  - +
                  - + - + @@ -186,26 +190,28 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ load_unsafe()

                  + +

                  ◆ load_unsafe()

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  +
                  +template<typename U = T>
                  static METAL_FUNC void GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::load_safe static METAL_FUNC void GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::load_safe ( const device T * src,
                  thread T dst[TN], thread U dst[TN],
                  - + - + @@ -222,19 +228,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ run()

                  + +

                  ◆ run()

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  static METAL_FUNC void GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::load_unsafe static METAL_FUNC void GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::load_unsafe ( const device T * src,
                  thread T dst[TN], thread U dst[TN],
                  - + @@ -286,7 +292,7 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - + @@ -319,19 +325,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c

                  Member Data Documentation

                  - -

                  ◆ blockM

                  + +

                  ◆ blockM

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  static METAL_FUNC void GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::run static METAL_FUNC void GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::run ( const device T * mat,
                  threadgroup T * tgp_memory, threadgroup AccT * tgp_memory,
                  @@ -343,19 +349,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ blockN

                  + +

                  ◆ blockN

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const int GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::blockM = threadsM * TMconstant constexpr const int GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::blockM = threadsM * TM
                  @@ -367,19 +373,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ has_mul_operand_mask

                  + +

                  ◆ has_mul_operand_mask

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const int GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::blockN = threadsN * TNconstant constexpr const int GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::blockN = threadsN * TN
                  @@ -389,24 +395,24 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c
                  - +
                  constant constexpr const bool GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::has_mul_operand_maskconstant constexpr const bool GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::has_mul_operand_mask
                  Initial value:
                  =
                  -
                  has_operand_mask && !metal::is_same_v<op_mask_t, bool>
                  -
                  GEMVKernel::has_operand_mask
                  static constant constexpr const bool has_operand_mask
                  Definition gemv_masked.h:63
                  +
                  has_operand_mask && !metal::is_same_v<op_mask_t, bool>
                  +
                  GEMVKernel::has_operand_mask
                  static constant constexpr const bool has_operand_mask
                  Definition gemv_masked.h:64
                  - -

                  ◆ has_mul_output_mask

                  + +

                  ◆ has_mul_output_mask

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  @@ -416,24 +422,24 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c
                  - +
                  constant constexpr const bool GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::has_mul_output_maskconstant constexpr const bool GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::has_mul_output_mask
                  Initial value:
                  =
                  -
                  has_output_mask && !metal::is_same_v<out_mask_t, bool>
                  -
                  GEMVKernel::has_output_mask
                  static constant constexpr const bool has_output_mask
                  Definition gemv_masked.h:64
                  +
                  has_output_mask && !metal::is_same_v<out_mask_t, bool>
                  +
                  GEMVKernel::has_output_mask
                  static constant constexpr const bool has_output_mask
                  Definition gemv_masked.h:65
                  - -

                  ◆ has_operand_mask

                  + +

                  ◆ has_operand_mask

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  @@ -445,19 +451,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ has_output_mask

                  + +

                  ◆ has_output_mask

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const bool GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::has_operand_mask = !metal::is_same_v<op_mask_t, nomask_t>constant constexpr const bool GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::has_operand_mask = !metal::is_same_v<op_mask_t, nomask_t>
                  @@ -469,19 +475,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ needs_tgp_reduction

                  + +

                  ◆ needs_tgp_reduction

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const bool GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::has_output_mask = !metal::is_same_v<out_mask_t, nomask_t>constant constexpr const bool GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::has_output_mask = !metal::is_same_v<out_mask_t, nomask_t>
                  @@ -493,19 +499,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ tgp_mem_size

                  + +

                  ◆ tgp_mem_size

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const bool GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::needs_tgp_reduction = BN > 1constant constexpr const bool GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::needs_tgp_reduction = BN > 1
                  @@ -517,19 +523,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ threadsM

                  + +

                  ◆ threadsM

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const short GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::tgp_mem_size = BN > 1 ? BN*(blockM + TM) : 0constant constexpr const short GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::tgp_mem_size = BN > 1 ? BN*(blockM + TM) : 0
                  @@ -541,19 +547,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ threadsN

                  + +

                  ◆ threadsN

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const int GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::threadsM = BM * SMconstant constexpr const int GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::threadsM = BM * SM
                  diff --git a/docs/build/html/struct_g_e_m_v_kernel.js b/docs/build/html/struct_g_e_m_v_kernel.js index b3fb0a9c7..4da5e24e0 100644 --- a/docs/build/html/struct_g_e_m_v_kernel.js +++ b/docs/build/html/struct_g_e_m_v_kernel.js @@ -1,16 +1,16 @@ var struct_g_e_m_v_kernel = [ - [ "load_safe", "struct_g_e_m_v_kernel.html#a04bb72da9a93d6d1eba468fa311bbba7", null ], - [ "load_unsafe", "struct_g_e_m_v_kernel.html#a6013e9c5b2f72fa1311dd038172df0ce", null ], - [ "run", "struct_g_e_m_v_kernel.html#ac4a7b5011a0ea938ab1949bb1767fc1a", null ], - [ "blockM", "struct_g_e_m_v_kernel.html#a7281520100658811076400060663903c", null ], - [ "blockN", "struct_g_e_m_v_kernel.html#a2fef17f9c9aa0bdf530ad3554fb0988b", null ], - [ "has_mul_operand_mask", "struct_g_e_m_v_kernel.html#ad47223ee49b3cb7bf3746a2cec45f883", null ], - [ "has_mul_output_mask", "struct_g_e_m_v_kernel.html#a0edbf2dd6a6563e7afa6dab6b670615c", null ], - [ "has_operand_mask", "struct_g_e_m_v_kernel.html#ab00784dff1512a7b0919fcb4cfa5d50e", null ], - [ "has_output_mask", "struct_g_e_m_v_kernel.html#ab8b64c94f4c8f6f09c0777415589b487", null ], - [ "needs_tgp_reduction", "struct_g_e_m_v_kernel.html#ae8113fddf6fb637acfd12efd978b704c", null ], - [ "tgp_mem_size", "struct_g_e_m_v_kernel.html#a9ef4d0e62094d7033069f5dda5efb236", null ], - [ "threadsM", "struct_g_e_m_v_kernel.html#a1dd943fcbf5e7be435fc36bed589a641", null ], - [ "threadsN", "struct_g_e_m_v_kernel.html#a47bfab7d21dd18760d3e0937ad36b19d", null ] + [ "load_safe", "struct_g_e_m_v_kernel.html#a047eca250e7cbc928bce0e13de98e558", null ], + [ "load_unsafe", "struct_g_e_m_v_kernel.html#af96a768a213a95e7a4d8f3ec1948034f", null ], + [ "run", "struct_g_e_m_v_kernel.html#ac1a9e1d9853489dd928916912cc627a7", null ], + [ "blockM", "struct_g_e_m_v_kernel.html#a188ef7ed5c1d74d9b540b6d4ebf12f2e", null ], + [ "blockN", "struct_g_e_m_v_kernel.html#af22b6e5ed1a9d350866aaafa35d63a8a", null ], + [ "has_mul_operand_mask", "struct_g_e_m_v_kernel.html#a09f0e646822d45dc2543e31509552258", null ], + [ "has_mul_output_mask", "struct_g_e_m_v_kernel.html#ad54fb5c6f0f9a820365b638542693291", null ], + [ "has_operand_mask", "struct_g_e_m_v_kernel.html#a68bad880d1e689228ae4d3c6958cc6c1", null ], + [ "has_output_mask", "struct_g_e_m_v_kernel.html#a3b0b9ccf11bd5d7de50b9626fa9a22cc", null ], + [ "needs_tgp_reduction", "struct_g_e_m_v_kernel.html#ae1c8e57e6718f22732570cc92d9bcf99", null ], + [ "tgp_mem_size", "struct_g_e_m_v_kernel.html#a53514fa199efc5b7328052dac45aabab", null ], + [ "threadsM", "struct_g_e_m_v_kernel.html#afbe7ab8ebfa912ffbf3ba2cf4db24940", null ], + [ "threadsN", "struct_g_e_m_v_kernel.html#a23142b7400f1f678e5d6d69d87f51032", null ] ]; \ No newline at end of file diff --git a/docs/build/html/struct_g_e_m_v_t_kernel-members.html b/docs/build/html/struct_g_e_m_v_t_kernel-members.html index e5be39c29..c8ce99b6f 100644 --- a/docs/build/html/struct_g_e_m_v_t_kernel-members.html +++ b/docs/build/html/struct_g_e_m_v_t_kernel-members.html @@ -102,23 +102,23 @@ $(function(){initNavTree('struct_g_e_m_v_t_kernel.html',''); initResizable(true)
                  -
                  GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN > Member List
                  +
                  GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT > Member List
                  -

                  This is the complete list of members for GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >, including all inherited members.

                  +

                  This is the complete list of members for GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >, including all inherited members.

                  - +
                  constant constexpr const int GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::threadsN = BN * SNconstant constexpr const int GEMVKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::threadsN = BN * SN
                  - - - - - - - - - - - + + + + + + + + + + +
                  blockMGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  blockNGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  has_mul_operand_maskGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  has_mul_output_maskGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  has_operand_maskGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  has_output_maskGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  needs_tgp_reductionGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  run(const device T *mat, const device T *in_vec, device T *out_vec, const constant int &in_vec_size, const constant int &out_vec_size, const constant int &marix_ld, const device out_mask_t *out_mask, const device op_mask_t *mat_mask, const device op_mask_t *vec_mask, const constant int *mask_strides, threadgroup T *tgp_memory, uint3 tid, uint3 lid, uint simd_gid, uint simd_lid)GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >inlinestatic
                  tgp_mem_sizeGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  threadsMGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  threadsNGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >static
                  blockMGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  blockNGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  has_mul_operand_maskGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  has_mul_output_maskGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  has_operand_maskGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  has_output_maskGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  needs_tgp_reductionGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  run(const device T *mat, const device T *in_vec, device T *out_vec, const constant int &in_vec_size, const constant int &out_vec_size, const constant int &marix_ld, const device out_mask_t *out_mask, const device op_mask_t *mat_mask, const device op_mask_t *vec_mask, const constant int *mask_strides, threadgroup AccT *tgp_memory, uint3 tid, uint3 lid, uint simd_gid, uint simd_lid)GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >inlinestatic
                  tgp_mem_sizeGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  threadsMGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  threadsNGEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >static
                  diff --git a/docs/build/html/struct_g_e_m_v_t_kernel.html b/docs/build/html/struct_g_e_m_v_t_kernel.html index 34b49e54a..5f5478498 100644 --- a/docs/build/html/struct_g_e_m_v_t_kernel.html +++ b/docs/build/html/struct_g_e_m_v_t_kernel.html @@ -5,7 +5,7 @@ -MLX: GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN > Struct Template Reference +MLX: GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT > Struct Template Reference @@ -106,7 +106,7 @@ $(function(){initNavTree('struct_g_e_m_v_t_kernel.html',''); initResizable(true) Static Public Member Functions | Static Public Attributes | List of all members -
                  GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN > Struct Template Reference
                  +
                  GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT > Struct Template Reference
                  @@ -117,49 +117,49 @@ $(function(){initNavTree('struct_g_e_m_v_t_kernel.html',''); initResizable(true) - - + +

                  Static Public Member Functions

                  static METAL_FUNC void run (const device T *mat, const device T *in_vec, device T *out_vec, const constant int &in_vec_size, const constant int &out_vec_size, const constant int &marix_ld, const device out_mask_t *out_mask, const device op_mask_t *mat_mask, const device op_mask_t *vec_mask, const constant int *mask_strides, threadgroup T *tgp_memory, uint3 tid, uint3 lid, uint simd_gid, uint simd_lid)
                   
                  static METAL_FUNC void run (const device T *mat, const device T *in_vec, device T *out_vec, const constant int &in_vec_size, const constant int &out_vec_size, const constant int &marix_ld, const device out_mask_t *out_mask, const device op_mask_t *mat_mask, const device op_mask_t *vec_mask, const constant int *mask_strides, threadgroup AccT *tgp_memory, uint3 tid, uint3 lid, uint simd_gid, uint simd_lid)
                   
                  - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + +

                  Static Public Attributes

                  static constant constexpr const int threadsM = BM * SM
                   
                  static constant constexpr const int threadsN = BN * SN
                   
                  static constant constexpr const int blockM = threadsM * TM
                   
                  static constant constexpr const int blockN = threadsN * TN
                   
                  static constant constexpr const bool has_operand_mask = !metal::is_same_v<op_mask_t, nomask_t>
                   
                  static constant constexpr const bool has_output_mask = !metal::is_same_v<out_mask_t, nomask_t>
                   
                  static constant constexpr const bool has_mul_operand_mask
                   
                  static constant constexpr const bool has_mul_output_mask
                   
                  static constant constexpr const short tgp_mem_size = BM > 1 ? BM*(blockN + TN) : 0
                   
                  static constant constexpr const bool needs_tgp_reduction = BM > 1
                   
                  static constant constexpr const int threadsM = BM * SM
                   
                  static constant constexpr const int threadsN = BN * SN
                   
                  static constant constexpr const int blockM = threadsM * TM
                   
                  static constant constexpr const int blockN = threadsN * TN
                   
                  static constant constexpr const bool has_operand_mask = !metal::is_same_v<op_mask_t, nomask_t>
                   
                  static constant constexpr const bool has_output_mask = !metal::is_same_v<out_mask_t, nomask_t>
                   
                  static constant constexpr const bool has_mul_operand_mask
                   
                  static constant constexpr const bool has_mul_output_mask
                   
                  static constant constexpr const short tgp_mem_size = BM > 1 ? BM*(blockN + TN) : 0
                   
                  static constant constexpr const bool needs_tgp_reduction = BM > 1
                   

                  Detailed Description

                  -
                  template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  -struct GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >

                  Vector matrix multiplication.

                  +
                  template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  +struct GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >

                  Vector matrix multiplication.

                  Member Function Documentation

                  - -

                  ◆ run()

                  + +

                  ◆ run()

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - + @@ -211,7 +211,7 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - + @@ -244,19 +244,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c

                  Member Data Documentation

                  - -

                  ◆ blockM

                  + +

                  ◆ blockM

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  static METAL_FUNC void GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::run static METAL_FUNC void GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::run ( const device T * mat,
                  threadgroup T * tgp_memory, threadgroup AccT * tgp_memory,
                  @@ -268,19 +268,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ blockN

                  + +

                  ◆ blockN

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const int GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::blockM = threadsM * TMconstant constexpr const int GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::blockM = threadsM * TM
                  @@ -292,19 +292,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ has_mul_operand_mask

                  + +

                  ◆ has_mul_operand_mask

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const int GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::blockN = threadsN * TNconstant constexpr const int GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::blockN = threadsN * TN
                  @@ -314,24 +314,24 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c
                  - +
                  constant constexpr const bool GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::has_mul_operand_maskconstant constexpr const bool GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::has_mul_operand_mask
                  Initial value:
                  =
                  -
                  has_operand_mask && !metal::is_same_v<op_mask_t, bool>
                  -
                  GEMVKernel::has_operand_mask
                  static constant constexpr const bool has_operand_mask
                  Definition gemv_masked.h:63
                  +
                  has_operand_mask && !metal::is_same_v<op_mask_t, bool>
                  +
                  GEMVKernel::has_operand_mask
                  static constant constexpr const bool has_operand_mask
                  Definition gemv_masked.h:64
                  - -

                  ◆ has_mul_output_mask

                  + +

                  ◆ has_mul_output_mask

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  @@ -341,24 +341,24 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c
                  - +
                  constant constexpr const bool GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::has_mul_output_maskconstant constexpr const bool GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::has_mul_output_mask
                  Initial value:
                  =
                  -
                  has_output_mask && !metal::is_same_v<out_mask_t, bool>
                  -
                  GEMVKernel::has_output_mask
                  static constant constexpr const bool has_output_mask
                  Definition gemv_masked.h:64
                  +
                  has_output_mask && !metal::is_same_v<out_mask_t, bool>
                  +
                  GEMVKernel::has_output_mask
                  static constant constexpr const bool has_output_mask
                  Definition gemv_masked.h:65
                  - -

                  ◆ has_operand_mask

                  + +

                  ◆ has_operand_mask

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  @@ -370,19 +370,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ has_output_mask

                  + +

                  ◆ has_output_mask

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const bool GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::has_operand_mask = !metal::is_same_v<op_mask_t, nomask_t>constant constexpr const bool GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::has_operand_mask = !metal::is_same_v<op_mask_t, nomask_t>
                  @@ -394,19 +394,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ needs_tgp_reduction

                  + +

                  ◆ needs_tgp_reduction

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const bool GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::has_output_mask = !metal::is_same_v<out_mask_t, nomask_t>constant constexpr const bool GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::has_output_mask = !metal::is_same_v<out_mask_t, nomask_t>
                  @@ -418,19 +418,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ tgp_mem_size

                  + +

                  ◆ tgp_mem_size

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const bool GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::needs_tgp_reduction = BM > 1constant constexpr const bool GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::needs_tgp_reduction = BM > 1
                  @@ -442,19 +442,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ threadsM

                  + +

                  ◆ threadsM

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const short GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::tgp_mem_size = BM > 1 ? BM*(blockN + TN) : 0constant constexpr const short GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::tgp_mem_size = BM > 1 ? BM*(blockN + TN) : 0
                  @@ -466,19 +466,19 @@ template<typename T, typename out_mask_t, typename op_mask_t, const int BM, c - -

                  ◆ threadsN

                  + +

                  ◆ threadsN

                  -template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN>
                  +template<typename T, typename out_mask_t, typename op_mask_t, const int BM, const int BN, const int SM, const int SN, const int TM, const int TN, typename AccT = float>
                  - +
                  constant constexpr const int GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::threadsM = BM * SMconstant constexpr const int GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::threadsM = BM * SM
                  diff --git a/docs/build/html/struct_g_e_m_v_t_kernel.js b/docs/build/html/struct_g_e_m_v_t_kernel.js index 23e833ffd..65577fb0c 100644 --- a/docs/build/html/struct_g_e_m_v_t_kernel.js +++ b/docs/build/html/struct_g_e_m_v_t_kernel.js @@ -1,14 +1,14 @@ var struct_g_e_m_v_t_kernel = [ - [ "run", "struct_g_e_m_v_t_kernel.html#a5d68656832de892f33db939005713927", null ], - [ "blockM", "struct_g_e_m_v_t_kernel.html#a2ae8ce535d59cccf453381b4485a77f0", null ], - [ "blockN", "struct_g_e_m_v_t_kernel.html#a60be87666006ba0bf88bc8e6902da42a", null ], - [ "has_mul_operand_mask", "struct_g_e_m_v_t_kernel.html#a8db6f01f96a36b216acd801c34a96ef5", null ], - [ "has_mul_output_mask", "struct_g_e_m_v_t_kernel.html#a8eb06f6569e4042e24fee220b11fa10d", null ], - [ "has_operand_mask", "struct_g_e_m_v_t_kernel.html#a6729d6e63e76a1e9c7c8e78d9aac4869", null ], - [ "has_output_mask", "struct_g_e_m_v_t_kernel.html#aaefdf8f023da255bbb70a0c3e3408626", null ], - [ "needs_tgp_reduction", "struct_g_e_m_v_t_kernel.html#a67be7ec69c3791f02e97ccdb00ae0e03", null ], - [ "tgp_mem_size", "struct_g_e_m_v_t_kernel.html#a48a09a21d7b822f380d040c752b785d7", null ], - [ "threadsM", "struct_g_e_m_v_t_kernel.html#a4a53e73a581aa8881b1f86ce653519e6", null ], - [ "threadsN", "struct_g_e_m_v_t_kernel.html#ade6f15a9744616de9dd71498ad7e758d", null ] + [ "run", "struct_g_e_m_v_t_kernel.html#a1a96467ee6957e62c2aa1061431095a4", null ], + [ "blockM", "struct_g_e_m_v_t_kernel.html#aa3f9e771c59770a72b73fb673eb7bf71", null ], + [ "blockN", "struct_g_e_m_v_t_kernel.html#a2091b9804b702cbb995899312e3da417", null ], + [ "has_mul_operand_mask", "struct_g_e_m_v_t_kernel.html#a94f56f0ecf1f148f0513312325f33653", null ], + [ "has_mul_output_mask", "struct_g_e_m_v_t_kernel.html#a19df54577e341044dc8e57cc5b6147f3", null ], + [ "has_operand_mask", "struct_g_e_m_v_t_kernel.html#aef8622b2f76d1ff272ced396c89e829d", null ], + [ "has_output_mask", "struct_g_e_m_v_t_kernel.html#a19bcb2d9377493a81da072f33711de33", null ], + [ "needs_tgp_reduction", "struct_g_e_m_v_t_kernel.html#a0cb1a4fa56fab7090b7c0fdc69a5470a", null ], + [ "tgp_mem_size", "struct_g_e_m_v_t_kernel.html#a3521f62aa2f4070fdc6858874121e3b4", null ], + [ "threadsM", "struct_g_e_m_v_t_kernel.html#a09cb1cda991a8d1b8dc83b22f8cab994", null ], + [ "threadsN", "struct_g_e_m_v_t_kernel.html#a2c30d01fd0932dfc3b4ef1e7e650d30f", null ] ]; \ No newline at end of file diff --git a/docs/build/html/structmlx_1_1core_1_1_command_encoder-members.html b/docs/build/html/structmlx_1_1core_1_1_command_encoder-members.html index 47bd0cae3..f35cc8a7b 100644 --- a/docs/build/html/structmlx_1_1core_1_1_command_encoder-members.html +++ b/docs/build/html/structmlx_1_1core_1_1_command_encoder-members.html @@ -117,7 +117,7 @@ $(function(){initNavTree('structmlx_1_1core_1_1_command_encoder.html',''); initR - + diff --git a/docs/build/html/structmlx_1_1core_1_1_command_encoder.html b/docs/build/html/structmlx_1_1core_1_1_command_encoder.html index 99d5e709c..07eb6f813 100644 --- a/docs/build/html/structmlx_1_1core_1_1_command_encoder.html +++ b/docs/build/html/structmlx_1_1core_1_1_command_encoder.html @@ -129,8 +129,8 @@ Public Member Functions - - + + @@ -388,8 +388,8 @@ Public Member Functions - -

                  ◆ register_output_array()

                  + +

                  ◆ register_output_array()

                  @@ -397,7 +397,7 @@ Public Member Functions
                  - +
                  - +
                  constant constexpr const int GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN >::threadsN = BN * SNconstant constexpr const int GEMVTKernel< T, out_mask_t, op_mask_t, BM, BN, SM, SN, TM, TN, AccT >::threadsN = BN * SN
                  maybeInsertBarrier()mlx::core::CommandEncoder
                  operator=(const CommandEncoder &)=deletemlx::core::CommandEncoder
                  outputs()mlx::core::CommandEncoderinline
                  register_output_array(array &a)mlx::core::CommandEncoder
                  register_output_array(const array &a)mlx::core::CommandEncoder
                  set_buffer(const MTL::Buffer *buf, int idx, int64_t offset=0)mlx::core::CommandEncoder
                  set_bytes(const T *v, int n, int idx)mlx::core::CommandEncoderinline
                  set_bytes(const T &v, int idx)mlx::core::CommandEncoderinline
                   
                  void set_output_array (array &a, int idx, int64_t offset=0)
                   
                  void register_output_array (array &a)
                   
                  void register_output_array (const array &a)
                   
                  void dispatch_threadgroups (MTL::Size grid_dims, MTL::Size group_dims)
                   
                  void dispatch_threads (MTL::Size grid_dims, MTL::Size group_dims)
                  void mlx::core::metal::CommandEncoder::register_output_array (array & a)const array & a)
                  diff --git a/docs/build/html/structmlx_1_1core_1_1_command_encoder.js b/docs/build/html/structmlx_1_1core_1_1_command_encoder.js index a9eec42dc..ce7025b5d 100644 --- a/docs/build/html/structmlx_1_1core_1_1_command_encoder.js +++ b/docs/build/html/structmlx_1_1core_1_1_command_encoder.js @@ -11,7 +11,7 @@ var structmlx_1_1core_1_1_command_encoder = [ "maybeInsertBarrier", "structmlx_1_1core_1_1_command_encoder.html#ad538ae88f90560063f9ba502e2795991", null ], [ "operator=", "structmlx_1_1core_1_1_command_encoder.html#a3f42a1362b4a513fa89e7b3dcc570a8e", null ], [ "outputs", "structmlx_1_1core_1_1_command_encoder.html#aefa48740fdee884f02e2d379bca4e78f", null ], - [ "register_output_array", "structmlx_1_1core_1_1_command_encoder.html#ada20558738968ca2ecdcd95f228e028a", null ], + [ "register_output_array", "structmlx_1_1core_1_1_command_encoder.html#a2d42827ff8551ec43cef2d33b9051c0f", null ], [ "set_buffer", "structmlx_1_1core_1_1_command_encoder.html#ae890f5cefa4ae24ae0f5d8e46a313a92", null ], [ "set_bytes", "structmlx_1_1core_1_1_command_encoder.html#abc52d18ea87d213c47fd26062c829849", null ], [ "set_bytes", "structmlx_1_1core_1_1_command_encoder.html#a9c343f791812a45c6c03a5c9f27f74d5", null ], diff --git a/docs/build/html/structmlx_1_1core_1_1_scalar_vector-members.html b/docs/build/html/structmlx_1_1core_1_1_scalar_vector-members.html index 3a1af7dd7..43186464a 100644 --- a/docs/build/html/structmlx_1_1core_1_1_scalar_vector-members.html +++ b/docs/build/html/structmlx_1_1core_1_1_scalar_vector-members.html @@ -108,9 +108,7 @@ $(function(){initNavTree('structmlx_1_1core_1_1_scalar_vector.html',''); initRes

                  This is the complete list of members for mlx::core::ScalarVector< Op >, including all inherited members.

                  - - - +
                  opmlx::core::ScalarVector< Op >
                  operator()(const T *a, const T *b, U *dst, int size)mlx::core::ScalarVector< Op >inline
                  ScalarVector(Op op_)mlx::core::ScalarVector< Op >inline
                  operator()(const T *a, const T *b, U *dst, int size)mlx::core::ScalarVector< Op >inline
                  diff --git a/docs/build/html/structmlx_1_1core_1_1_scalar_vector.html b/docs/build/html/structmlx_1_1core_1_1_scalar_vector.html index e1cefb73d..fb2dd48b7 100644 --- a/docs/build/html/structmlx_1_1core_1_1_scalar_vector.html +++ b/docs/build/html/structmlx_1_1core_1_1_scalar_vector.html @@ -104,7 +104,6 @@ $(function(){initNavTree('structmlx_1_1core_1_1_scalar_vector.html',''); initRes
                  Public Member Functions | -Public Attributes | List of all members
                  mlx::core::ScalarVector< Op > Struct Template Reference
                  @@ -114,45 +113,10 @@ $(function(){initNavTree('structmlx_1_1core_1_1_scalar_vector.html',''); initRes - - -

                  Public Member Functions

                   ScalarVector (Op op_)
                   
                  template<typename T, typename U>
                  void operator() (const T *a, const T *b, U *dst, int size)
                   
                  - - -

                  -Public Attributes

                  Op op
                   
                  -

                  Constructor & Destructor Documentation

                  - -

                  ◆ ScalarVector()

                  - -
                  -
                  -
                  -template<typename Op>
                  - - - - - -
                  - - - - - - - -
                  mlx::core::ScalarVector< Op >::ScalarVector (Op op_)
                  -                   		-inline
                  -
                  - -
                  -

                  Member Function Documentation

                  ◆ operator()()

                  @@ -195,23 +159,6 @@ template<typename T, typename U>
                  -
                  -
                  -

                  Member Data Documentation

                  - -

                  ◆ op

                  - -
                  -
                  -
                  -template<typename Op>
                  - - - - -
                  Op mlx::core::ScalarVector< Op >::op
                  -
                  -
                  The documentation for this struct was generated from the following file:
                    diff --git a/docs/build/html/structmlx_1_1core_1_1_scalar_vector.js b/docs/build/html/structmlx_1_1core_1_1_scalar_vector.js index bea7d3e61..34e57da88 100644 --- a/docs/build/html/structmlx_1_1core_1_1_scalar_vector.js +++ b/docs/build/html/structmlx_1_1core_1_1_scalar_vector.js @@ -1,6 +1,4 @@ var structmlx_1_1core_1_1_scalar_vector = [ - [ "ScalarVector", "structmlx_1_1core_1_1_scalar_vector.html#a69d6a3ddd7586e8e19a42c5e6f5a287b", null ], - [ "operator()", "structmlx_1_1core_1_1_scalar_vector.html#ab174fe55970fb4ee1c6a2b7628a24df1", null ], - [ "op", "structmlx_1_1core_1_1_scalar_vector.html#ac9c2214744bc972150740e169b603b9b", null ] + [ "operator()", "structmlx_1_1core_1_1_scalar_vector.html#ab174fe55970fb4ee1c6a2b7628a24df1", null ] ]; \ No newline at end of file diff --git a/docs/build/html/structmlx_1_1core_1_1_vector_scalar-members.html b/docs/build/html/structmlx_1_1core_1_1_vector_scalar-members.html index 1633cb018..d690dfa4c 100644 --- a/docs/build/html/structmlx_1_1core_1_1_vector_scalar-members.html +++ b/docs/build/html/structmlx_1_1core_1_1_vector_scalar-members.html @@ -108,9 +108,7 @@ $(function(){initNavTree('structmlx_1_1core_1_1_vector_scalar.html',''); initRes

                    This is the complete list of members for mlx::core::VectorScalar< Op >, including all inherited members.

                    - - - +
                    opmlx::core::VectorScalar< Op >
                    operator()(const T *a, const T *b, U *dst, int size)mlx::core::VectorScalar< Op >inline
                    VectorScalar(Op op_)mlx::core::VectorScalar< Op >inline
                    operator()(const T *a, const T *b, U *dst, int size)mlx::core::VectorScalar< Op >inline
                  diff --git a/docs/build/html/structmlx_1_1core_1_1_vector_scalar.html b/docs/build/html/structmlx_1_1core_1_1_vector_scalar.html index 080b339ea..a6c519b72 100644 --- a/docs/build/html/structmlx_1_1core_1_1_vector_scalar.html +++ b/docs/build/html/structmlx_1_1core_1_1_vector_scalar.html @@ -104,7 +104,6 @@ $(function(){initNavTree('structmlx_1_1core_1_1_vector_scalar.html',''); initRes
                  Public Member Functions | -Public Attributes | List of all members
                  mlx::core::VectorScalar< Op > Struct Template Reference
                  @@ -114,45 +113,10 @@ $(function(){initNavTree('structmlx_1_1core_1_1_vector_scalar.html',''); initRes - - -

                  Public Member Functions

                   VectorScalar (Op op_)
                   
                  template<typename T, typename U>
                  void operator() (const T *a, const T *b, U *dst, int size)
                   
                  - - -

                  -Public Attributes

                  Op op
                   
                  -

                  Constructor & Destructor Documentation

                  - -

                  ◆ VectorScalar()

                  - -
                  -
                  -
                  -template<typename Op>
                  - - - - - -
                  - - - - - - - -
                  mlx::core::VectorScalar< Op >::VectorScalar (Op op_)
                  -                   		-inline
                  -
                  - -
                  -

                  Member Function Documentation

                  ◆ operator()()

                  @@ -195,23 +159,6 @@ template<typename T, typename U>
                  -
                  - -

                  Member Data Documentation

                  - -

                  ◆ op

                  - -
                  -
                  -
                  -template<typename Op>
                  - - - - -
                  Op mlx::core::VectorScalar< Op >::op
                  -
                  -
                  The documentation for this struct was generated from the following file:
                    diff --git a/docs/build/html/structmlx_1_1core_1_1_vector_scalar.js b/docs/build/html/structmlx_1_1core_1_1_vector_scalar.js index b9712673b..b25b45d27 100644 --- a/docs/build/html/structmlx_1_1core_1_1_vector_scalar.js +++ b/docs/build/html/structmlx_1_1core_1_1_vector_scalar.js @@ -1,6 +1,4 @@ var structmlx_1_1core_1_1_vector_scalar = [ - [ "VectorScalar", "structmlx_1_1core_1_1_vector_scalar.html#a97088143e6d301d753dcdd1ccdd82287", null ], - [ "operator()", "structmlx_1_1core_1_1_vector_scalar.html#a1af3ff644ce023a7e4f92a7c3634c44f", null ], - [ "op", "structmlx_1_1core_1_1_vector_scalar.html#a5fe1744adb58aaa845acca1e46725537", null ] + [ "operator()", "structmlx_1_1core_1_1_vector_scalar.html#a1af3ff644ce023a7e4f92a7c3634c44f", null ] ]; \ No newline at end of file diff --git a/docs/build/html/structmlx_1_1core_1_1_vector_vector-members.html b/docs/build/html/structmlx_1_1core_1_1_vector_vector-members.html index 6ea14dd26..7fb418bc7 100644 --- a/docs/build/html/structmlx_1_1core_1_1_vector_vector-members.html +++ b/docs/build/html/structmlx_1_1core_1_1_vector_vector-members.html @@ -108,9 +108,7 @@ $(function(){initNavTree('structmlx_1_1core_1_1_vector_vector.html',''); initRes

                    This is the complete list of members for mlx::core::VectorVector< Op >, including all inherited members.

                    - - - +
                    opmlx::core::VectorVector< Op >
                    operator()(const T *a, const T *b, U *dst, int size)mlx::core::VectorVector< Op >inline
                    VectorVector(Op op_)mlx::core::VectorVector< Op >inline
                    operator()(const T *a, const T *b, U *dst, int size)mlx::core::VectorVector< Op >inline
                    diff --git a/docs/build/html/structmlx_1_1core_1_1_vector_vector.html b/docs/build/html/structmlx_1_1core_1_1_vector_vector.html index 983ff5b72..7a2b61c66 100644 --- a/docs/build/html/structmlx_1_1core_1_1_vector_vector.html +++ b/docs/build/html/structmlx_1_1core_1_1_vector_vector.html @@ -104,7 +104,6 @@ $(function(){initNavTree('structmlx_1_1core_1_1_vector_vector.html',''); initRes
                    Public Member Functions | -Public Attributes | List of all members
                    mlx::core::VectorVector< Op > Struct Template Reference
                    @@ -114,45 +113,10 @@ $(function(){initNavTree('structmlx_1_1core_1_1_vector_vector.html',''); initRes - - -

                    Public Member Functions

                     VectorVector (Op op_)
                     
                    template<typename T, typename U>
                    void operator() (const T *a, const T *b, U *dst, int size)
                     
                    - - -

                    -Public Attributes

                    Op op
                     
                    -

                    Constructor & Destructor Documentation

                    - -

                    ◆ VectorVector()

                    - -
                    -
                    -
                    -template<typename Op>
                    - - - - - -
                    - - - - - - - -
                    mlx::core::VectorVector< Op >::VectorVector (Op op_)
                    -                     		-inline
                    -
                    - -
                    -

                    Member Function Documentation

                    ◆ operator()()

                    @@ -195,23 +159,6 @@ template<typename T, typename U>
                  -
                  - -

                  Member Data Documentation

                  - -

                  ◆ op

                  - -
                  -
                  -
                  -template<typename Op>
                  - - - - -
                  Op mlx::core::VectorVector< Op >::op
                  -
                  -
                  The documentation for this struct was generated from the following file:
                    diff --git a/docs/build/html/structmlx_1_1core_1_1_vector_vector.js b/docs/build/html/structmlx_1_1core_1_1_vector_vector.js index f17c57aa2..c8824b4cf 100644 --- a/docs/build/html/structmlx_1_1core_1_1_vector_vector.js +++ b/docs/build/html/structmlx_1_1core_1_1_vector_vector.js @@ -1,6 +1,4 @@ var structmlx_1_1core_1_1_vector_vector = [ - [ "VectorVector", "structmlx_1_1core_1_1_vector_vector.html#a4867666c95c597a113afb64f173cc022", null ], - [ "operator()", "structmlx_1_1core_1_1_vector_vector.html#a97a0bed419933d7685238a962f2e4215", null ], - [ "op", "structmlx_1_1core_1_1_vector_vector.html#a6d69d070c75cf0281e11e36e0717ab50", null ] + [ "operator()", "structmlx_1_1core_1_1_vector_vector.html#a97a0bed419933d7685238a962f2e4215", null ] ]; \ No newline at end of file diff --git a/docs/build/html/structmlx_1_1core_1_1cpu_1_1_command_encoder-members.html b/docs/build/html/structmlx_1_1core_1_1cpu_1_1_command_encoder-members.html new file mode 100644 index 000000000..c996df6f4 --- /dev/null +++ b/docs/build/html/structmlx_1_1core_1_1cpu_1_1_command_encoder-members.html @@ -0,0 +1,131 @@ + + + + + + + +MLX: Member List + + + + + + + + + + + + + + + + +
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                    mlx::core::cpu::CommandEncoder Member List
                    +
                    +
                    + +

                    This is the complete list of members for mlx::core::cpu::CommandEncoder, including all inherited members.

                    + + + + + + + + + + + + +
                    add_temporaries(std::vector< array > arrays)mlx::core::cpu::CommandEncoderinline
                    add_temporary(array arr)mlx::core::cpu::CommandEncoderinline
                    CommandEncoder(Stream stream)mlx::core::cpu::CommandEncoderinline
                    CommandEncoder(const CommandEncoder &)=deletemlx::core::cpu::CommandEncoder
                    CommandEncoder(CommandEncoder &&)=deletemlx::core::cpu::CommandEncoder
                    dispatch(F &&f, Args &&... args)mlx::core::cpu::CommandEncoderinline
                    operator=(const CommandEncoder &)=deletemlx::core::cpu::CommandEncoder
                    operator=(CommandEncoder &&)=deletemlx::core::cpu::CommandEncoder
                    set_input_array(const array &a)mlx::core::cpu::CommandEncoderinline
                    set_output_array(array &a)mlx::core::cpu::CommandEncoderinline
                    temporaries()mlx::core::cpu::CommandEncoderinline
                    +
                    + + + + diff --git a/docs/build/html/structmlx_1_1core_1_1cpu_1_1_command_encoder.html b/docs/build/html/structmlx_1_1core_1_1cpu_1_1_command_encoder.html new file mode 100644 index 000000000..8eb9a66b6 --- /dev/null +++ b/docs/build/html/structmlx_1_1core_1_1cpu_1_1_command_encoder.html @@ -0,0 +1,436 @@ + + + + + + + +MLX: mlx::core::cpu::CommandEncoder Struct Reference + + + + + + + + + + + + + + + + +
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                    Loading...
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                    +
                    +
                    +
                    +
                    + +
                    +
                    +Public Member Functions | +List of all members
                    +
                    mlx::core::cpu::CommandEncoder Struct Reference
                    +
                    +
                    + +

                    #include <encoder.h>

                    + + + + + + + + + + + + + + + + + + + + + + + + + +

                    +Public Member Functions

                     CommandEncoder (Stream stream)
                     
                     CommandEncoder (const CommandEncoder &)=delete
                     
                    CommandEncoder & operator= (const CommandEncoder &)=delete
                     
                     CommandEncoder (CommandEncoder &&)=delete
                     
                    CommandEncoder & operator= (CommandEncoder &&)=delete
                     
                    void set_input_array (const array &a)
                     
                    void set_output_array (array &a)
                     
                    void add_temporary (array arr)
                     
                    void add_temporaries (std::vector< array > arrays)
                     
                    std::vector< array > & temporaries ()
                     
                    template<class F, class... Args>
                    void dispatch (F &&f, Args &&... args)
                     
                    +

                    Constructor & Destructor Documentation

                    + +

                    ◆ CommandEncoder() [1/3]

                    + +
                    +
                    + + + + + +
                    + + + + + + + +
                    mlx::core::cpu::CommandEncoder::CommandEncoder (Stream stream)
                    +                     		+inline
                    +
                    + +
                    +
                    + +

                    ◆ CommandEncoder() [2/3]

                    + +
                    +
                    + + + + + +
                    + + + + + + + +
                    mlx::core::cpu::CommandEncoder::CommandEncoder (const CommandEncoder & )
                    +                     		+delete
                    +
                    + +
                    +
                    + +

                    ◆ CommandEncoder() [3/3]

                    + +
                    +
                    + + + + + +
                    + + + + + + + +
                    mlx::core::cpu::CommandEncoder::CommandEncoder (CommandEncoder && )
                    +                     		+delete
                    +
                    + +
                    +
                    +

                    Member Function Documentation

                    + +

                    ◆ add_temporaries()

                    + +
                    +
                    + + + + + +
                    + + + + + + + +
                    void mlx::core::cpu::CommandEncoder::add_temporaries (std::vector< array > arrays)
                    +                     		+inline
                    +
                    + +
                    +
                    + +

                    ◆ add_temporary()

                    + +
                    +
                    + + + + + +
                    + + + + + + + +
                    void mlx::core::cpu::CommandEncoder::add_temporary (array arr)
                    +                     		+inline
                    +
                    + +
                    +
                    + +

                    ◆ dispatch()

                    + +
                    +
                    +
                    +template<class F, class... Args>
                    + + + + + +
                    + + + + + + + + + + + +
                    void mlx::core::cpu::CommandEncoder::dispatch (F && f,
                    Args &&... args )
                    +                     		+inline
                    +
                    + +
                    +
                    + +

                    ◆ operator=() [1/2]

                    + +
                    +
                    + + + + + +
                    + + + + + + + +
                    CommandEncoder & mlx::core::cpu::CommandEncoder::operator= (CommandEncoder && )
                    +                     		+delete
                    +
                    + +
                    +
                    + +

                    ◆ operator=() [2/2]

                    + +
                    +
                    + + + + + +
                    + + + + + + + +
                    CommandEncoder & mlx::core::cpu::CommandEncoder::operator= (const CommandEncoder & )
                    +                     		+delete
                    +
                    + +
                    +
                    + +

                    ◆ set_input_array()

                    + +
                    +
                    + + + + + +
                    + + + + + + + +
                    void mlx::core::cpu::CommandEncoder::set_input_array (const array & a)
                    +                     		+inline
                    +
                    + +
                    +
                    + +

                    ◆ set_output_array()

                    + +
                    +
                    + + + + + +
                    + + + + + + + +
                    void mlx::core::cpu::CommandEncoder::set_output_array (array & a)
                    +                     		+inline
                    +
                    + +
                    +
                    + +

                    ◆ temporaries()

                    + +
                    +
                    + + + + + +
                    + + + + + + + +
                    std::vector< array > & mlx::core::cpu::CommandEncoder::temporaries ()
                    +                     		+inline
                    +
                    + +
                    +
                    +
                    The documentation for this struct was generated from the following file: +
                    +
                    + + + + diff --git a/docs/build/html/structmlx_1_1core_1_1cpu_1_1_command_encoder.js b/docs/build/html/structmlx_1_1core_1_1cpu_1_1_command_encoder.js new file mode 100644 index 000000000..db4a0c39a --- /dev/null +++ b/docs/build/html/structmlx_1_1core_1_1cpu_1_1_command_encoder.js @@ -0,0 +1,14 @@ +var structmlx_1_1core_1_1cpu_1_1_command_encoder = +[ + [ "CommandEncoder", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html#a23815084f53da65b092624c89df7383c", null ], + [ "CommandEncoder", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html#a8e66b11850caa812b1eab2304493aa95", null ], + [ "CommandEncoder", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html#aa82e91e3b530f13126f674a6f4902096", null ], + [ "add_temporaries", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html#a30676a55a977418879a6a3a8a858d7c3", null ], + [ "add_temporary", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html#a0879746a3ca3531a081de1bcf484fa31", null ], + [ "dispatch", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html#ae7753ac99229f9241c41bcf1b5216c9b", null ], + [ "operator=", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html#af2623c4a8fd0408e5be2c5fabaf98771", null ], + [ "operator=", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html#a3d4415f4022da093cee23ef6f2a50c7c", null ], + [ "set_input_array", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html#aa0646f94b37d9d419b0e379c8b81a5fe", null ], + [ "set_output_array", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html#addd04a642072b7097faa74d1a924147b", null ], + [ "temporaries", "structmlx_1_1core_1_1cpu_1_1_command_encoder.html#a61e90a31f29ae3ffe5f6f1e7672f79b0", null ] +]; \ No newline at end of file diff --git a/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder-members.html b/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder-members.html index 83ec674e6..fedf36aa0 100644 --- a/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder-members.html +++ b/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder-members.html @@ -117,7 +117,7 @@ $(function(){initNavTree('structmlx_1_1core_1_1metal_1_1_command_encoder.html','
                  maybeInsertBarrier()mlx::core::metal::CommandEncoder
                  operator=(const CommandEncoder &)=deletemlx::core::metal::CommandEncoder
                  outputs()mlx::core::metal::CommandEncoderinline
                  register_output_array(array &a)mlx::core::metal::CommandEncoder
                  register_output_array(const array &a)mlx::core::metal::CommandEncoder
                  set_buffer(const MTL::Buffer *buf, int idx, int64_t offset=0)mlx::core::metal::CommandEncoder
                  set_bytes(const T *v, int n, int idx)mlx::core::metal::CommandEncoderinline
                  set_bytes(const T &v, int idx)mlx::core::metal::CommandEncoderinline
                   
                  void set_output_array (array &a, int idx, int64_t offset=0)
                   
                  void register_output_array (array &a)
                   
                  void register_output_array (const array &a)
                   
                  void dispatch_threadgroups (MTL::Size grid_dims, MTL::Size group_dims)
                   
                  void dispatch_threads (MTL::Size grid_dims, MTL::Size group_dims)
                  void mlx::core::metal::CommandEncoder::register_output_array (array & a)const array & a)
                  diff --git a/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.js b/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.js index f70a1b4ca..56cc8bdf3 100644 --- a/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.js +++ b/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.js @@ -11,7 +11,7 @@ var structmlx_1_1core_1_1metal_1_1_command_encoder = [ "maybeInsertBarrier", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#ad538ae88f90560063f9ba502e2795991", null ], [ "operator=", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#a3f42a1362b4a513fa89e7b3dcc570a8e", null ], [ "outputs", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#aefa48740fdee884f02e2d379bca4e78f", null ], - [ "register_output_array", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#ada20558738968ca2ecdcd95f228e028a", null ], + [ "register_output_array", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#a2d42827ff8551ec43cef2d33b9051c0f", null ], [ "set_buffer", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#ae890f5cefa4ae24ae0f5d8e46a313a92", null ], [ "set_bytes", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#abc52d18ea87d213c47fd26062c829849", null ], [ "set_bytes", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#a9c343f791812a45c6c03a5c9f27f74d5", null ], diff --git a/docs/build/html/structmlx_1_1core_1_1scheduler_1_1_stream_thread-members.html b/docs/build/html/structmlx_1_1core_1_1scheduler_1_1_stream_thread-members.html index 5276a85f6..cc7eb62bb 100644 --- a/docs/build/html/structmlx_1_1core_1_1scheduler_1_1_stream_thread-members.html +++ b/docs/build/html/structmlx_1_1core_1_1scheduler_1_1_stream_thread-members.html @@ -113,11 +113,10 @@ $(function(){initNavTree('structmlx_1_1core_1_1scheduler_1_1_stream_thread.html' mtxmlx::core::scheduler::StreamThread qmlx::core::scheduler::StreamThread stopmlx::core::scheduler::StreamThread - streammlx::core::scheduler::StreamThread - StreamThread(Stream stream)mlx::core::scheduler::StreamThreadinline - threadmlx::core::scheduler::StreamThread - thread_fn()mlx::core::scheduler::StreamThreadinline - ~StreamThread()mlx::core::scheduler::StreamThreadinline + StreamThread()mlx::core::scheduler::StreamThreadinline + threadmlx::core::scheduler::StreamThread + thread_fn()mlx::core::scheduler::StreamThreadinline + ~StreamThread()mlx::core::scheduler::StreamThreadinline
                  diff --git a/docs/build/html/structmlx_1_1core_1_1scheduler_1_1_stream_thread.html b/docs/build/html/structmlx_1_1core_1_1scheduler_1_1_stream_thread.html index bedbb45af..b26e2d6df 100644 --- a/docs/build/html/structmlx_1_1core_1_1scheduler_1_1_stream_thread.html +++ b/docs/build/html/structmlx_1_1core_1_1scheduler_1_1_stream_thread.html @@ -114,8 +114,8 @@ $(function(){initNavTree('structmlx_1_1core_1_1scheduler_1_1_stream_thread.html' - - + + @@ -134,14 +134,12 @@ Public Attributes - -

                  Public Member Functions

                   StreamThread (Stream stream)
                   
                   StreamThread ()
                   
                   ~StreamThread ()
                   
                  void thread_fn ()
                   
                  bool stop
                   
                  Stream stream
                   
                  std::thread thread
                   

                  Constructor & Destructor Documentation

                  - -

                  ◆ StreamThread()

                  + +

                  ◆ StreamThread()

                  @@ -152,7 +150,7 @@ Public Attributes mlx::core::scheduler::StreamThread::StreamThread ( - Stream stream) + ) @@ -298,20 +296,6 @@ template<typename F>
                  -
                  -
                  - -

                  ◆ stream

                  - -
                  -
                  - - - - -
                  Stream mlx::core::scheduler::StreamThread::stream
                  -
                  -
                  diff --git a/docs/build/html/structmlx_1_1core_1_1scheduler_1_1_stream_thread.js b/docs/build/html/structmlx_1_1core_1_1scheduler_1_1_stream_thread.js index 5bbad5a92..d60417558 100644 --- a/docs/build/html/structmlx_1_1core_1_1scheduler_1_1_stream_thread.js +++ b/docs/build/html/structmlx_1_1core_1_1scheduler_1_1_stream_thread.js @@ -1,6 +1,6 @@ var structmlx_1_1core_1_1scheduler_1_1_stream_thread = [ - [ "StreamThread", "structmlx_1_1core_1_1scheduler_1_1_stream_thread.html#ac528109a11abcb82e6e221c5efa4493c", null ], + [ "StreamThread", "structmlx_1_1core_1_1scheduler_1_1_stream_thread.html#a18486415163f4d531bedb3b923d724cf", null ], [ "~StreamThread", "structmlx_1_1core_1_1scheduler_1_1_stream_thread.html#a71de50591388b6e2cc6c57827e1a1ad4", null ], [ "enqueue", "structmlx_1_1core_1_1scheduler_1_1_stream_thread.html#a4918720319cf224a1b4208568964c286", null ], [ "thread_fn", "structmlx_1_1core_1_1scheduler_1_1_stream_thread.html#a06a62c21c1174e4eb4d242e50aad7adf", null ], @@ -8,6 +8,5 @@ var structmlx_1_1core_1_1scheduler_1_1_stream_thread = [ "mtx", "structmlx_1_1core_1_1scheduler_1_1_stream_thread.html#a70410c9e612f871663929f1e8441a976", null ], [ "q", "structmlx_1_1core_1_1scheduler_1_1_stream_thread.html#adf608e22d0c0397217472408aab52631", null ], [ "stop", "structmlx_1_1core_1_1scheduler_1_1_stream_thread.html#a456ad1c0c9e731833a2f8411c4ed51aa", null ], - [ "stream", "structmlx_1_1core_1_1scheduler_1_1_stream_thread.html#a8462e4acffcd385c6248bd7102e6bcb1", null ], [ "thread", "structmlx_1_1core_1_1scheduler_1_1_stream_thread.html#a449de02bf2ac80d8fe2f208fa7eac359", null ] ]; \ No newline at end of file diff --git a/docs/build/html/structmlx_1_1steel_1_1_attn_mask_params-members.html b/docs/build/html/structmlx_1_1steel_1_1_attn_mask_params-members.html new file mode 100644 index 000000000..333c5c04a --- /dev/null +++ b/docs/build/html/structmlx_1_1steel_1_1_attn_mask_params-members.html @@ -0,0 +1,121 @@ + + + + + + + +MLX: Member List + + + + + + + + + + + + + + + + +
                  +
                  + + + + + + + +
                  +
                  MLX +
                  +
                  + +   + + + + +
                  +
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                  + + + + +
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                  mlx::steel::AttnMaskParams Member List
                  +
                  +
                  + +

                  This is the complete list of members for mlx::steel::AttnMaskParams, including all inherited members.

                  + + +
                  M_stridesmlx::steel::AttnMaskParams
                  +
                  + + + + diff --git a/docs/build/html/backend_2metal_2event_8h_source.html b/docs/build/html/structmlx_1_1steel_1_1_attn_mask_params.html similarity index 56% rename from docs/build/html/backend_2metal_2event_8h_source.html rename to docs/build/html/structmlx_1_1steel_1_1_attn_mask_params.html index 7fe5da87d..60c46c5fa 100644 --- a/docs/build/html/backend_2metal_2event_8h_source.html +++ b/docs/build/html/structmlx_1_1steel_1_1_attn_mask_params.html @@ -5,7 +5,7 @@ -MLX: mlx/backend/metal/event.h Source File +MLX: mlx::steel::AttnMaskParams Struct Reference @@ -76,7 +76,7 @@ $(function() { codefold.init(0); });
                  @@ -102,29 +102,47 @@ $(function(){initNavTree('backend_2metal_2event_8h_source.html',''); initResizab
                  -
                  event.h
                  +
                  +Public Attributes | +List of all members
                  +
                  mlx::steel::AttnMaskParams Struct Reference
                  -Go to the documentation of this file.
                  1// Copyright © 2024 Apple Inc.
                  -
                  2#pragma once
                  -
                  3
                  -
                  4namespace mlx::core {
                  -
                  5
                  -
                  6void encode_wait(Event e);
                  -
                  7
                  -
                  8void encode_signal(Event e);
                  -
                  9
                  -
                  10} // namespace mlx::core
                  -
                  mlx::core::Event
                  Definition event.h:11
                  -
                  mlx::core
                  Definition allocator.h:7
                  -
                  mlx::core::encode_wait
                  void encode_wait(Event e)
                  -
                  mlx::core::encode_signal
                  void encode_signal(Event e)
                  -
                  + +

                  #include <params.h>

                  + + + + + +

                  +Public Attributes

                  int64_t M_strides [3]
                   Mask strides (B, H, qL, kL = 1)
                   
                  +

                  Member Data Documentation

                  + +

                  ◆ M_strides

                  + +
                  +
                  + + + + +
                  int64_t mlx::steel::AttnMaskParams::M_strides[3]
                  +
                  + +

                  Mask strides (B, H, qL, kL = 1)

                  + +
                  +
                  +
                  The documentation for this struct was generated from the following file:
                    +
                  • mlx/backend/metal/kernels/steel/attn/params.h
                    • +
                  +
                  diff --git a/docs/build/html/structmlx_1_1steel_1_1_attn_mask_params.js b/docs/build/html/structmlx_1_1steel_1_1_attn_mask_params.js new file mode 100644 index 000000000..6ccb70450 --- /dev/null +++ b/docs/build/html/structmlx_1_1steel_1_1_attn_mask_params.js @@ -0,0 +1,4 @@ +var structmlx_1_1steel_1_1_attn_mask_params = +[ + [ "M_strides", "structmlx_1_1steel_1_1_attn_mask_params.html#aaf6c5822d2cb2dcf0992798dc08e27d6", null ] +]; \ No newline at end of file diff --git a/docs/build/html/structmlx_1_1steel_1_1_attn_params-members.html b/docs/build/html/structmlx_1_1steel_1_1_attn_params-members.html index 016e098c5..881349bd6 100644 --- a/docs/build/html/structmlx_1_1steel_1_1_attn_params-members.html +++ b/docs/build/html/structmlx_1_1steel_1_1_attn_params-members.html @@ -114,15 +114,18 @@ $(function(){initNavTree('structmlx_1_1steel_1_1_attn_params.html',''); initResi Hmlx::steel::AttnParams K_stridesmlx::steel::AttnParams kLmlx::steel::AttnParams - NKmlx::steel::AttnParams - NK_alignedmlx::steel::AttnParams - NQmlx::steel::AttnParams - NQ_alignedmlx::steel::AttnParams - O_stridesmlx::steel::AttnParams - Q_stridesmlx::steel::AttnParams - qLmlx::steel::AttnParams - scalemlx::steel::AttnParams - V_stridesmlx::steel::AttnParams + kL_remmlx::steel::AttnParams + NKmlx::steel::AttnParams + NK_alignedmlx::steel::AttnParams + NQmlx::steel::AttnParams + NQ_alignedmlx::steel::AttnParams + O_stridesmlx::steel::AttnParams + Q_stridesmlx::steel::AttnParams + qLmlx::steel::AttnParams + qL_offmlx::steel::AttnParams + qL_remmlx::steel::AttnParams + scalemlx::steel::AttnParams + V_stridesmlx::steel::AttnParams
                  diff --git a/docs/build/html/structmlx_1_1steel_1_1_attn_params.html b/docs/build/html/structmlx_1_1steel_1_1_attn_params.html index a3e659fc9..c3509e164 100644 --- a/docs/build/html/structmlx_1_1steel_1_1_attn_params.html +++ b/docs/build/html/structmlx_1_1steel_1_1_attn_params.html @@ -146,6 +146,15 @@ Public Attributes int NK_aligned  Number of full key/value blocks.
                    +int qL_rem + Remainder in last query block.
                  +  +int kL_rem + Remainder in last key/value block.
                  +  +int qL_off + Offset in query sequence start.
                  +  int64_t Q_strides [3]  Query strides (B, H, L, D = 1)
                    @@ -254,6 +263,22 @@ Public Attributes

                  Key Sequence Length.

                  +
                  +
                  + +

                  ◆ kL_rem

                  + +
                  +
                  + + + + +
                  int mlx::steel::AttnParams::kL_rem
                  +
                  + +

                  Remainder in last key/value block.

                  +
                  @@ -366,6 +391,38 @@ Public Attributes

                  Query Sequence Length.

                  +
                  +
                  + +

                  ◆ qL_off

                  + +
                  +
                  + + + + +
                  int mlx::steel::AttnParams::qL_off
                  +
                  + +

                  Offset in query sequence start.

                  + +
                  +
                  + +

                  ◆ qL_rem

                  + +
                  +
                  + + + + +
                  int mlx::steel::AttnParams::qL_rem
                  +
                  + +

                  Remainder in last query block.

                  +
                  diff --git a/docs/build/html/structmlx_1_1steel_1_1_attn_params.js b/docs/build/html/structmlx_1_1steel_1_1_attn_params.js index 1092c71d0..76c6e0322 100644 --- a/docs/build/html/structmlx_1_1steel_1_1_attn_params.js +++ b/docs/build/html/structmlx_1_1steel_1_1_attn_params.js @@ -6,6 +6,7 @@ var structmlx_1_1steel_1_1_attn_params = [ "H", "structmlx_1_1steel_1_1_attn_params.html#a3d286a0c27bace6016ed7a87f43291b7", null ], [ "K_strides", "structmlx_1_1steel_1_1_attn_params.html#af71b762aa702a3ee592d2098a14b74a9", null ], [ "kL", "structmlx_1_1steel_1_1_attn_params.html#a497b7404bcd25b535c3589c61f269f63", null ], + [ "kL_rem", "structmlx_1_1steel_1_1_attn_params.html#a752033afdf873d2c506aa83b02e38139", null ], [ "NK", "structmlx_1_1steel_1_1_attn_params.html#a68a66e3fafa922dcfd1ab1f6bdc2375e", null ], [ "NK_aligned", "structmlx_1_1steel_1_1_attn_params.html#aaf953954274794cfcb4e35e82d681b58", null ], [ "NQ", "structmlx_1_1steel_1_1_attn_params.html#a48575afc94ab9ff74deaba61464e57a1", null ], @@ -13,6 +14,8 @@ var structmlx_1_1steel_1_1_attn_params = [ "O_strides", "structmlx_1_1steel_1_1_attn_params.html#ab210f29dcc3a732aba34894cd5a42cf7", null ], [ "Q_strides", "structmlx_1_1steel_1_1_attn_params.html#a9150df3fb79de521bbccf57c43f6b092", null ], [ "qL", "structmlx_1_1steel_1_1_attn_params.html#a59255882cbd78bb6f15e704e3a356a7f", null ], + [ "qL_off", "structmlx_1_1steel_1_1_attn_params.html#a2d18657f764a8b4097bc5a05238b5dde", null ], + [ "qL_rem", "structmlx_1_1steel_1_1_attn_params.html#af3fcd78329de006a9a44db64ba469345", null ], [ "scale", "structmlx_1_1steel_1_1_attn_params.html#ad81bcd32e6ff8fec0000eca505fb6826", null ], [ "V_strides", "structmlx_1_1steel_1_1_attn_params.html#ad1495980297901b8ded1fb6dd73979b1", null ] ]; \ No newline at end of file diff --git a/docs/build/html/transforms_8h_source.html b/docs/build/html/transforms_8h_source.html index b668571e9..634505ba3 100644 --- a/docs/build/html/transforms_8h_source.html +++ b/docs/build/html/transforms_8h_source.html @@ -284,7 +284,7 @@ $(function(){initNavTree('transforms_8h_source.html',''); initResizable(true); }
                  mlx::core::ValueAndGradFn
                  std::function< std::pair< std::vector< array >, std::vector< array > >( const std::vector< array > &)> ValueAndGradFn
                  Definition transforms.h:68
                  mlx::core::value_and_grad
                  ValueAndGradFn value_and_grad(const std::function< std::vector< array >(const std::vector< array > &)> &fun, const std::vector< int > &argnums)
                  Returns a function which computes the value and gradient of the input function with respect to a vect...
                  mlx::core::vmap
                  std::function< array(const array &)> vmap(const std::function< array(const array &)> &fun, int in_axis=0, int out_axis=0)
                  Automatically vectorize a unary function over the requested axes.
                  -
                  mlx::core::enable_for_arrays_t
                  typename std::enable_if_t< is_arrays_v< T... > > enable_for_arrays_t
                  Definition array.h:630
                  +
                  mlx::core::enable_for_arrays_t
                  typename std::enable_if_t< is_arrays_v< T... > > enable_for_arrays_t
                  Definition array.h:615
                  diff --git a/docs/build/html/usage/compile.html b/docs/build/html/usage/compile.html index dfff6bba9..45613f5de 100644 --- a/docs/build/html/usage/compile.html +++ b/docs/build/html/usage/compile.html @@ -8,7 +8,7 @@ - Compilation — MLX 0.23.2 documentation + Compilation — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/usage/distributed.html b/docs/build/html/usage/distributed.html index 0d3e250bb..39575e5c3 100644 --- a/docs/build/html/usage/distributed.html +++ b/docs/build/html/usage/distributed.html @@ -8,7 +8,7 @@ - Distributed Communication — MLX 0.23.2 documentation + Distributed Communication — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home +
                  diff --git a/docs/build/html/usage/export.html b/docs/build/html/usage/export.html index 460bef38e..4b8dc1557 100644 --- a/docs/build/html/usage/export.html +++ b/docs/build/html/usage/export.html @@ -8,7 +8,7 @@ - Exporting Functions — MLX 0.23.2 documentation + Exporting Functions — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/usage/function_transforms.html b/docs/build/html/usage/function_transforms.html index 41f0f80fa..326f82d71 100644 --- a/docs/build/html/usage/function_transforms.html +++ b/docs/build/html/usage/function_transforms.html @@ -8,7 +8,7 @@ - Function Transforms — MLX 0.23.2 documentation + Function Transforms — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/usage/indexing.html b/docs/build/html/usage/indexing.html index 6706727c0..31d95cf77 100644 --- a/docs/build/html/usage/indexing.html +++ b/docs/build/html/usage/indexing.html @@ -8,7 +8,7 @@ - Indexing Arrays — MLX 0.23.2 documentation + Indexing Arrays — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/usage/launching_distributed.html b/docs/build/html/usage/launching_distributed.html index 63e28fd49..92e3ecb78 100644 --- a/docs/build/html/usage/launching_distributed.html +++ b/docs/build/html/usage/launching_distributed.html @@ -8,7 +8,7 @@ - Launching Distributed Programs — MLX 0.23.2 documentation + Launching Distributed Programs — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/usage/lazy_evaluation.html b/docs/build/html/usage/lazy_evaluation.html index c3475e254..6aafec562 100644 --- a/docs/build/html/usage/lazy_evaluation.html +++ b/docs/build/html/usage/lazy_evaluation.html @@ -8,7 +8,7 @@ - Lazy Evaluation — MLX 0.23.2 documentation + Lazy Evaluation — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/usage/numpy.html b/docs/build/html/usage/numpy.html index 45decb81c..5da0163fd 100644 --- a/docs/build/html/usage/numpy.html +++ b/docs/build/html/usage/numpy.html @@ -8,7 +8,7 @@ - Conversion to NumPy and Other Frameworks — MLX 0.23.2 documentation + Conversion to NumPy and Other Frameworks — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/usage/quick_start.html b/docs/build/html/usage/quick_start.html index 27a8f83b7..a8b7f194b 100644 --- a/docs/build/html/usage/quick_start.html +++ b/docs/build/html/usage/quick_start.html @@ -8,7 +8,7 @@ - Quick Start Guide — MLX 0.23.2 documentation + Quick Start Guide — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/usage/saving_and_loading.html b/docs/build/html/usage/saving_and_loading.html index 82de56c25..434f68b9b 100644 --- a/docs/build/html/usage/saving_and_loading.html +++ b/docs/build/html/usage/saving_and_loading.html @@ -8,7 +8,7 @@ - Saving and Loading Arrays — MLX 0.23.2 documentation + Saving and Loading Arrays — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/usage/unified_memory.html b/docs/build/html/usage/unified_memory.html index 1cd5d8c6a..ad4abb9ed 100644 --- a/docs/build/html/usage/unified_memory.html +++ b/docs/build/html/usage/unified_memory.html @@ -8,7 +8,7 @@ - Unified Memory — MLX 0.23.2 documentation + Unified Memory — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/usage/using_streams.html b/docs/build/html/usage/using_streams.html index 6bbd0e5fc..47b5e5595 100644 --- a/docs/build/html/usage/using_streams.html +++ b/docs/build/html/usage/using_streams.html @@ -8,7 +8,7 @@ - Using Streams — MLX 0.23.2 documentation + Using Streams — MLX 0.24.0 documentation @@ -36,7 +36,7 @@ - + @@ -137,8 +137,8 @@ - MLX 0.23.2 documentation - Home - + MLX 0.24.0 documentation - Home + diff --git a/docs/build/html/utils_8h.html b/docs/build/html/utils_8h.html index 6aeeb5c9e..f3ce05b51 100644 --- a/docs/build/html/utils_8h.html +++ b/docs/build/html/utils_8h.html @@ -147,6 +147,8 @@ Typedefs Functions Stream mlx::core::to_stream (StreamOrDevice s)   +Stream mlx::core::to_stream (StreamOrDevice s, Device default_) +  PrintFormatter & mlx::core::get_global_formatter ()   void mlx::core::abort_with_exception (const std::exception &error) diff --git a/docs/build/html/utils_8h.js b/docs/build/html/utils_8h.js index 8f2255b0b..f33c73477 100644 --- a/docs/build/html/utils_8h.js +++ b/docs/build/html/utils_8h.js @@ -28,5 +28,6 @@ var utils_8h = [ "mlx::core::result_type", "namespacemlx_1_1core.html#a8b984eef832f757e28cd262d64a49ae7", null ], [ "mlx::core::result_type", "namespacemlx_1_1core.html#ac457c232f956ba802acb69c5a621633d", null ], [ "mlx::core::result_type", "namespacemlx_1_1core.html#aafaf24a28297428caf6d0c36c623489e", null ], - [ "mlx::core::to_stream", "namespacemlx_1_1core.html#a4734a596e57434492ddfe79f2cb9dbf9", null ] + [ "mlx::core::to_stream", "namespacemlx_1_1core.html#a4734a596e57434492ddfe79f2cb9dbf9", null ], + [ "mlx::core::to_stream", "namespacemlx_1_1core.html#a999be930e8a5b35eb33d934eefd548e8", null ] ]; \ No newline at end of file diff --git a/docs/build/html/utils_8h_source.html b/docs/build/html/utils_8h_source.html index cfb2f2257..16acbbbf4 100644 --- a/docs/build/html/utils_8h_source.html +++ b/docs/build/html/utils_8h_source.html @@ -121,187 +121,188 @@ $(function(){initNavTree('utils_8h_source.html',''); initResizable(true); });
                  14
                  15using StreamOrDevice = std::variant<std::monostate, Stream, Device>;
                  16Stream to_stream(StreamOrDevice s);
                  -
                  17
                  -
                  -
                  18struct StreamContext {
                  -
                  19 public:
                  -
                  -
                  20 StreamContext(StreamOrDevice s) : _stream(default_stream(default_device())) {
                  -
                  21 if (std::holds_alternative<std::monostate>(s)) {
                  -
                  22 throw std::runtime_error(
                  -
                  23 "[StreamContext] Invalid argument, please specify a stream or device.");
                  -
                  24 }
                  -
                  25 auto _s = to_stream(s);
                  -
                  26 set_default_device(_s.device);
                  -
                  27 set_default_stream(_s);
                  -
                  28 }
                  +
                  17Stream to_stream(StreamOrDevice s, Device default_);
                  +
                  18
                  +
                  +
                  19struct StreamContext {
                  +
                  20 public:
                  +
                  +
                  21 StreamContext(StreamOrDevice s) : _stream(default_stream(default_device())) {
                  +
                  22 if (std::holds_alternative<std::monostate>(s)) {
                  +
                  23 throw std::runtime_error(
                  +
                  24 "[StreamContext] Invalid argument, please specify a stream or device.");
                  +
                  25 }
                  +
                  26 auto _s = to_stream(s);
                  +
                  27 set_default_device(_s.device);
                  +
                  28 set_default_stream(_s);
                  +
                  29 }
                  -
                  29
                  -
                  -
                  30 ~StreamContext() {
                  -
                  31 set_default_device(_stream.device);
                  -
                  32 set_default_stream(_stream);
                  -
                  33 }
                  +
                  30
                  +
                  +
                  31 ~StreamContext() {
                  +
                  32 set_default_device(_stream.device);
                  +
                  33 set_default_stream(_stream);
                  +
                  34 }
                  -
                  34
                  -
                  35 private:
                  -
                  36 Stream _stream;
                  -
                  37};
                  +
                  35
                  +
                  36 private:
                  +
                  37 Stream _stream;
                  +
                  38};
                  -
                  38
                  -
                  -
                  39struct PrintFormatter {
                  -
                  40 inline void print(std::ostream& os, bool val);
                  -
                  41 inline void print(std::ostream& os, int16_t val);
                  -
                  42 inline void print(std::ostream& os, uint16_t val);
                  -
                  43 inline void print(std::ostream& os, int32_t val);
                  -
                  44 inline void print(std::ostream& os, uint32_t val);
                  -
                  45 inline void print(std::ostream& os, int64_t val);
                  -
                  46 inline void print(std::ostream& os, uint64_t val);
                  -
                  47 inline void print(std::ostream& os, float16_t val);
                  -
                  48 inline void print(std::ostream& os, bfloat16_t val);
                  -
                  49 inline void print(std::ostream& os, float val);
                  -
                  50 inline void print(std::ostream& os, double val);
                  -
                  51 inline void print(std::ostream& os, complex64_t val);
                  -
                  52
                  -
                  53 bool capitalize_bool{false};
                  -
                  54};
                  +
                  39
                  +
                  +
                  40struct PrintFormatter {
                  +
                  41 inline void print(std::ostream& os, bool val);
                  +
                  42 inline void print(std::ostream& os, int16_t val);
                  +
                  43 inline void print(std::ostream& os, uint16_t val);
                  +
                  44 inline void print(std::ostream& os, int32_t val);
                  +
                  45 inline void print(std::ostream& os, uint32_t val);
                  +
                  46 inline void print(std::ostream& os, int64_t val);
                  +
                  47 inline void print(std::ostream& os, uint64_t val);
                  +
                  48 inline void print(std::ostream& os, float16_t val);
                  +
                  49 inline void print(std::ostream& os, bfloat16_t val);
                  +
                  50 inline void print(std::ostream& os, float val);
                  +
                  51 inline void print(std::ostream& os, double val);
                  +
                  52 inline void print(std::ostream& os, complex64_t val);
                  +
                  53
                  +
                  54 bool capitalize_bool{false};
                  +
                  55};
                  -
                  55
                  -
                  56PrintFormatter& get_global_formatter();
                  -
                  57
                  -
                  59void abort_with_exception(const std::exception& error);
                  -
                  60
                  -
                  -
                  62struct finfo {
                  -
                  63 explicit finfo(Dtype dtype);
                  -
                  64 Dtype dtype;
                  -
                  65 double min;
                  -
                  66 double max;
                  -
                  67};
                  +
                  56
                  +
                  57PrintFormatter& get_global_formatter();
                  +
                  58
                  +
                  60void abort_with_exception(const std::exception& error);
                  +
                  61
                  +
                  +
                  63struct finfo {
                  +
                  64 explicit finfo(Dtype dtype);
                  +
                  65 Dtype dtype;
                  +
                  66 double min;
                  +
                  67 double max;
                  +
                  68};
                  -
                  68
                  -
                  -
                  70inline Dtype result_type(const array& a, const array& b) {
                  -
                  71 return promote_types(a.dtype(), b.dtype());
                  -
                  72}
                  +
                  69
                  +
                  +
                  71inline Dtype result_type(const array& a, const array& b) {
                  +
                  72 return promote_types(a.dtype(), b.dtype());
                  +
                  73}
                  -
                  -
                  73inline Dtype result_type(const array& a, const array& b, const array& c) {
                  -
                  74 return promote_types(result_type(a, b), c.dtype());
                  -
                  75}
                  +
                  +
                  74inline Dtype result_type(const array& a, const array& b, const array& c) {
                  +
                  75 return promote_types(result_type(a, b), c.dtype());
                  +
                  76}
                  -
                  76Dtype result_type(const std::vector<array>& arrays);
                  -
                  77
                  -
                  78Shape broadcast_shapes(const Shape& s1, const Shape& s2);
                  -
                  79
                  -
                  83int normalize_axis_index(
                  -
                  84 int axis,
                  -
                  85 int ndim,
                  -
                  86 const std::string& msg_prefix = "");
                  -
                  87
                  -
                  88std::ostream& operator<<(std::ostream& os, const Device& d);
                  -
                  89std::ostream& operator<<(std::ostream& os, const Stream& s);
                  -
                  90std::ostream& operator<<(std::ostream& os, const Dtype& d);
                  -
                  91std::ostream& operator<<(std::ostream& os, const Dtype::Kind& k);
                  -
                  92std::ostream& operator<<(std::ostream& os, array a);
                  -
                  93std::ostream& operator<<(std::ostream& os, const std::vector<int>& v);
                  -
                  94std::ostream& operator<<(std::ostream& os, const std::vector<int64_t>& v);
                  -
                  -
                  95inline std::ostream& operator<<(std::ostream& os, const complex64_t& v) {
                  -
                  96 return os << v.real() << (v.imag() >= 0 ? "+" : "") << v.imag() << "j";
                  -
                  97}
                  +
                  77Dtype result_type(const std::vector<array>& arrays);
                  +
                  78
                  +
                  79Shape broadcast_shapes(const Shape& s1, const Shape& s2);
                  +
                  80
                  +
                  84int normalize_axis_index(
                  +
                  85 int axis,
                  +
                  86 int ndim,
                  +
                  87 const std::string& msg_prefix = "");
                  +
                  88
                  +
                  89std::ostream& operator<<(std::ostream& os, const Device& d);
                  +
                  90std::ostream& operator<<(std::ostream& os, const Stream& s);
                  +
                  91std::ostream& operator<<(std::ostream& os, const Dtype& d);
                  +
                  92std::ostream& operator<<(std::ostream& os, const Dtype::Kind& k);
                  +
                  93std::ostream& operator<<(std::ostream& os, array a);
                  +
                  94std::ostream& operator<<(std::ostream& os, const std::vector<int>& v);
                  +
                  95std::ostream& operator<<(std::ostream& os, const std::vector<int64_t>& v);
                  +
                  +
                  96inline std::ostream& operator<<(std::ostream& os, const complex64_t& v) {
                  +
                  97 return os << v.real() << (v.imag() >= 0 ? "+" : "") << v.imag() << "j";
                  +
                  98}
                  -
                  -
                  98inline std::ostream& operator<<(std::ostream& os, const float16_t& v) {
                  -
                  99 return os << static_cast<float>(v);
                  -
                  100}
                  +
                  +
                  99inline std::ostream& operator<<(std::ostream& os, const float16_t& v) {
                  +
                  100 return os << static_cast<float>(v);
                  +
                  101}
                  -
                  -
                  101inline std::ostream& operator<<(std::ostream& os, const bfloat16_t& v) {
                  -
                  102 return os << static_cast<float>(v);
                  -
                  103}
                  +
                  +
                  102inline std::ostream& operator<<(std::ostream& os, const bfloat16_t& v) {
                  +
                  103 return os << static_cast<float>(v);
                  +
                  104}
                  -
                  104
                  -
                  -
                  105inline bool is_power_of_2(int n) {
                  -
                  106 return ((n & (n - 1)) == 0) && n != 0;
                  -
                  107}
                  +
                  105
                  +
                  +
                  106inline bool is_power_of_2(int n) {
                  +
                  107 return ((n & (n - 1)) == 0) && n != 0;
                  +
                  108}
                  -
                  108
                  -
                  -
                  109inline int next_power_of_2(int n) {
                  -
                  110 if (is_power_of_2(n)) {
                  -
                  111 return n;
                  -
                  112 }
                  -
                  113 return pow(2, std::ceil(std::log2(n)));
                  -
                  114}
                  +
                  109
                  +
                  +
                  110inline int next_power_of_2(int n) {
                  +
                  111 if (is_power_of_2(n)) {
                  +
                  112 return n;
                  +
                  113 }
                  +
                  114 return pow(2, std::ceil(std::log2(n)));
                  +
                  115}
                  -
                  115
                  -
                  -
                  116namespace env {
                  -
                  117
                  -
                  118int get_var(const char* name, int default_value);
                  -
                  119
                  -
                  -
                  120inline int bfs_max_width() {
                  -
                  121 static int bfs_max_width_ = get_var("MLX_BFS_MAX_WIDTH", 20);
                  -
                  122 return bfs_max_width_;
                  -
                  123}
                  +
                  116
                  +
                  +
                  117namespace env {
                  +
                  118
                  +
                  119int get_var(const char* name, int default_value);
                  +
                  120
                  +
                  +
                  121inline int bfs_max_width() {
                  +
                  122 static int bfs_max_width_ = get_var("MLX_BFS_MAX_WIDTH", 20);
                  +
                  123 return bfs_max_width_;
                  +
                  124}
                  -
                  124
                  -
                  -
                  125inline int max_ops_per_buffer(int default_value) {
                  -
                  126 static int max_ops_per_buffer_ =
                  -
                  127 get_var("MLX_MAX_OPS_PER_BUFFER", default_value);
                  -
                  128 return max_ops_per_buffer_;
                  -
                  129}
                  +
                  125
                  +
                  +
                  126inline int max_ops_per_buffer(int default_value) {
                  +
                  127 static int max_ops_per_buffer_ =
                  +
                  128 get_var("MLX_MAX_OPS_PER_BUFFER", default_value);
                  +
                  129 return max_ops_per_buffer_;
                  +
                  130}
                  -
                  130
                  -
                  -
                  131inline int max_mb_per_buffer(int default_value) {
                  -
                  132 static int max_mb_per_buffer_ =
                  -
                  133 get_var("MLX_MAX_MB_PER_BUFFER", default_value);
                  -
                  134 return max_mb_per_buffer_;
                  -
                  135}
                  +
                  131
                  +
                  +
                  132inline int max_mb_per_buffer(int default_value) {
                  +
                  133 static int max_mb_per_buffer_ =
                  +
                  134 get_var("MLX_MAX_MB_PER_BUFFER", default_value);
                  +
                  135 return max_mb_per_buffer_;
                  +
                  136}
                  -
                  136
                  -
                  -
                  137inline bool metal_fast_synch() {
                  -
                  138 static bool metal_fast_synch = get_var("MLX_METAL_FAST_SYNCH", 0);
                  -
                  139 return metal_fast_synch;
                  -
                  140}
                  +
                  137
                  +
                  +
                  138inline bool metal_fast_synch() {
                  +
                  139 static bool metal_fast_synch = get_var("MLX_METAL_FAST_SYNCH", 0);
                  +
                  140 return metal_fast_synch;
                  +
                  141}
                  -
                  141
                  -
                  142} // namespace env
                  +
                  142
                  +
                  143} // namespace env
                  -
                  143
                  -
                  144} // namespace mlx::core
                  +
                  144
                  +
                  145} // namespace mlx::core
                  mlx::core::array
                  Definition array.h:24
                  mlx::core::array::dtype
                  Dtype dtype() const
                  Get the arrays data type.
                  Definition array.h:131
                  mlx::core::operator<<
                  array operator<<(const array &a, const array &b)
                  -
                  mlx::core::env
                  Definition utils.h:116
                  +
                  mlx::core::env
                  Definition utils.h:117
                  mlx::core::env::get_var
                  int get_var(const char *name, int default_value)
                  -
                  mlx::core::env::max_ops_per_buffer
                  int max_ops_per_buffer(int default_value)
                  Definition utils.h:125
                  -
                  mlx::core::env::bfs_max_width
                  int bfs_max_width()
                  Definition utils.h:120
                  -
                  mlx::core::env::metal_fast_synch
                  bool metal_fast_synch()
                  Definition utils.h:137
                  -
                  mlx::core::env::max_mb_per_buffer
                  int max_mb_per_buffer(int default_value)
                  Definition utils.h:131
                  +
                  mlx::core::env::max_ops_per_buffer
                  int max_ops_per_buffer(int default_value)
                  Definition utils.h:126
                  +
                  mlx::core::env::bfs_max_width
                  int bfs_max_width()
                  Definition utils.h:121
                  +
                  mlx::core::env::metal_fast_synch
                  bool metal_fast_synch()
                  Definition utils.h:138
                  +
                  mlx::core::env::max_mb_per_buffer
                  int max_mb_per_buffer(int default_value)
                  Definition utils.h:132
                  mlx::core
                  Definition allocator.h:7
                  mlx::core::default_device
                  const Device & default_device()
                  mlx::core::normalize_axis_index
                  int normalize_axis_index(int axis, int ndim, const std::string &msg_prefix="")
                  Returns the axis normalized to be in the range [0, ndim).
                  mlx::core::set_default_device
                  void set_default_device(const Device &d)
                  mlx::core::to_stream
                  Stream to_stream(StreamOrDevice s)
                  mlx::core::promote_types
                  Dtype promote_types(const Dtype &t1, const Dtype &t2)
                  -
                  mlx::core::next_power_of_2
                  int next_power_of_2(int n)
                  Definition utils.h:109
                  +
                  mlx::core::next_power_of_2
                  int next_power_of_2(int n)
                  Definition utils.h:110
                  mlx::core::Shape
                  std::vector< ShapeElem > Shape
                  Definition array.h:21
                  -
                  mlx::core::result_type
                  Dtype result_type(const array &a, const array &b)
                  The type from promoting the arrays' types with one another.
                  Definition utils.h:70
                  +
                  mlx::core::result_type
                  Dtype result_type(const array &a, const array &b)
                  The type from promoting the arrays' types with one another.
                  Definition utils.h:71
                  mlx::core::StreamOrDevice
                  std::variant< std::monostate, Stream, Device > StreamOrDevice
                  Definition utils.h:15
                  mlx::core::default_stream
                  Stream default_stream(Device d)
                  Get the default stream for the given device.
                  mlx::core::bfloat16_t
                  struct _MLX_BFloat16 bfloat16_t
                  Definition half_types.h:34
                  -
                  mlx::core::is_power_of_2
                  bool is_power_of_2(int n)
                  Definition utils.h:105
                  +
                  mlx::core::is_power_of_2
                  bool is_power_of_2(int n)
                  Definition utils.h:106
                  mlx::core::abort_with_exception
                  void abort_with_exception(const std::exception &error)
                  Print the exception and then abort.
                  mlx::core::broadcast_shapes
                  Shape broadcast_shapes(const Shape &s1, const Shape &s2)
                  mlx::core::set_default_stream
                  void set_default_stream(Stream s)
                  Make the stream the default for its device.
                  @@ -311,7 +312,7 @@ $(function(){initNavTree('utils_8h_source.html',''); initResizable(true); });
                  mlx::core::Device
                  Definition device.h:7
                  mlx::core::Dtype
                  Definition dtype.h:13
                  mlx::core::Dtype::Kind
                  Kind
                  Definition dtype.h:31
                  -
                  mlx::core::PrintFormatter
                  Definition utils.h:39
                  +
                  mlx::core::PrintFormatter
                  Definition utils.h:40
                  mlx::core::PrintFormatter::print
                  void print(std::ostream &os, uint32_t val)
                  mlx::core::PrintFormatter::print
                  void print(std::ostream &os, float val)
                  mlx::core::PrintFormatter::print
                  void print(std::ostream &os, bool val)
                  @@ -323,16 +324,16 @@ $(function(){initNavTree('utils_8h_source.html',''); initResizable(true); });
                  mlx::core::PrintFormatter::print
                  void print(std::ostream &os, float16_t val)
                  mlx::core::PrintFormatter::print
                  void print(std::ostream &os, uint64_t val)
                  mlx::core::PrintFormatter::print
                  void print(std::ostream &os, int32_t val)
                  -
                  mlx::core::PrintFormatter::capitalize_bool
                  bool capitalize_bool
                  Definition utils.h:53
                  +
                  mlx::core::PrintFormatter::capitalize_bool
                  bool capitalize_bool
                  Definition utils.h:54
                  mlx::core::PrintFormatter::print
                  void print(std::ostream &os, bfloat16_t val)
                  -
                  mlx::core::StreamContext::StreamContext
                  StreamContext(StreamOrDevice s)
                  Definition utils.h:20
                  -
                  mlx::core::StreamContext::~StreamContext
                  ~StreamContext()
                  Definition utils.h:30
                  +
                  mlx::core::StreamContext::StreamContext
                  StreamContext(StreamOrDevice s)
                  Definition utils.h:21
                  +
                  mlx::core::StreamContext::~StreamContext
                  ~StreamContext()
                  Definition utils.h:31
                  mlx::core::Stream
                  Definition stream.h:9
                  mlx::core::complex64_t
                  Definition complex.h:35
                  mlx::core::finfo::finfo
                  finfo(Dtype dtype)
                  -
                  mlx::core::finfo::min
                  double min
                  Definition utils.h:65
                  -
                  mlx::core::finfo::dtype
                  Dtype dtype
                  Definition utils.h:64
                  -
                  mlx::core::finfo::max
                  double max
                  Definition utils.h:66
                  +
                  mlx::core::finfo::min
                  double min
                  Definition utils.h:66
                  +
                  mlx::core::finfo::dtype
                  Dtype dtype
                  Definition utils.h:65
                  +
                  mlx::core::finfo::max
                  double max
                  Definition utils.h:67
                  diff --git a/docs/build/html/version_8h.html b/docs/build/html/version_8h.html index ec31e3ffc..c5a609e5c 100644 --- a/docs/build/html/version_8h.html +++ b/docs/build/html/version_8h.html @@ -123,9 +123,9 @@ Namespaces Macros #define MLX_VERSION_MAJOR   0   -#define MLX_VERSION_MINOR   23 +#define MLX_VERSION_MINOR   24   -#define MLX_VERSION_PATCH   2 +#define MLX_VERSION_PATCH   0   #define MLX_VERSION_NUMERIC    (100000 * MLX_VERSION_MAJOR + 1000 * MLX_VERSION_MINOR + MLX_VERSION_PATCH)   @@ -157,7 +157,7 @@ Functions
                  - +
                  #define MLX_VERSION_MINOR   23#define MLX_VERSION_MINOR   24
                  @@ -185,7 +185,7 @@ Functions
                  - +
                  #define MLX_VERSION_PATCH   2#define MLX_VERSION_PATCH   0
                  diff --git a/docs/build/html/version_8h_source.html b/docs/build/html/version_8h_source.html index f47967947..d08682a01 100644 --- a/docs/build/html/version_8h_source.html +++ b/docs/build/html/version_8h_source.html @@ -110,8 +110,8 @@ $(function(){initNavTree('version_8h_source.html',''); initResizable(true); });
                  3#pragma once
                  4
                  5#define MLX_VERSION_MAJOR 0
                  -
                  6#define MLX_VERSION_MINOR 23
                  -
                  7#define MLX_VERSION_PATCH 2
                  +
                  6#define MLX_VERSION_MINOR 24
                  +
                  7#define MLX_VERSION_PATCH 0
                  8#define MLX_VERSION_NUMERIC \
                  9 (100000 * MLX_VERSION_MAJOR + 1000 * MLX_VERSION_MINOR + MLX_VERSION_PATCH)