* Skip using Residency sets in VMs
Attempting to use residency sets in a VM throws[^1]
libc++abi: terminating due to uncaught exception of type std::runtime_error: [metal::Device] Unable to construct residency set.
Not quite sure if this is the best fix, but it does make the error go
away.
Note that it was previously possible to run simple programs that used
mlx in a VM prior to 0eb56d5be0. See
related discussion at Homebrew/homebrew-core#195627.
[^1]: https://github.com/Homebrew/homebrew-core/actions/runs/11525831492/job/32105148462#step:3:56
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
* change residency check
---------
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
Co-authored-by: Awni Hannun <awni@apple.com>
* initial eigvalsh
* add compute_vectors
* add compute_vectors_
* return a pair
* add eigh to return only eigenvectors
* fixed typo
* merge merge Eighvalsh and Eigh into a single primitive
* use the same primate with the flag
* fix primatives
* use MULTI
* fix eval_gpu
* fix decleration
* rename EighPrimitive to Eigh
* tests
* tests
* fix rebase and format
* cleanup lapack
* format
* add cblas.h
---------
Co-authored-by: Awni Hannun <awni@apple.com>
* faster binary and cleaner copy
* use recursive template for other ops
* more cleanup
* fix from cleanup
* more clean
* fix binary
* use contiguous iterator
* add 3d
* nits
* fix
* fix?
* fix
* fix rebase
* compile works for big arrays when contiguous
* style
* nits in docs
* a bunch more stuff
* update jit
* update jit
* use constant for shapes and strides and remove elem_to_loc overload
* use kernel instantiation
* docs nits
* update binary and ternary
* comments
* fix copying scalars by adding fill_gpu
* Another copy scalar changed to fill
---------
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
* Add `zero_outputs` and `atomic_outputs` options to `metal_kernel`
* add grid sample to docs
* zero_outputs -> init_value
* add missing header for linux
* start
* simple kernels working
* restructure
* inverse example working
* docs + fixes
* missing file
* fix imports
* address comments
* add docs + fix test
* Review comments + refactor to a single function
* update docs
* remove hashing
* fix contig bug in test
* back to a class
* trailing whitespace
* fix tests
* match c++ and python apis
* add link + make args kw_only
* add gemv masked to JIT plus some fixes
* some cleanup
* add utils
* fix
* fix 2
* more cleaning
* fix
* remove unused mps matmul support
* one more nit
* revert
* Add fast affine dequantize
* add full quantize kernel
* fused kernel with scale/bias computation
* fix docstring
* fix no jit error
* fix test
* test fix
* reduce fast api to only affine_quantize
* Working hadamard for powers of 2
* working for m*2^k
* add scale and check contiguity
* add size check
* clean up
* fix test
* add grads + vmap
* gpu only
* skip on linux
* test typo
* add cpu impl
* remove gpu only tests
* fix linux build + add is_equivalent
* Update veclib and bnns includes to #include <Accelerate/Accelerate.h> for compatibility with ios
* Mark float literals in softmax.cpp to be float16_t for errors in ios
* Add arm neon vector operation guards
* Redirect to common backend for consistency
* Metal shaders for efficient self attention on large sequences
Updated fast attention: GEMM-ified with Steel primitives
Uses flash attention 1 for scale correction
* more compiler silencing
* Address rebase issues
* Templatize kernel instantiation, revise cpu bindings
* Safer writes to output
* Permit batch size > 1
* Numerical fixes for sdpa self attention
* Re-enable test, remove unused variable
* add benchmarking script
* Disable sdpa prior to perf tuning, and simplify tests for per-patch CI
* Added groups to 2-D convolutions. Only implemented for **some** specializations.
Also fixed 1D grouped convs with different kernel strides and added more tests.
* fix channels condition
* try cpp 20 for compile
* unary, binary, ternary in jit
* nits
* fix gather/scatter
* fix rebase
* reorg compile
* add ternary to compile
* jit copy
* jit compile flag
* fix build
* use linked function for ternary
* some nits
* docs + circle min size build
* docs + circle min size build
* fix extension
* fix no cpu build
* improve includes
* add synchronize function
* fix linux
* fix linux
* fix and fix docs
* fix test
* try synchronize in stream destroy
* synchronize works for both cpu and gpu
* more async eval
* fix rebase
* try correct async eval
* fix async
* more tests for async eval
* use shared events for synchronization
* comment + cleanup
* with autorelease pool
* fix no metal build
* fix compile
* fix patch
* don't eval if asyn evale'd
* don't use is_evaled
* comments
* more multi stream tests
* try and cleanup use of is_evaled
* use a status flag
* std and expm1
* actually add expm1
* fix linux
* fix vjp
* relax tol for linux test
* Add it to the compilable primitives
---------
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
Without the && args would be copied and perfect forwarding won't work.
Also add template utils to make sure the function only forwards array
and not vector<array>.
* add numeric type hierarchy and issubdtype as well as a set_dtype method to nn.Module with predicate
numeric type hierarchy and issubtype is compatible to the [numpy hierarchy](220f0ab2c5/numpy/_core/numerictypes.py (L42)).
Closes#285.
* nits in docs
* unify type category checking
* nits in docs
* nits in docs
* more docs nits
* fix callable type
---------
Co-authored-by: Awni Hannun <awni@apple.com>
* fast rmsnorm
* no rms gpu
* kernel
* fix shared mem
* looped rms and donation in softmax
* Make the squaring in float32 to avoid underflow
* Fix the default StreamOrDevice for rope and rms_norm in fast
* nits
---------
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
* Enable copy to work with int64 strides
* Fix uniform buffer indices or copy kernel arguments
* Update utils.h
* Remove manual unrolling of elem to loc loop
* GPU copy updated to handle negative strides
* Add slice update primitive
1. Anonymous namespace means internal linkage, static keyword is not needed.
2. The default constructor of std::shared_ptr initializes the pointer to
nullptr, you don't need to explicitly set it.
* Enable collapsing batch dims in gemm
* Update gemm to only make copies when neither of the last 2 axes are contiguous
* Update addmm to support gemv shapes
* Update addmm to support irregular batch strides
* Update tests
* Fast Inference SDPA op
Implements metal shaders for:
o = mx.fast_inference_sdpa(queries, keys, values, scale, mask)
Supports fp16, fp32 dtypes; assumes d_k = 128.
Generic op support / prompt encoding supported via mlx primitives.
Metal implementation is for the inference use case only.
Majority of performance benefits appears to results from GQA & reduced
bandwidth requirements; there is approximate performance parity for the
MHA use case (from some measurements on M3 Max).
* Flush shared memory to zero before unprotected reads for (scores @ values)
* Move to fast:: namespace, address reviewer comments
... also attempt to revert formatter auto-change for files not relevant
to this change
* Shared memory flush to top of kernel
* Resolve compiler warnings
* Update python/src/fast.cpp
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
* Update python/src/fast.cpp
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
* Update python/src/fast.cpp
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
* Update python/src/fast.cpp
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
* Update docstring per PR feedback
* Softmax in higher precision, ...
* route to fallback for more use cases - batch size > 1, head_dim other
than 128, etc.
* Address linux build failure
* Address other reviewer comments
* Remove extraneous eval_cpu function per review
---------
Co-authored-by: Atila Orhon <64497909+atiorh@users.noreply.github.com>
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
Co-authored-by: atila <atiorh@icloud.com>
* try to fix build for ios
* skip cpu compile
* fix namespace
* fix namespace
* Use CMake for platform specific cpu compile
---------
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
* Split reduction files to reduce compile times
* Add small and medium axis size specializations for row reductions
* Add non-row-reduction options for small and med kernels
* Faster scatter.
Add specialization for 1-d index tensors.
* Address review comments.
- Check for row contiguity of index, update tensors
instead of checking strides.
- Add support for 1d specialization with col contiguous update
tensor, along with a test.
* Nit1
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
* Nit2
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
---------
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
* shapeless compilation for some graphs
* update compile benchmark
* default compile a few activations
* buffer donation
* bugfix
* shapeless fix
* update tests to work for cpu and gpu fusion
* test kwargs
* add kwargs to compile
* Recompile when python arguments change
* no compile for tanh
* some constant tests
---------
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
* refactor cpu preamble
* fix include order
* fix some issues'
* fixes for linux
* try to fix includes
* add back warning suppression
* more linux fixes
* extensions start
* rope custom op
* fix build
* docs + rope benchmark
* fix test
* Add a Metal kernel for RoPE
* Fix position of traditional
* transform tests
* Move rope computation to float and fix tests
* Fix the test and a typo
* change to fast
* fix no metal build
---------
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
* Replace argument encoder usage for gather and scatter
* Use constant address space for shapes and strides
* Split gather and scatter to improve compile times
* Enable the GPU tests
* Update the CI config
* Fix scatter dispatch for scalar indices
* Remove arg encoder utils
---------
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
Reduce unnecessary integer ops, especially since
there kernels are integer bound.
Increase number of iterations for benchmarks for
better smoothing.
Github Issue #506
Co-authored-by: Vijay Krishnamoorthy <vijay_krish@apple.com>
Launch 2D grid to eliminate divide and mod in device code,
since 64b integer division is very expensive.
Github Issue #506
Co-authored-by: Vijay Krishnamoorthy <vijay_krish@apple.com>
* Implement custom_vjp and checkpointing
* Add a dependency management primitive
* Change the eval order to deep branches first
* Add graph depth tracking to the array
* Add option to specialize metal functions on function constants
* Update Compute Pipeline Creation API
* Add options to make libraries from source and stitching
* Update function specialization name options
* propagate nans in binary ops
* handle empty matmul
* cpu minimum/maximum propagate nan
* benchmark maximum
* add min as well
* throw on negative indices with full
* verbose on linux
* fix matmul for zero K
* buffer donation
* fix to move shared pointer
* format
* gpu in place for copy and binary
* revert ops test
* cpu in place
* a little cleanup
* remove useless bench
* support disable metal buffer cache, due to large unused memory buffered when llm generated long context tokens
* Run format and add "cache_enabled" feature tests
* Organize and collect metal subroutine templates and elements in `metal/kernels/steel/`
* Update gemm elements for better performance
* Add split-K specialization for gemm
* Add `addmm` primitive, op and bindings for fused matmul and bias addition
* Update tests and benchmarks as needed
