* add implicit conversion of list to array for equality constraint
* add tests for array equality
* add test for tuple and array equality
* return False if __eq__ arg is list or tuple
* write tests for equality
* update the rule of comparison for __ge__/__gt__/__lt__/__le__
* add a helper function for detecting mlx.core.array
* return true in case fo inequality
* debug minor issue regarding detecting mlx array
* add tests for inequality comparisons
* add name for contribution
* reformat files using pre-commit
* update tests for float
* update tests for inequality
* raise exception in case of invalid comparisons
* use isinstance instead of string comparison
* replace "is_convirtable_to_array" with previous logic
* remove throwing exceptions for other operations
* just a comment
* minor changes for efficiency
* optimize a utils function
* change the function name
* Update ACKNOWLEDGMENTS.md
---------
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
The arm64 macbook pros are heavy and I usually care my intel one for
mobile, it would be nice if I can play with MLX on it.
To build with x64, user must pass `MLX_ENABLE_X64_MAC` to cmake:
CMAKE_ARGS='-DMLX_ENABLE_X64_MAC=ON' python setup.py
* 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>
* mostly builds
* most tests pass
* fix circle build
* add back buffer protocol
* includes
* fix for py38
* limit to cpu device
* include
* fix stubs
* move signatures for docs
* stubgen + docs fix
* doc for compiled function, comments
* 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>
* refactor tree utils
* fix compile + tree code refactor
* Add an extra test
* add a few missing activations to docs
* hash structure
* Encode the full argument structure
---------
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
