* 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>
* Add linear warmup to schedules for use with existing schedules
* Changed parameters for simplicity of most common case (0 initial value)
* Added ScheduleJoiner and updated documentation
* ScheduleJoiner -> join_schedules (ala optax #)
* black compliance
* Different evaluation of schedules
* nits
---------
Co-authored-by: Awni Hannun <awni@apple.com>
* Fix case for step=inf in arange and add inf check for start/stop
* Add test cases for arange
* Update ops.cpp to include climits header
* Fix arange
* Fix formatting
* Refactor
* Add missing include
* 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>
* Add a few LR schedulers
* Move parents's constructor call to the top
* Fix docstring
* refactor optimizers into two files
* add docs
* nit
* Fix Callable type annotation for python 3.8
---------
Co-authored-by: Awni Hannun <awni@apple.com>
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
* 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>
* Simple kernel generation
* Remove the generate kernel from graph_utils
* fix multi-output with compile
* fuse with stopgrad
* v1 input, output capture in compile
* cleanup tree update with visitor update
* nit
* remove todo
* state for model, optional explicit init and more pure optimizer steps
* move learning rate to state
* add lr to opt state, some fixes in capture
* fix optim
* update tuple of containers as well
* fix stream for compiled output
* rng state for compile
* nit
* updates and comments
---------
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
* CI update
* Skip large binary test for now
* Upgrade pip
* Add proper env variable skipping
* Update the CI
* Fix workflow name
* Set the low memory flag for the tests
* Change build process
* Add pip upgrade
* Use a venv
* Add a missing env activate
* Add setuptools
* Add twine upload back
* Re-enable automatic release builds
* Implement diagonal operator
This implements mx.diagonal in operator level, inspired by
@ManishAradwad.
* added `mx.diag` with tests
* corrected few things
* nits in bindings
* updates to diag
---------
Co-authored-by: ManishAradwad <manisharadwad@gmail.com>
Co-authored-by: Awni Hannun <awni@apple.com>
* 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
* fix tests for linux
* make a move on compile
* basic compile scaffold works
* compile binding
* clean
* fix
* fix grad, more tests
* basic python tests
* fix segfault on python exit
* compile works with python closures
* fix test
* fix python globals bug, and erase
* simplify
* more cpp tests
* bug fix with move function and compile at exit
* simplify inputs also
* enable and disable compiler
* remove simplify
* simplify tests use compile now
* fix multi-output with compile
* clear output tree from cache when function goes out of scope
* ../python/src/transforms.cpp
* remove closure capture
* comments
* Added adafactor
* Added Adafactor and ran pre-commit
* modified operations
* Added docstrings
* Switched two ops to fix a bug
* added underscore for internal functions and removed the plus sign in the last return statment
* Removed parameter rms from the optimizer state because its not needed
* Added simple MNIST test for Adafactor and temporary training log
* remove test files
* nits in docs
* comment nit
---------
Co-authored-by: Awni Hannun <awni@apple.com>
* Enable cross_entropy loss to handle dense targets
Dense targets means probabilities or one-hot encodings.
* better shape check of weights
* nits in docstring
---------
Co-authored-by: Awni Hannun <awni@apple.com>
* 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
* Allow arbitrary first dim on qmm_t and qmv
* Allow arbitrary first dim on qmm and qvm
* Specialized aligned vs unaligned case
* Add more checks for valid quantizations
* feat: add logicalAnd and logicalOR
* run pre-commit
* Refactor logical_and and logical_or functions
* Add acknowledgement
* Add logical AND and logical OR operators
* Refactor logical_and and logical_or functions
* Add support for logical operators on bool arrays
* Update mlx/ops.cpp
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
* Update mlx/ops.cpp
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
* Add logical AND and OR operators for arrays and scalars
* Refactor vjp and jvp methods in primitives.cpp
* Add overloaded operators for logical AND and OR
* format
---------
Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
Co-authored-by: Awni Hannun <awni@apple.com>
* Added GLU activation function and gated activation function
* Ran pre-commit
* Ran pre commit
* Removed old sigmoid implementation to match with main
* Removed gated activation from __init__.py
* Removed unused test cases
* Removed unused imports
* format / docstring
---------
Co-authored-by: Awni Hannun <awni@apple.com>
* inner / outer impl
* python tests
* ops list and ack
* updated descriptions
* use test helper
* removed dtype check and flatten outer to 1-D
* updated docs
* just use the reshape to flatten
All functions that take an optional dtype should
* have a default dtype visible in the generated docs (accomplished via `"dtype"_a = std::optional{float32}`)
* behave identical when `dtype=None` or no dtype is passed
This important when passing kw args down from a numpy function like:
```
def f(x, dtype=None):
mx.random.uniform(dtype=dtype)
# ...
```
NumPy functions behave like this.
It also fixes a minor bug in `tri`: #378Closes#378
* support python mlx.array creation from list of mlx.array's
* include bfloat16 in UT
* refactor so that sub array made of all python primitive types gets initialized by fill_vector
* address PR comment: arr.shape().size() -> arr.ndim()
* address PR comment: get back Dtype constness and let stack to handle type promotions automatically
* implemented instancenorm
* implemented vector_norm in cpp
added linalg to mlx
* implemented vector_norm python binding
* renamed vector_norm to norm, implemented norm without provided ord
* completed the implementation of the norm
* added tests
* removed unused import in linalg.cpp
* updated python bindings
* added some tests for python bindings
* handling inf, -inf as numpy does, more extensive tests of compatibility with numpy
* added better docs and examples
* refactored mlx.linalg.norm bindings
* reused existing util for implementation of linalg.norm
* more tests
* fixed a bug with no ord and axis provided
* removed unused imports
* some style and API consistency updates to linalg norm
* remove unused includes
* fix python tests
* fixed a bug with frobenius norm of a complex-valued matrix
* complex for vector too
* addressed PR review comments
* fixed import order in __init__
* expected values in instancenorm tests are simple lists
* minor return expression style change
* added InstanceNorm to docs
* doc string nits
* added myself to individual contributors
---------
Co-authored-by: Awni Hannun <awni@apple.com>
* update module to check weights on load, also fix docs and reorganize tests
* nits + rebase
* a few more docs updates for Module
* use manual module file
* comment
* Added an identity and bilinear layers
Added a reset_parameters option
Added normal init for bias
* pre-commit run
* add type hints for parameters and the return type
change Bilinear math to x_1 and x_2
change __call__ arguments to x and y instead of input and output
add explanation to the Initialization
* Remove unnecessary reshape
* Added 'i' to bilinear formula
* Changed bilinear computation to two matrix multiplications
* avoid saving intermediate results, kept y in bilinear for better clarity (can be replaced with x1)
* Changed math formula in Linear
Added more explanation to math formulas
Changed x1, x2 reshape to support all inputs sizes
* add repeat function
* fix styling
* optimizing repeat
* fixed minor issues
* not sure why that folder is there xD
* fixed now for sure
* test repeat not repeat test
* Fixed
---------
Co-authored-by: Bahaa Eddin tabbakha <bahaa@Bahaas-MacBook-Pro.local>
* implemented vector_norm in cpp
added linalg to mlx
* implemented vector_norm python binding
* renamed vector_norm to norm, implemented norm without provided ord
* completed the implementation of the norm
* added tests
* removed unused import in linalg.cpp
* updated python bindings
* added some tests for python bindings
* handling inf, -inf as numpy does, more extensive tests of compatibility with numpy
* added better docs and examples
* refactored mlx.linalg.norm bindings
* reused existing util for implementation of linalg.norm
* more tests
* fixed a bug with no ord and axis provided
* removed unused imports
* some style and API consistency updates to linalg norm
* remove unused includes
* fix python tests
* fixed a bug with frobenius norm of a complex-valued matrix
* complex for vector too
---------
Co-authored-by: Awni Hannun <awni@apple.com>
