* 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
* Add `py.typed` to support PEP-561 (type-hinting)
This adds support for type-hinting information as laid in [PEP-561](https://peps.python.org/pep-0561/).
* add py.typed to MANIFEST.in
* 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
* 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>
* 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
* 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
