* initial attempt, working with wrong types
* not compiling; mx.float16 and mx.bfloat16 tests added
* fix nan to num
* nit
---------
Co-authored-by: Awni Hannun <awni@apple.com>
* 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
* 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>
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>
* 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
* 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
