* einsum initial
* fix comma break
* sum axis was wrong
* small cleanups
* python binding
* changed bindings to resemble numpy
* remove todo comment
* comment changes
* add count of operands/inputs
* fail fast if operands list is empty
* ignore comma if no output
* einsum path matching numpy
* getting somewhere with path
* remove print
* it passes the first test
* moved einsum tests to seperate file
* seperated einsum path
* moved einsum naive
* remove space from equation
* fast fail if no operands passed
* update tests and remove printf
* small cleanup
* some more cleanups
* removed python helper file
* ack
* utilize std for finding min in vector
* duplicate def
* remove the tuple as it was unreadable
* moved einsum_naive back to ops
* remaining isn't needed
* avoid creating another set
* cleanup
* greedy path, start of naive einsum
* more einsum
* fix some bugs
* some more fixes, tests pass
* benchmark
* some simplify
* fix einsum and test
Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com>
* add a bunch more tests and fix a bunch more bugs
* some docs nits
---------
Co-authored-by: dc-dc-dc <dgcruz983@gmail.com>
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
* 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>
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
