* cvar dtype:DType|tuple[DType, ...]|None=None
* fmt
* add a test
* list typeguard as a dep for CI
* extra step to install mypy
* fix venv
* ci fixes
* mv typeguard to testing install group
* simpler TYPED=1 test
* add typeguard to lint group
* bump
* thou hast implement functions
* hacked in domain support
* some clean ups
* hack quantize_onnx_test too
* add helper lol, why onnx tests why
* better dispatcher, but need tests and better naming
* flaky ci
* change some names
* small clean ups
* make it easier to clean up tests once ORT supports 1.18.0
* nits
* fix bug of Softmax_1 being registered in onnx_ops
* need a default value
* resolve_const is better name
* fix OnnxRunner.to
* use proper domain names
* truncate fp8
* fix
* maybe like that?
* fix linters
* ruff
* move from extra and add ml_types to tests
* minor changes
* str to dtypes and nan support
---------
Co-authored-by: pkotzbach <pawkotz@gmail.com>
* add system json for mi300x mlperf
```
python3 -m mlperf_logging.system_desc_checker examples/mlperf/training_submission_v5.0/tinycorp/systems/tinybox_8xMI300X.json training 4.1.0
INFO - System description checker passed for tinybox 8xMI300X
```
also removed the rocm from tinybox_red since we are not using it
* update mlperf-logging version
* fast idiv with tests and fuzzer
* Add todo comment
* Add env variable to toggle fast_idiv
* Move env check
* Add fuzz fast_idiv to ci
---------
Co-authored-by: chenyu <chenyu@fastmail.com>
* boom
* fix webgpu
* use exact variable names in test so that AI can read easier
* add tag for specific test name like test a specific dtype
* fix ruff
* astype everything
* dtype in array creation
* just arange
* is 67% considered fixed?
* move test up
* small cleanups
* share function
* add qgemm as well
* add qgemm too
* make sure qgemm comes out as int
* take out qgemm for now
* fixed test
* add correct qgemm
* addressing feedback here too, early naive fix for now
* simplify bias and c to be minimalistic enough to test correctness
* refactored qlinearops
* maybe these asserts aren't the best..
* fix test
* updated tests to cover new ops
* try to add to CI
* move test_onnx_ops into testextra/
* more attention tests
* qlinear_add atol=1
* attention still not fullllllly correct
* it is what it is
---------
Co-authored-by: chenyu <chenyu@fastmail.com>
* Switch to dawn, all tests passing locally
* Use dawn-python
* Skip failing test
* Skip midcast and fix timestamp on metal ci
* Autogen webgpu
* Try fetch dawn lib again
* /usr/lib
* Without lib prefix
* Test autogen diff
* Delete webgpu support, move everything to ops_webgpu
* mypy fix
* Simplify, refactor
* Line savings
* No ResultContainer
* Type annotation for result
* Some more simplifications
* Why was this explicit sync used at all?
* Refactor: delete functions that are only used once
* Create shader module inline
* Clear unit tests cache, maybe that solves it
* That wasn't it
* Try deleting cache to pass failing weight compare
* weights_only=False for pytorch 2.6
* Simplify ctype array creation
* Remove nanosecond precision timestamps
* Simplify error handling
* Refactor, add back type annotations
* Deleted custom submit function, refactor
* read_buffer simplify
* Fix use after free, refactor
* Simplify supported_features
* Runtime docs
---------
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
