### Description
`get_device()` returns a string of hyphen connected device names, such
as "GPU-DML". It's a problem that when CUDA is disabled but OpenVino GPU
is enabled in the build, because in this case `get_device()` returns
"CPU-OPENVINO_GPU", so `supports_device("CUDA")` will return `True` in
this build.
Splitting the value of `get_device()` by "-" and check if the input is
in the list is not an option because it seems some code in the code base
stores the value of `get_device()` and use the value to call
`supports_device()`. Using this implementation will cause
`supports_device("GPU-DML")` to return `False` for a build with
`get_device() == "GPU-DML"` because `"GPU-DML" in ["GPU", "DML"]` is
`False`.
This change also helps to avoid further problems when "WebGPU" is
introduced.
### Description
Disable two PERF* rules in ruff to allow better readability. Rational
commented inline. This change also removes the unused noqa directives
because of the rule change.
### Motivation and Context
Readability
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at
bottom):
* __->__ #16789
Bump ruff to 0.0.278 and fix new lint errors. I added noqa to all
existing RUF012 errors which requires mutable class variables to be
annotated with `ClassVar`, as well as all PERF issues.
Signed-off-by: Justin Chu <justinchu@microsoft.com>
### Description
`lintrunner` is a linter runner successfully used by pytorch, onnx and
onnx-script. It provides a uniform experience running linters locally
and in CI. It supports all major dev systems: Windows, Linux and MacOs.
The checks are enforced by the `Python format` workflow.
This PR adopts `lintrunner` to onnxruntime and fixed ~2000 flake8 errors
in Python code. `lintrunner` now runs all required python lints
including `ruff`(replacing `flake8`), `black` and `isort`. Future lints
like `clang-format` can be added.
Most errors are auto-fixed by `ruff` and the fixes should be considered
robust.
Lints that are more complicated to fix are applied `# noqa` for now and
should be fixed in follow up PRs.
### Notable changes
1. This PR **removed some suboptimal patterns**:
- `not xxx in` -> `xxx not in` membership checks
- bare excepts (`except:` -> `except Exception`)
- unused imports
The follow up PR will remove:
- `import *`
- mutable values as default in function definitions (`def func(a=[])`)
- more unused imports
- unused local variables
2. Use `ruff` to replace `flake8`. `ruff` is much (40x) faster than
flake8 and is more robust. We are using it successfully in onnx and
onnx-script. It also supports auto-fixing many flake8 errors.
3. Removed the legacy flake8 ci flow and updated docs.
4. The added workflow supports SARIF code scanning reports on github,
example snapshot:
5. Removed `onnxruntime-python-checks-ci-pipeline` as redundant
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Unified linting experience in CI and local.
Replacing https://github.com/microsoft/onnxruntime/pull/14306
---------
Signed-off-by: Justin Chu <justinchu@microsoft.com>
Description: Format all python files under onnxruntime with black and isort.
After checking in, we can use .git-blame-ignore-revs to ignore the formatting PR in git blame.
#11315, #11316
* add use_tensorrt build option
* Add use_tensorrt to running tests
* add use_tensorrt for Windows
* make trt ep to skip backend test
* make trt ep to skip backend test
* Fix bug
* Add/Modify description
* modify for debug
* swtich pool to test
* modify to debug
* modify to debug
* add vobersity
* refine the code
* refine the code
* refine the code
* fix flake8 warning
* refine the code
* add pre_load check for trt as well as add cupti lib to cuda depedencies
* modify script to make trt build path the same as cuda
* show error message when user wants to run TensorRT but TensorRT is not installed in the env
* fix bug
* fix bug
* add trt lib for manylinux
* include cuda_dependencies for trt
* rewrite the condition to throw exception
* make code more compact
* remove default python ep registration. raise exception if providers are not explicitly set if there are available providers
* temporarily disable exception
* fix python tests
* explicitly set CUDAProvider for python iobinding tests
* explicitly set providers param for InferenceSession())
* onnxrt
* raise ValueError if not explicitly set providers when creating InferenceSession
* add required providers param
* explicitly set providers
* typo
* The serialization can be very heavy for large models
* Only use the serialized model check on compatible onnx versions
* onnx version >= 1.10.0 supports serialized model check
Signed-off-by: IceTDrinker <49040125+IceTDrinker@users.noreply.github.com>
* Enable running PEP8 checks via flake8 as part of the build if flake8 is installed.
Update scripts in \tools and \onnxruntime\python. Excluding \onnxruntime\python\tools which needs a lot more work to be PEP8 compliant. Also excluding orttraining\tools for the same reason.
Install flake8 as part of the static_analysis build task in the Win-CPU CI so the checks are run in one CI build.
Update coding standards doc.
Update ReformatSourcePython.bat to use YAPF to format python code, and add onnxruntime\test directory to be formatted.
Add onnxruntime\.style.yapf for configuration. The style is based on google, except max column width 120.
Format python scripts using ReformatSourcePython.bat.
* py fallback initial commit.
* fixes.
* update NGRAPHCustomOp::Initialize() to return Status
* fixes in session.py
* FAIL status to EP_FAIL in ngraph custom op
* disable fallback for backend api
