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### 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>
74 lines
4 KiB
Python
74 lines
4 KiB
Python
# -------------------------------------------------------------------------
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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# --------------------------------------------------------------------------
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"""
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ONNX Runtime is a performance-focused scoring engine for Open Neural Network Exchange (ONNX) models.
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For more information on ONNX Runtime, please see `aka.ms/onnxruntime <https://aka.ms/onnxruntime/>`_
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or the `Github project <https://github.com/microsoft/onnxruntime/>`_.
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"""
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__version__ = "1.15.0"
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__author__ = "Microsoft"
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# we need to do device version validation (for example to check Cuda version for an onnxruntime-training package).
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# in order to know whether the onnxruntime package is for training it needs
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# to do import onnxruntime.training.ortmodule first.
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# onnxruntime.capi._pybind_state is required before import onnxruntime.training.ortmodule.
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# however, import onnxruntime.capi._pybind_state will already raise an exception if a required Cuda version
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# is not found.
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# here we need to save the exception and continue with Cuda version validation in order to post
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# meaningful messages to the user.
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# the saved exception is raised after device version validation.
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try:
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from onnxruntime.capi._pybind_state import ExecutionMode # noqa: F401
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from onnxruntime.capi._pybind_state import ExecutionOrder # noqa: F401
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from onnxruntime.capi._pybind_state import GraphOptimizationLevel # noqa: F401
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from onnxruntime.capi._pybind_state import ModelMetadata # noqa: F401
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from onnxruntime.capi._pybind_state import NodeArg # noqa: F401
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from onnxruntime.capi._pybind_state import OrtAllocatorType # noqa: F401
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from onnxruntime.capi._pybind_state import OrtArenaCfg # noqa: F401
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from onnxruntime.capi._pybind_state import OrtMemoryInfo # noqa: F401
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from onnxruntime.capi._pybind_state import OrtMemType # noqa: F401
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from onnxruntime.capi._pybind_state import OrtSparseFormat # noqa: F401
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from onnxruntime.capi._pybind_state import RunOptions # noqa: F401
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from onnxruntime.capi._pybind_state import SessionIOBinding # noqa: F401
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from onnxruntime.capi._pybind_state import SessionOptions # noqa: F401
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from onnxruntime.capi._pybind_state import create_and_register_allocator # noqa: F401
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from onnxruntime.capi._pybind_state import disable_telemetry_events # noqa: F401
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from onnxruntime.capi._pybind_state import enable_telemetry_events # noqa: F401
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from onnxruntime.capi._pybind_state import get_all_providers # noqa: F401
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from onnxruntime.capi._pybind_state import get_available_providers # noqa: F401
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from onnxruntime.capi._pybind_state import get_device # noqa: F401
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from onnxruntime.capi._pybind_state import get_version_string # noqa: F401
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from onnxruntime.capi._pybind_state import set_default_logger_severity # noqa: F401
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from onnxruntime.capi._pybind_state import set_default_logger_verbosity # noqa: F401
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from onnxruntime.capi._pybind_state import set_seed # noqa: F401
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import_capi_exception = None
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except Exception as e:
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import_capi_exception = e
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from onnxruntime.capi import onnxruntime_validation
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if import_capi_exception:
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raise import_capi_exception
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from onnxruntime.capi.onnxruntime_inference_collection import InferenceSession # noqa: F401
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from onnxruntime.capi.onnxruntime_inference_collection import IOBinding # noqa: F401
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from onnxruntime.capi.onnxruntime_inference_collection import OrtDevice # noqa: F401
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from onnxruntime.capi.onnxruntime_inference_collection import OrtValue # noqa: F401
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from onnxruntime.capi.onnxruntime_inference_collection import SparseTensor # noqa: F401
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from onnxruntime.capi.training import * # noqa: F403
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# TODO: thiagofc: Temporary experimental namespace for new PyTorch front-end
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try: # noqa: SIM105
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from . import experimental # noqa: F401
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except ImportError:
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pass
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from onnxruntime.capi.onnxruntime_validation import cuda_version, package_name, version # noqa: F401
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if version:
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__version__ = version
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onnxruntime_validation.check_distro_info()
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