mirror of
https://github.com/saymrwulf/onnxruntime.git
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c7c8757a1c
Use ruff as the code formatter in place of black and isort since it is much faster, and as projects like PyTorch and ONNX have adopted ruff format as well. This PR include only auto-fixed changes in formatting.
83 lines
3.1 KiB
Python
83 lines
3.1 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__ = "1.21.0"
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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 (
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ExecutionMode, # noqa: F401
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ExecutionOrder, # noqa: F401
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GraphOptimizationLevel, # noqa: F401
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LoraAdapter, # noqa: F401
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ModelMetadata, # noqa: F401
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NodeArg, # noqa: F401
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OrtAllocatorType, # noqa: F401
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OrtArenaCfg, # noqa: F401
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OrtMemoryInfo, # noqa: F401
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OrtMemType, # noqa: F401
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OrtSparseFormat, # noqa: F401
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RunOptions, # noqa: F401
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SessionIOBinding, # noqa: F401
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SessionOptions, # noqa: F401
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create_and_register_allocator, # noqa: F401
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create_and_register_allocator_v2, # noqa: F401
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disable_telemetry_events, # noqa: F401
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enable_telemetry_events, # noqa: F401
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get_all_providers, # noqa: F401
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get_available_providers, # noqa: F401
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get_build_info, # noqa: F401
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get_device, # noqa: F401
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get_version_string, # noqa: F401
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has_collective_ops, # noqa: F401
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set_default_logger_severity, # noqa: F401
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set_default_logger_verbosity, # noqa: F401
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set_seed, # noqa: F401
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)
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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 (
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AdapterFormat, # noqa: F401
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InferenceSession, # noqa: F401
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IOBinding, # noqa: F401
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OrtDevice, # noqa: F401
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OrtValue, # noqa: F401
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SparseTensor, # noqa: F401
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)
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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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