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0a274c4b6c
Default runtime type checking to raise by changing the default value to `GLOBALS.runtime_type_check_state` into ERRORS Pull Request resolved: https://github.com/pytorch/pytorch/pull/86555 Approved by: https://github.com/BowenBao
90 lines
3.1 KiB
Python
90 lines
3.1 KiB
Python
"""Globals used internally by the ONNX exporter.
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Do not use this module outside of `torch.onnx` and its tests.
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Be very judicious when adding any new global variables. Do not create new global
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variables unless they are absolutely necessary.
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"""
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import os
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import torch._C._onnx as _C_onnx
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# This module should only depend on _constants and nothing else in torch.onnx to keep
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# dependency direction clean.
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from torch.onnx import _constants, _exporter_states
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class _InternalGlobals:
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"""Globals used internally by ONNX exporter.
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NOTE: Be very judicious when adding any new variables. Do not create new
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global variables unless they are absolutely necessary.
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"""
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def __init__(self):
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self._export_onnx_opset_version = _constants.ONNX_DEFAULT_OPSET
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self._training_mode: _C_onnx.TrainingMode = _C_onnx.TrainingMode.EVAL
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self._in_onnx_export: bool = False
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# Whether the user's model is training during export
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self.export_training: bool = False
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self.operator_export_type: _C_onnx.OperatorExportTypes = (
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_C_onnx.OperatorExportTypes.ONNX
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)
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self.onnx_shape_inference: bool = True
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# Internal feature flags
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if os.getenv("TORCH_ONNX_EXPERIMENTAL_RUNTIME_TYPE_CHECK") == "WARNINGS":
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self.runtime_type_check_state = (
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_exporter_states.RuntimeTypeCheckState.WARNINGS
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)
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elif os.getenv("TORCH_ONNX_EXPERIMENTAL_RUNTIME_TYPE_CHECK") == "DISABLED":
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self.runtime_type_check_state = (
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_exporter_states.RuntimeTypeCheckState.DISABLED
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)
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else:
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self.runtime_type_check_state = (
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_exporter_states.RuntimeTypeCheckState.ERRORS
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)
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@property
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def training_mode(self):
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"""The training mode for the exporter."""
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return self._training_mode
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@training_mode.setter
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def training_mode(self, training_mode: _C_onnx.TrainingMode):
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if not isinstance(training_mode, _C_onnx.TrainingMode):
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raise TypeError(
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"training_mode must be of type 'torch.onnx.TrainingMode'. This is "
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"likely a bug in torch.onnx."
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)
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self._training_mode = training_mode
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@property
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def export_onnx_opset_version(self) -> int:
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"""Opset version used during export."""
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return self._export_onnx_opset_version
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@export_onnx_opset_version.setter
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def export_onnx_opset_version(self, value: int):
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supported_versions = range(
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_constants.ONNX_MIN_OPSET, _constants.ONNX_MAX_OPSET + 1
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)
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if value not in supported_versions:
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raise ValueError(f"Unsupported ONNX opset version: {value}")
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self._export_onnx_opset_version = value
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@property
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def in_onnx_export(self) -> bool:
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"""Whether it is in the middle of ONNX export."""
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return self._in_onnx_export
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@in_onnx_export.setter
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def in_onnx_export(self, value: bool):
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if type(value) is not bool:
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raise TypeError("in_onnx_export must be a boolean")
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self._in_onnx_export = value
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GLOBALS = _InternalGlobals()
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