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"""Globals used internally by the ONNX exporter.
Do not use this module outside of `torch.onnx` and its tests.
Be very judicious when adding any new global variables. Do not create new global
variables unless they are absolutely necessary.
"""
import torch._C._onnx as _C_onnx
# This module should only depend on _constants and nothing else in torch.onnx to keep
# dependency direction clean.
from torch.onnx import _constants
class _InternalGlobals:
"""Globals used internally by ONNX exporter.
NOTE: Be very judicious when adding any new variables. Do not create new
global variables unless they are absolutely necessary.
"""
def __init__(self):
self._export_onnx_opset_version = _constants.ONNX_DEFAULT_OPSET
self._training_mode: _C_onnx.TrainingMode = _C_onnx.TrainingMode.EVAL
self._in_onnx_export: bool = False
# Whether the user's model is training during export
self.export_training: bool = False
self.operator_export_type: _C_onnx.OperatorExportTypes = (
_C_onnx.OperatorExportTypes.ONNX
)
self.onnx_shape_inference: bool = True
self._autograd_inlining: bool = True
@property
def training_mode(self):
"""The training mode for the exporter."""
return self._training_mode
@training_mode.setter
def training_mode(self, training_mode: _C_onnx.TrainingMode):
if not isinstance(training_mode, _C_onnx.TrainingMode):
raise TypeError(
"training_mode must be of type 'torch.onnx.TrainingMode'. This is "
"likely a bug in torch.onnx."
)
self._training_mode = training_mode
@property
def export_onnx_opset_version(self) -> int:
"""Opset version used during export."""
return self._export_onnx_opset_version
@export_onnx_opset_version.setter
def export_onnx_opset_version(self, value: int):
supported_versions = range(
_constants.ONNX_MIN_OPSET, _constants.ONNX_MAX_OPSET + 1
)
if value not in supported_versions:
raise ValueError(f"Unsupported ONNX opset version: {value}")
self._export_onnx_opset_version = value
@property
def in_onnx_export(self) -> bool:
"""Whether it is in the middle of ONNX export."""
return self._in_onnx_export
@in_onnx_export.setter
def in_onnx_export(self, value: bool):
if type(value) is not bool:
raise TypeError("in_onnx_export must be a boolean")
self._in_onnx_export = value
@property
def autograd_inlining(self) -> bool:
"""Whether Autograd must be inlined."""
return self._autograd_inlining
@autograd_inlining.setter
def autograd_inlining(self, value: bool):
if type(value) is not bool:
raise TypeError("autograd_inlining must be a boolean")
self._autograd_inlining = value
GLOBALS = _InternalGlobals()
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