def _convert(self) -> None:
prev_opset_version = None
prev_export_type = None
prev_shape_inference = None
try:
assert not to_utils.is_in_onnx_export() # type: ignore[no-untyped-call]
with to_utils.select_model_mode_for_export(self.original_model, self.training):
to_utils.__IN_ONNX_EXPORT = True
prev_opset_version = sym_hel._export_onnx_opset_version
sym_hel._set_opset_version(self.opset_version) # type: ignore[no-untyped-call]
prev_export_type = sym_hel._operator_export_type
sym_hel._set_operator_export_type(self.operator_export_type) # type: ignore[no-untyped-call]
prev_shape_inference = sym_hel._onnx_shape_inference
sym_hel._set_onnx_shape_inference( # type: ignore[no-untyped-call]
False # TODO(twata): Use `self.onnx_shape_inference`
)
self._run_trace()
self.model: onnx.ModelProto = self.generate_onnx()
finally:
to_utils.__IN_ONNX_EXPORT = False
if prev_opset_version is not None:
sym_hel._set_opset_version(prev_opset_version) # type: ignore[no-untyped-call]
if prev_shape_inference is not None:
sym_hel._set_operator_export_type(prev_export_type) # type: ignore[no-untyped-call]
if prev_shape_inference is not None:
sym_hel._set_onnx_shape_inference(prev_shape_inference) # type: ignore[no-untyped-call]
def is_in_onnx_export():
r"""
Returns True iff :func:`export` is running in the current thread
"""
from torch.onnx import utils
return utils.is_in_onnx_export()
def is_in_onnx_export():
r"""
Check whether it's in the middle of the ONNX export.
This function returns True in the middle of torch.onnx.export().
torch.onnx.export should be executed with single thread.
"""
from torch.onnx import utils
return utils.is_in_onnx_export()
def is_in_onnx_export():
from torch.onnx import utils
return utils.is_in_onnx_export()
