def _strip_raw_data(tensor: onnx.TensorProto) -> onnx.TensorProto:
arr = onnx.numpy_helper.to_array(tensor)
meta_dict = {}
meta_dict['type'] = "stripped"
meta_dict['average'] = float(arr.mean()) # type: ignore[assignment]
meta_dict['variance'] = float(arr.var()) # type: ignore[assignment]
if not tensor.HasField("raw_data"):
tensor.raw_data = onnx.numpy_helper.from_array(arr,
tensor.name).raw_data
onnx.external_data_helper.set_external_data(tensor,
location=json.dumps(meta_dict),
length=arr.nbytes)
tensor.data_location = onnx.TensorProto.EXTERNAL
tensor.ClearField('raw_data')
tensor.ClearField('float_data')
return tensor
def make_external_tensor(name, data_type, dims, raw_data=None, **kwargs):
tensor = TensorProto()
tensor.data_type = data_type
tensor.name = name
tensor.dims.extend(dims)
tensor.raw_data = raw_data if raw_data is not None else b''
external_data_helper.set_external_data(tensor, **kwargs)
if raw_data is None:
tensor.ClearField("raw_data")
order_repeated_field(tensor.external_data, 'key', kwargs.keys())
return tensor
