Hi,
i have a problem when converting torch script module in to ONNX module,
but it’s works just fine on “normal” module,
i open a bug request about that at https://github.com/pytorch/pytorch/issues/30512 13,
but if i could convert the torch script module to nn module it’s will solve my issue,
Thanks,
Liron
code example:(you can ignore the test_normal )
    def _test_normal(self, num_classes, dummy_input):
        model = torchvision.models.resnet18(num_classes=num_classes)
        model_state_fixed = {}
        for k, v in self._model_state.items():
            k_fixed = k[3:len(k)]
            model_state_fixed[k_fixed] = v
        model.load_state_dict(model_state_fixed)
        torch.onnx.export(model, dummy_input, "/app_data/test_torch_script/torch_script_test_normal.onnx")

    def convert(self):
        loaded = torch.jit.load(self._torch_script_path)
        # loaded.load_state_dict(self._model_state)
        dummy_input = torch.randn(1, 3, 224, 224)
        target = loaded(dummy_input)
        self._test_normal(num_classes=len(target[0]), dummy_input=dummy_input)
        torch.onnx.export(loaded, dummy_input, self._out_onnx_path, verbose=True,
                          operator_export_type=torch.onnx.OperatorExportTypes.ONNX,
                          example_outputs=target)