turtleizzy edited a comment on issue #13949: Error: shape inconsistent while converting PyTorch model to mxnet model with onnx URL: https://github.com/apache/incubator-mxnet/issues/13949#issuecomment-471307657 > @wangliye00 @Con-Mi However, I do see the error that you facing with MXNet v1.3.1. For fixing this, could you try pulling in the commit #13413 and checking if you are able to proceed further? I am facing similar issue when loading pytorch-densenet onnx model into mxnet. The error message reads: ``` /usr/local/lib/python3.6/site-packages/mxnet/contrib/onnx/onnx2mx/import_onnx.py in _convert_operator(self, node_name, op_name, attrs, inputs) 59 """ 60 if op_name in convert_map: ---> 61 op_name, new_attrs, inputs = convert_map[op_name](attrs, inputs, self) 62 else: 63 raise NotImplementedError("Operator {} not implemented.".format(op_name)) /usr/local/lib/python3.6/site-packages/mxnet/contrib/onnx/onnx2mx/_op_translations.py in reshape(attrs, inputs, proto_obj) 432 if len(inputs) == 1: 433 return 'reshape', attrs, inputs[0] --> 434 reshape_shape = list(proto_obj._params[inputs[1].name].asnumpy()) 435 reshape_shape = [int(i) for i in reshape_shape] 436 new_attrs = {'shape': reshape_shape} KeyError: 'concat51' ``` I tried mxnet 1.3.1 (after patched `import_onnx.py` following your suggestion) and 1.4.0 with no luck, both raised similar exception.
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