woolpeeker
commented
4 years ago I meet the same problem. Has it solved?
Open thomas-beznik opened 4 years ago
woolpeeker
commented
4 years ago I meet the same problem. Has it solved?
Description
Hello,
I am trying to convert an ONNX model coming from a PyTorch model to an MXNet model. The PyTorch model is an FPN that comes from this repository https://github.com/qubvel/segmentation_models.pytorch. I am running into the following error when using the method mxnet.contrib.onnx.onnx2mx.import_model
Error Message
Traceback (most recent call last): File "C:/Users/thoma/Documents/relu/AI_API/API/Detectors/Slice2DDetectorONNX.py", line 96, in
sym, arg_params, aux_params = import_model(model_path)
File "C:\Users\thoma\Documents\relu\AI_API\env\lib\site-packages\mxnet\contrib\onnx\onnx2mx\import_model.py", line 59, in import_model
sym, arg_params, aux_params = graph.from_onnx(model_proto.graph)
File "C:\Users\thoma\Documents\relu\AI_API\env\lib\site-packages\mxnet\contrib\onnx\onnx2mx\import_onnx.py", line 115, in from_onnx
inputs = [self._nodes[i] for i in node.input]
File "C:\Users\thoma\Documents\relu\AI_API\env\lib\site-packages\mxnet\contrib\onnx\onnx2mx\import_onnx.py", line 115, in
inputs = [self._nodes[i] for i in node.input]
KeyError: 'components.0.net.net.encoders.0.basic_module.SingleConv1.conv.weight'
I saw similar issues (such as https://github.com/apache/incubator-mxnet/issues/13395), which say that the problem comes from the fact that Dynamic Shape isn't implemented. But in my case, I am not using a dynamic shape; all my inputs are resized to a fixed shape before being fed to the model. Is there thus a way to easily change my architecture such that it uses this fixed shape and enables me to load my model in MXNet?
I can give more information if needed, any direction to solve this would be greatly appreciated!
To Reproduce