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Hi, @longcw, thanks for your work. Recently, I need to transform a pytorch model(RFBNet) which has two sibling output to caffe's format. When I used your pytorch2caffe function, it shown that CudnnConvolutionBackward not in dict of layer_dict, when I set torch.backends.cudnn.enabled==False, it shown that ThnnConv2DBackward not in dict of layer_dict. Additionly, MulBackward0,AddBackward1 as the same. How should I parse the
operator of CudnnConvolutionBackward(ThnnConv2DBackward), ThresholdBackward1, ThresholdBackward0, MulBackward0, AddBackward1?
The version of torch I used is 0.4.0
The text was updated successfully, but these errors were encountered:
@peyer 0.4.0 is not supported, you should transform the model manully. If you really want to parse AddBackward1, you should change the key value "AddBackward" to "AddBackward1" in layer_dict. Other layers are similar.
Hi, @longcw, thanks for your work. Recently, I need to transform a pytorch model(RFBNet) which has two sibling output to caffe's format. When I used your pytorch2caffe function, it shown that CudnnConvolutionBackward not in dict of layer_dict, when I set torch.backends.cudnn.enabled==False, it shown that ThnnConv2DBackward not in dict of layer_dict. Additionly, MulBackward0,AddBackward1 as the same. How should I parse the
operator of CudnnConvolutionBackward(ThnnConv2DBackward), ThresholdBackward1, ThresholdBackward0, MulBackward0, AddBackward1?
The version of torch I used is 0.4.0
The text was updated successfully, but these errors were encountered: