xiaoheizi123 commented on issue #7162: Cant convert caffe model to mxnet
   I also cannot convert resnet-50 using **python convert_caffe_modelzoo.py 
   `converting scale layer, beta shape = (2048,), gamma shape = (2048,)
           skipping layer res5c of type Eltwise
           skipping layer res5c_relu of type ReLU
           skipping layer pool5 of type Pooling
   converting layer fc1000, wmat shape = (1000, 2048), bias shape = (1000,)
           skipping layer prob of type Softmax
 UserWarning: Data provided by label_shapes don't match names specified by 
label_names ([] vs. ['prob_label'])
   Traceback (most recent call last):
     File "convert_caffe_modelzoo.py", line 144, in <module>
       fname, _ = convert_caffe_model(args.model_name, 
     File "convert_caffe_modelzoo.py", line 133, in convert_caffe_model
       convert_mean(mean, [mx_mean])
 line 44, in convert_mean
   google.protobuf.message.DecodeError: Error parsing message
   f.read() is ok, but mean_blob is None when print it?
   I also read 
 and do what **Converting Caffe trained models to MXNet**  part shows, but it 
is still wrong, what should I do? 

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