chinakook commented on issue #7820: Low accuracy of pvanet URL: https://github.com/apache/incubator-mxnet/issues/7820#issuecomment-328280564 1. You can fix the same net weights in both caffe and mxnet, and debug layer by layer to see the result is whether the same. 2. Check mean file and std scale value. 3. Weights initialized with mx.random.normal in mxnet is worse than Xaviar or msra. So weights initialization is very sensitive in mxnet, otherwise you will get bad result as my experience. 4. I can't understand the meaning of the line 'pool5 = mx.sym.Pooling(data=bsr, kernel=(1, 1), stride=(1, 1), pad=(0, 0), pool_type='max', name='pool5')'. Moreover, pooling is 'valid' in mxnet but 'full' in caffe. Anyway, If you want to port caffe to mxnet, fix the same net weights and compare the result of inferencing result of both framework is needed. As for training, It's complicated because the platform differences. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
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