[GitHub] [incubator-mxnet] sxjscience edited a comment on issue #18931: [Development] MXNet 2.0 Update

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sxjscience edited a comment on issue #18931:
URL: https://github.com/apache/incubator-mxnet/issues/18931#issuecomment-676595439


   @StevenJokes In addition, for the DCGAN issue that is related to D2L, a simple way to verify that you are correct (and also convince the others), is to write a test case that checks whether these two networks are **equivalent**.
   
   For example, you have a network A implemented in MXNet and a network B implemented in PyTorch. There are several checks that you can do:
   
   - Just try to see if these two networks have the same number of parameters
   - Do a forward pass of both networks and check whether the outputs are the same. 
   - Do a forward + backward and match the gradient.
   
   Usually, you will need to do more to convince the others that certain issues exist. There are some examples:
   
   - Here, the minimal reproducible example related to Autograd helps us locate the problem: https://github.com/apache/incubator-mxnet/issues/17989
   - A minimal example that captures a potential issue of the GELU implementation in MKLDNN https://github.com/apache/incubator-mxnet/issues/18826
   
   I think it will be a good practice if you can write such test cases and post it under the D2L issue.
   


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