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From Xingjian Shi <notificati...@github.com>
Subject Re: [apache/incubator-mxnet] [Development] MXNet 2.0 Update (#18931)
Date Wed, 19 Aug 2020 18:42:45 GMT
@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:


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