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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2020/08/31 18:55:09 UTC

[GitHub] [incubator-mxnet] Zha0q1 edited a comment on pull request #19033: Numpy RNN operator large dim checks

Zha0q1 edited a comment on pull request #19033:
URL: https://github.com/apache/incubator-mxnet/pull/19033#issuecomment-683964791


   > To start with, we may first check the gradient of smaller workloads by calculating the finite difference: #19045. We can pregenerate the states and inputs to avoid flaky test.
   
   Just a random thought: since we would be comparing numerical and analytical gradient results, I think there might be some requirements on the precision/scale of inputs to limit the error? We might want to try this approach out on some simple ops first


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