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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2017/12/21 23:35:39 UTC

[GitHub] kalpitdixit commented on issue #9171: MXNet: Using FusedRNNCell with its "bidirectional" flag turned True, can lead to hanging of training run.

kalpitdixit commented on issue #9171: MXNet: Using FusedRNNCell with its "bidirectional" flag turned True, can lead to hanging of training run.
URL: https://github.com/apache/incubator-mxnet/issues/9171#issuecomment-353484524
 
 
   I am using:
   MXNet==1.0.0
   CUDA==9.0
   cuDNN==7.0
   
   As I understand, the FusedRNNCell is faster than the unused RNNCell because it makes direct function calls to a cuda kernel. It seems that the "bidirectional" flag in FusedRNNCell is directly passed to the cuda kernel call. This is just fyi. This might imply some cuda kernel issue but I am not a cuda expert.
   
   @eric-haibin-lin 

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