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Subject [GitHub] [singa] chrishkchris commented on pull request #730: Support training RNN with computation graph
Date Tue, 16 Jun 2020 11:04:14 GMT

chrishkchris commented on pull request #730:
URL: https://github.com/apache/singa/pull/730#issuecomment-644694297


   > This pr is almost done. Now the constructed graph is correct and can be executed normally.
   > There is only one issue. After training some iterations, the loss value will become
NaN. This phenomenon will appear no matter whether the graph is enabled or not. Any ideas
about this problem? @dcslin @chrishkchris
   > 
   > ```shell
   > root@ip-172-31-6-19:/home/ubuntu/Program/singa/examples/qabot git:(lstm-graph*) #
python train.py -g
   > successfully loaded word2vec model and corpus
   > successfully generated train, eval, test data
   > epoch 0, time used 7 sec, top1 hits: 0.000000, loss:  [6.2321043]
   > epoch 1, time used 7 sec, top1 hits: 0.000000, loss:  [6.1910734]
   > epoch 2, time used 7 sec, top1 hits: 0.010000, loss:  [6.1914635]
   > epoch 3, time used 7 sec, top1 hits: 1.000000, loss:  [nan]
   > epoch 4, time used 7 sec, top1 hits: 1.000000, loss:  [nan]
   > epoch 5, time used 7 sec, top1 hits: 1.000000, loss:  [nan]
   > epoch 6, time used 7 sec, top1 hits: 1.000000, loss:  [nan]
   > epoch 7, time used 7 sec, top1 hits: 1.000000, loss:  [nan]
   > epoch 8, time used 7 sec, top1 hits: 1.000000, loss:  [nan]
   > epoch 9, time used 7 sec, top1 hits: 1.000000, loss:  [nan]
   > training top1 hits rate:  1.0
   > ```
   
   @XJDKC 
   
   The LSTM seems still have problem, @dcslin is checking the LSTM with a simpler binary semantic
analysis example at https://github.com/apache/singa/pull/733.
   
   For example, maybe can check the following:
   
   From the website, https://docs.nvidia.com/deeplearning/sdk/cudnn-api/index.html#cudnnRNNForwardTraining
   it says  "strides in xDesc should be set as follows: `strideA[0]=inputSize, strideA[1]=1,
strideA[2]=1`"
   
   While in our code, https://github.com/apache/singa/blob/dev/src/model/operation/rnn.cc#L174
   ```
     strideA[0] = dimA[2] * dimA[1];
     strideA[1] = dimA[2];
     strideA[2] = 1;
   ```
   
   When you finish all other tasks, you may also help to check the rnn.cc also :)


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