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[MXNET-107] Add Fused Vanilla RNN and dropout for CPU#11399
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piiswrong merged 1 commit intoapache:masterfrom Jun 26, 2018
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[MXNET-107] Add Fused Vanilla RNN and dropout for CPU#11399piiswrong merged 1 commit intoapache:masterfrom
piiswrong merged 1 commit intoapache:masterfrom
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Please remove [WIP] from the title and add the JIRA number to it. https://issues.apache.org/jira/browse/MXNET-107 |
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Description
In this PR, it creates Fused Vanilla RNN(tanh/relu) operator and dropout of GRU/LSTM/vRNN for CPU.
@pengzhao-intel, @TaoLv
Feature changes
New features
Unit-test changes
Performance
We have tested performance of FusedRNN and NonFused RNNCell on our local Skylake-8180 with 2 Sockets and 56 cores. Use MKL as blas lib in this performance test.
Test input size is from DS2 default parameters(seq_length = 300, batch_size = 20, input_size = 800, hidden_size = 800).
Layer=1 bidirectional = False
Layer=5 bidirectional = True
Convergency Curve
We have tested Convergency of FusedGRU/LSTM(dropout = 0.5) on our CPU-Skylake-8180 with 2 Sockets and 56 cores and GPU-P100 by using example/rnn/bucketing/cudnn_rnn_bucketing.py
Test input size is layer = 3, batch_size = 32, num-embed = 800, num-hidden = 800, num-epochs 20
@szha: resolves #10870, #10872