char-rnn-keras
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CuDNNLSTM
I believe CuDNNLSTM will be beneficial for the model.
I tested this on my side and CuDNNLSTM seems to work as a drop-in replacement for LSTM. This only works for keras tensorflow backend though.
That said in my current test case using CuDNNLSTM instead of LSTM make learning phase go 3 times faster. I don't took time to thoroughly cross check results between the 2 variants after learning.
Perhaps one could programmatically check backend and use CuDNNLSTM whenever
keras.backend.backend()=='tensorflow'
@GameLogist thank you for your suggestion I'll use it when possible.