KerasによるLSTMの高速化: cuDNNLSTM ref: https://qiita.com/GushiSnow/items/65975667482291329bd5

file0.txt

pip install git+https://github.com/fchollet/keras.git

file1.py

model = Sequential()
model.add(CuDNNLSTM(hidden_number))

file2.py

x = CuDNNLSTM(hidden_number)(x)

file3.py

        params = self._canonical_to_params(
            weights=[
                self.kernel_r,
                self.kernel_z,
                self.kernel_h,
                self.recurrent_kernel_r,
                self.recurrent_kernel_z,
                self.recurrent_kernel_h,
            ],
            biases=[
                self.bias_r_i,
                self.bias_z_i,
                self.bias_h_i,
                self.bias_r,
                self.bias_z,
                self.bias_h,
            ],
        )

file4.txt

RNNParamsSaveable