QRNN(Quasi-Recurrent Neural Networks)
keras代碼:https://github.com/DingKe/qrnn QRNN爲LSTM加速算法,模型結構如下: qrnn第一層爲卷積層,用於提取輸入特徵,第二層爲pooling層,用於減少特徵數目,但語常用的pooling層不同的是,qrnn採用fo-pool方法,具體計算如下. 卷積層: 對於輸入X,分別通過三個卷積層和非線性層得到Z,F,O,公式如下: Z=tanh(Wz∗X) F=
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