gated_cnn:Keras实施“门控线性单元”

# Gated CNN This is Keras implementation of “Gated Linear Unit”. # Requirements - Keras 2.1.2 - Tensorflow 1.0.0 - Others can be seen in requirements.txt # Usage The main Class is `GatedConvBlock` in `py/gated_cnn.py`. Because there is a residual connection in Gated Linear Unit (GLU), the padding of conv must be `same`. Let's take some example. ``` from gated_cnn import GatedConvBlock model = Sequential() model.add(Convolution2D(nb_filters, kernel_size, padding='valid', input_shape=input_shape)) model.add(Activation('relu')) model.add(GatedConvBlock(Convolution2D(nb_filters*2, kernel_size, padding='same'))) model.add(Activation('relu')) model.add(MaxPooling2D(pool_size=pool_size)) model.add(Dropout(0.25)) model.add(Flatten()) model.add(Dense(128)) model.add(Activation('relu')) model.add(Dropout(0.5)) model.add(Dense(nb_classes)) model.add(Activation('softmax')) model.compile(loss='categorical_crossentropy', optimizer='adadelta', metrics=['accuracy']) model.fit(X_train, Y_train, batch_size=batch_size, epochs=nb_epoch, verbose=1, validation_data=(X_test, Y_test)) ``` Check `py/mnist_gated_cnn.py` for more detail. # Reference - https://github.com/anantzoid/Language-Modeling-GatedCNN > Written with [StackEdit](https://stackedit.io/).