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Keras implementation of “Gated Linear Unit ”
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yangperasd/gated_cnn
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This is Keras implementation of “Gated Linear Unit”.
- Keras 2.1.2
- Tensorflow 1.0.0
- Others can be seen in requirements.txt
The main Class isGatedConvBlock inpy/gated_cnn.py.Because there is a residual connection in Gated Linear Unit (GLU), the padding of conv must besame.Let's take some example.
from gated_cnn import GatedConvBlockmodel = 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))Checkpy/mnist_gated_cnn.py for more detail.
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