discriminator.py 文件源码

def create_trainable_model(self,nb_event,nb_type,nb_feature):
        from keras.layers import Input, Dense, Flatten, Convolution2D, Activation, Dropout, merge
        from keras.models import Model
        from keras.regularizers import l1,l2

        x = Input(batch_shape=(1, nb_event, nb_type, nb_feature), dtype='float')
        y = Convolution2D(128, kernel_size=[nb_event-10+1, 1], strides=(2,1), activation='relu')(x)
        y = Dropout(0.5)(y)
        y = Convolution2D(128, kernel_size=[3, nb_type], activation='relu')(y)
        y = Dropout(0.5)(y)
        y = Flatten()(y)
        y = Dense(2,activation='softmax')(y)

        model = Model(inputs=[x], outputs=[y], name='dis_output')
        self.model = model
        return model