pg.py 文件源码

def _build_model(self):
        model = Sequential()
        model.add(Reshape((1, 80, 80), input_shape=(self.state_size,)))
        model.add(Convolution2D(32, 6, 6, subsample=(3, 3), border_mode='same',
                                activation='relu', init='he_uniform'))
        model.add(Flatten())
        model.add(Dense(64, activation='relu', init='he_uniform'))
        model.add(Dense(32, activation='relu', init='he_uniform'))
        model.add(Dense(self.action_size, activation='softmax'))
        opt = Adam(lr=self.learning_rate)
        model.compile(loss='categorical_crossentropy', optimizer=opt)
        return model