test_keras2_numeric.py 文件源码

def test_tiny_image_captioning(self):
        # use a conv layer as a image feature branch
        img_input_1 = Input(shape=(16,16,3))
        x = Conv2D(2,(3,3))(img_input_1)
        x = Flatten()(x)
        img_model = Model(inputs=[img_input_1], outputs=[x])

        img_input = Input(shape=(16,16,3))
        x = img_model(img_input)
        x = Dense(8, name = 'cap_dense')(x)
        x = Reshape((1,8), name = 'cap_reshape')(x)

        sentence_input = Input(shape=(5,)) # max_length = 5
        y = Embedding(8, 8, name = 'cap_embedding')(sentence_input)
        z = concatenate([x,y], axis = 1, name = 'cap_merge')
        z = LSTM(4, return_sequences = True, name = 'cap_lstm')(z)
        z = TimeDistributed(Dense(8), name = 'cap_timedistributed')(z)

        combined_model = Model(inputs=[img_input, sentence_input], outputs=[z])
        self._test_keras_model(combined_model, one_dim_seq_flags=[False, True])