Let's define a CNN from VGG and the LSTM model, using the following code:
vgg_model = tf.keras.applications.vgg16.VGG16(weights='imagenet', include_top=False, input_tensor=input_tensor, input_shape=input_shape) word_embedding = tf.keras.layers.Embedding( vocabulary_size, embedding_dimension, input_length=sequence_length) embbedding = word_embedding(previous_words) embbedding = tf.keras.layers.Activation('relu')(embbedding) embbedding = tf.keras.layers.Dropout(dropout_prob)(embbedding) cnn_features_flattened = tf.keras.layers.Reshape((height * height, shape))(cnn_features) net = tf.keras.layers.GlobalAveragePooling1D()(cnn_features_flattened) net = tf.keras.layers.Dense(embedding_dimension, activation='relu')(net) net = tf.keras.layers.Dropout(dropout_prob)(net) net = tf.keras.layers.RepeatVector(sequence_length...