user_id_input = Input(shape=[1], name='user')
item_id_input = Input(shape=[1], name='item')

embedding_size = 10
user_embedding = Embedding(output_dim=embedding_size, input_dim=users.shape[0],
                           input_length=1, name='user_embedding')(user_id_input)
item_embedding = Embedding(output_dim=embedding_size, input_dim=beers.shape[0],
                           input_length=1, name='item_embedding')(item_id_input)

user_vecs = Reshape([embedding_size])(user_embedding)
item_vecs = Reshape([embedding_size])(item_embedding)

# Add dense towers or not.
# user_vecs = Dense(64, activation='relu')(user_vecs)
# item_vecs = Dense(64, activation='relu')(item_vecs)

input_vecs = Multiply()([user_vecs, item_vecs]) # can be changed by concat or dot.
                                                # (if dot, no dense layer can be used after)
input_vecs = Dropout(0.2)(input_vecs)

x = Dense(128, activation='relu')(input_vecs)
#x = Dropout(0.2)(x) # Add droupout or not
#x = Dense(64, activation='relu')(x) # Add dense again or not
#x = Dropout(0.2)(x) # Add droupout or not
#x = Dense(32, activation='relu')(x) # Add dense again or not

y = Dense(1)(x)

model = Model(inputs=[user_id_input, item_id_input], outputs=y)
model.compile(optimizer='adam', loss='mse')