[code lang="python"] from keras.models import Model from keras.layers import Input, Dense
input_1 = Input(..., name='input_1') x = Dense(...)(input_1) x = Dense(...)(x) ... output_1 = Dense(dim_output_1, ..., name='output_1')
input_2 = Input(..., name='input_2') x = keras.layers.concatenate([output_1, input_2]) x = Dense(...)(x) x = Dense(...)(x) x = Dense(...)(x) output_2 = Dense(dim_output_2, ..., name='output_2')(x)
model = Model(inputs=[input_1, input_2], outputs=[output_1, output_2]) model.compile(..., loss={'output_1': 'binary_crossentropy', 'output_2': 'binary_crossentropy'}, loss_weights={'output_1': weight_1., 'output_2': weight_2}) model.fit({'input_1': data_input_1, 'input_2': data_input_2}, {'output_1': data_output_1, 'output_2': data_output_2}, ...) [/code]
