keras 实现多输入和多输出

1. 加载数据
   from keras.layers import Input, Embedding, LSTM, Dense
   from keras.models import Model
   import numpy as np
   import keras

main_input = Input((100,), dtype='int32', name='main_input')

x = Embedding(output_dim=512, input_dim=10000, input_length=100)(main_input)
lstm_out = LSTM(32)(x)
aux_output = Dense(1, activation='sigmoid', name='aux_output')(lstm_out)
aux_input = Input((5,), name='aux_input')
x = keras.layers.concatenate([lstm_out, aux_input])
x = Dense(64, activation='relu')(x)
x = Dense(64, activation='relu')(x)
x = Dense(64, activation='relu')(x)
main_output = Dense(1, activation='sigmoid', name='main_output')(x)

model = Model(inputs=[main_input, aux_input], outputs=[main_output, aux_output])
model.compile(optimizer='rmsprop',
loss={'main_output': 'binary_crossentropy', 'aux_output': 'binary_crossentropy'},
loss_weights={'main_output': 1., 'aux_output': 0.3})
print(model.summary())

dssm.png