sentiment_lstm.py 文件源码

def train_lstm(dict,x,y,xt,yt):
  model = Sequential()
  model.add(Embedding(len(dict)+1, 256, input_length=maxlen))
  model.add(LSTM(output_dim=128, activation='sigmoid', inner_activation='hard_sigmoid'))
  model.add(Dropout(0.5))
  model.add(Dense(1))
  # model.add(Dense(input_dim = 32, output_dim = 1))
  model.add(Activation('sigmoid'))
  print ('??????')
  #model.compile(loss='binary_crossentropy', optimizer='adam', class_mode="binary")
  model.compile(optimizer='rmsprop', loss='binary_crossentropy', metrics=['accuracy'])
  print ("??????")
  model.fit(x, y, batch_size=lstm_batch_size, epochs=lstm_epochs, verbose=0)
  print ("??????")
  print ("????")
  yaml_string = model.to_yaml()
  with open(modeldir + '/lstm.yml', 'w') as outfile:
    outfile.write( yaml.dump(yaml_string, default_flow_style=True) )
  model.save_weights(modeldir + '/lstm.h5')
  print ("?????")
  score = model.evaluate(xt, yt, verbose=0)
  print ("???:",score[1])
  return model