rnnmlp.py 文件源码

def LSTMModel(self, nHidden=150, lr = 0.01):
#               print('nHidden: %i\tlr: %.3f' % ( nHidden, lr) )
                self.rnnModel.add(GRU( nHidden, activation='sigmoid', input_shape =( None, self.maxFeatures), return_sequences=True))
#                self.rnnModel.add(LSTM( nHidden, activation='sigmoid', input_shape =( None, nHidden), return_sequences=True))
                self.rnnModel.add(TimeDistributedDense(nHidden))
                self.rnnModel.add(Activation('relu'))
                self.rnnModel.add(TimeDistributedDense(self.maxFeatures))
                self.rnnModel.add(Activation('softmax'))
                rmsprop = RMSprop(lr=lr, rho=0.9, epsilon=1e-06)
                self.rnnModel.compile(loss='categorical_crossentropy', optimizer=rmsprop)