LSTM调参感悟

train -= np.mean(train, axis = 0) # zero-center train /= np.std(train, axis = 0) # normalize test -= np.mean(test,axis=0) test /= np.std(test,axis=0)

def init_weight(self):           for name, param in self.lstm.named_parameters():               if 'bias' in name:                      nn.init.constant(param, 0.0)                      print('\nbias init done')               elif 'weight' in name:                      nn.init.orthogonal(param)                        print('\nweight init done')

5.learning_rate一般取0.001

文章来源: LSTM调参感悟