Question

我正在尝试使用Keras用LSTM Autoencoder训练模型以重构我提供给模型的输入，并且在解码部分后得到的结果中出现NaN错误。这是我的代码；

    # lstm autoencoder recreate sequence
    from numpy import array
    import numpy as np
    from keras.models import Sequential
    from keras.layers import LSTM
    from keras.layers import Dense
    from keras.layers import RepeatVector
    from keras.layers import TimeDistributed
    from keras.utils import plot_model
    import pandas as pd

    df = pd.read_csv('flight_data.csv',sep=',',header=None)
    data = df.to_numpy()
    print(data.shape)


    # define input sequence
    sequence1 = array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
    sequence2 = array([0.2, 0.4, 0.6, 0.4, 1.0, 1.2, 1.4, 1.6, 1.8])
    # reshape input into [samples, timesteps, features]
    n_in = 100
    data = data[73666:,:]
    sequence = data.reshape((1,100,24))
    print(sequence)
    # define model
    model = Sequential()
    model.add(LSTM(100, activation='relu', input_shape=(n_in,24)))
    model.add(RepeatVector(n_in))
    model.add(LSTM(100, activation='relu', return_sequences=True))
    model.add(TimeDistributed(Dense(24)))
    model.compile(optimizer='adam', loss='mse')
    # fit model
    model.fit(sequence, sequence, epochs=300, verbose=0)
    plot_model(model, show_shapes=True, to_file='reconstruct_lstm_autoencoder.png')
    # demonstrate recreation
    yhat = model.predict(sequence, verbose=0)

    print(yhat)

我得到的输出为；

[[[9.46687355e+14 1.00000000e+01 4.42748822e+08 ... 0.00000000e+00
   0.00000000e+00 0.00000000e+00]
  [9.46687355e+14 1.00000000e+01 4.42748822e+08 ... 0.00000000e+00
   0.00000000e+00 0.00000000e+00]
  [9.46687355e+14 1.00000000e+01 4.42748823e+08 ... 0.00000000e+00
   0.00000000e+00 0.00000000e+00]
  ...
  [9.46687359e+14 1.00000000e+01 4.42748824e+08 ... 0.00000000e+00
   0.00000000e+00 0.00000000e+00]
  [9.46687359e+14 1.00000000e+01 4.42748824e+08 ... 0.00000000e+00
   0.00000000e+00 0.00000000e+00]
  [9.46687359e+14 1.00000000e+01 4.42748825e+08 ... 0.00000000e+00
   0.00000000e+00 0.00000000e+00]]]

[[[nan nan nan ... nan nan nan]
  [nan nan nan ... nan nan nan]
  [nan nan nan ... nan nan nan]
  ...
  [nan nan nan ... nan nan nan]
  [nan nan nan ... nan nan nan]
  [nan nan nan ... nan nan nan]]]

哪个部分可能引起问题？我该怎么办？

Answer 1

这看起来像您具有爆炸性的渐变，而LSTM倾向于创建这种渐变。剪切渐变可以解决此问题，请尝试将clipnorm设置为1。

ADAM = keras.optimizers.Adam(lr=0.001, beta_1=0.9, beta_2=0.999, epsilon=None, decay=0.0, amsgrad=False, clipnorm=1.)
model.compile(optimizer=ADAM, loss='mse')

使用LSTM自动编码器时出现NaN错误

1 个答案: