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Keras重塑输入LSTM

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我正在研究一个虚拟的例子,以了解LSTM如何使用Keras . 我正在重塑数据输入和输出的方式有问题 .

ValueError:输入0与图层重复不兼容:预期ndim = 3,找到ndim = 2

import random
import numpy as np

from keras.layers import Input, LSTM, Dense
from keras.layers.wrappers import TimeDistributed
from keras.models import Model

def gen_number():
    return np.random.choice([random.random(), 1], p=[0.2, 0.8])    
truth_input = [gen_number() for i in range(0,2000)]    
# shift input by one
truth_shifted = truth_input[1:] + [np.mean(truth_input)]      
truth = np.array(truth_input)
test_ouput = np.array(truth_shifted)        
truth_reshaped = truth.reshape(1, len(truth), 1)    
shifted_truth_reshaped = test_ouput.reshape(1, len(test_ouput), 1)  
yes = Input(shape=(len(truth_reshaped),), name = 'truth_in')    
recurrent = LSTM(20, return_sequences=True, name='recurrent')(yes)    
TimeDistributed_output = TimeDistributed(Dense(1), name='test_pseudo')(recurrent)    
model_built = Model(input=yes, output=TimeDistributed_output)    
model_built.compile(loss='mse', optimizer='adam')    
model_built.fit(truth_reshaped, shifted_truth_reshaped, nb_epoch=100)

如何才能正确输入数据?

1 回答

  • 1
    yes = Input(shape=(len(truth_reshaped),), name = 'truth_in')
    

    Len(truth_reshaped)将返回1,因为你将它塑造成(1,2000,1) . 这里第一个是序列数,2000是序列中的时间步数,第二个是序列中每个元素的值数 .

    所以你的输入应该是

    yes = Input(shape=(len(truth),1), name = 'truth_in')
    

    这将告诉您的网络输入将是长度为len的序列(真值,1),并且元素的维度为1 .

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