Keras卷積自動編碼器不工作

我從Keras筆者就在這裏測試的卷積的自動編碼： https://blog.keras.io/building-autoencoders-in-keras.html Keras卷積自動編碼器不工作

但我有這樣的問題：

Exception: Error when checking model target: expected convolution2d_7 to have shape (None, 8, 32, 1) but got array with shape (60000, 1, 28, 28)

我準確的，我已經設置好的最後一個conv層中的字段'border_mode ='same''。所以，我真的不從那裏來，從知道.. 以下是摘要：

Layer (type)      Output Shape   Param #   Connected to      
     ==================================================================================================== 
input_1 (InputLayer)    (None, 1, 28, 28)  0            
____________________________________________________________________________________________________ 
convolution2d_1 (Convolution2D) (None, 1, 28, 16)  4048  input_1[0][0]      
____________________________________________________________________________________________________ 
maxpooling2d_1 (MaxPooling2D) (None, 1, 14, 16)  0   convolution2d_1[0][0]    
     ______________________________________________________________________________ ______________________ 
convolution2d_2 (Convolution2D) (None, 1, 14, 8)  1160  maxpooling2d_1[0][0]    
____________________________________________________________________________________________________ 
maxpooling2d_2 (MaxPooling2D) (None, 1, 7, 8)  0   convolution2d_2[0][0]    
____________________________________________________________________________________________________ 
convolution2d_3 (Convolution2D) (None, 1, 7, 8)  584   maxpooling2d_2[0][0]    
____________________________________________________________________________________________________ 
maxpooling2d_3 (MaxPooling2D) (None, 1, 4, 8)  0   convolution2d_3[0][0]    
____________________________________________________________________________________________________ 
convolution2d_4 (Convolution2D) (None, 1, 4, 8)  584   maxpooling2d_3[0][0]    
____________________________________________________________________________________________________ 
upsampling2d_1 (UpSampling2D) (None, 2, 8, 8)  0   convolution2d_4[0][0]    
____________________________________________________________________________________________________ 
convolution2d_5 (Convolution2D) (None, 2, 8, 8)  584   upsampling2d_1[0][0]    
____________________________________________________________________________________________________ 
upsampling2d_2 (UpSampling2D) (None, 4, 16, 8)  0   convolution2d_5[0][0]    
____________________________________________________________________________________________________ 
convolution2d_6 (Convolution2D) (None, 4, 16, 16)  1168  upsampling2d_2[0][0]    
____________________________________________________________________________________________________ 
upsampling2d_3 (UpSampling2D) (None, 8, 32, 16)  0   convolution2d_6[0][0]    
______________________________________________________________________________ ______________________ 

convolution2d_7 (Convolution2D) (None, 8, 32, 1)  145    

upsampling2d_3[0][0]    
==================================================================================================== 
Total params: 8273 
____________________________________________________________________________________________________

來源

2016-12-27 Pusheen_the_dev

此問題可能是以下情況的重複：http://stackoverflow.com/questions/39848466/tensorflow-keras-convolution2d-valueerror-filter-must-not-be-larger-than-t?noredirect=1#comment67013494_39848466 –

嗨，我看到這個線程，的確，dim_ordering需要更改爲theano dim。（1，x，x）但是，問題保持不變，現在，網絡期望（1,28,28），但得到（1,32,32）我明白這是因爲最後一個upsampling層，但是最後一個帶3x3大小過濾器的conv應該安排不？ –

終於找到了答案。我認爲本教程的創建者使用32x32 MNIST圖像而不是28x28進行了測試。

因爲，當添加到最後一個conv layer border_mode ='same'時，您將得到一個輸出形狀（32,32,1）因此，要獲得良好的輸出（28,28,1），您需要將border_mode ='valid'添加到前一個conv層。

總結：將尺寸排序更正爲28x28x1而不是1x28x28。然後將邊框模式添加到最後一個conv層最後添加對最後一個conv層有效的邊框模式。

希望這會有所幫助。

來源

2016-12-27 15:54:41

Keras卷積自動編碼器不工作

回答

相關問題