【问题标题】：Conv Autoencoder layer progressionConv Autoencoder 层级数
【发布时间】：2020-10-10 12:08:52
【问题描述】：

我想建立一个简单的卷积自动编码器：

层（类型）输出形状参数#

输入(InputLayer) (None, 64, 64, 1) 0

encoder_conv_1 (Conv2D) (None, 64, 64, 32) 320

max_pooling2d_1 (MaxPooling2 (None, 32, 32, 32) 0

decoder_conv_1 (Conv2D) (None, 30, 30, 32) 9248

up_sampling2d_1 (UpSampling2 (None, 60, 60, 32) 0

输出（Conv2D）（无、60、60、1）289

为什么我的最后一层没有回到 64, 64 ,1？或者更确切地说，为什么decoder_conv_1层会到30、30、32？

【问题讨论】：

标签： python tensorflow keras conv-neural-network autoencoder

【解决方案1】：

你错过了同样的填充。试试这种方式...

inp = Input((64,64,1))
c = Conv2D(32, 3, padding='same')(inp)
c = MaxPool2D()(c)
c = Conv2D(32, 3, padding='same')(c) # <=== padding same
c = UpSampling2D()(c)
out = Conv2D(1, 3, padding='same')(c)

m = Model(inp, out)
m.summary()

_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_5 (InputLayer)         [(None, 64, 64, 1)]       0         
_________________________________________________________________
conv2d_8 (Conv2D)            (None, 64, 64, 32)        320       
_________________________________________________________________
max_pooling2d_3 (MaxPooling2 (None, 32, 32, 32)        0         
_________________________________________________________________
conv2d_9 (Conv2D)            (None, 32, 32, 32)        9248      
_________________________________________________________________
up_sampling2d_2 (UpSampling2 (None, 64, 64, 32)        0         
_________________________________________________________________
conv2d_10 (Conv2D)           (None, 64, 64, 1)         289       
=================================================================

【讨论】：

这解决了它。不知道为什么我在最后一层缺少填充属性。谢谢。