Edit your encoding layers to include a padding in the following way:
class AutoEncoderConv(nn.Module):
    def __init__(self):
        super(AutoEncoderConv, self).__init__()

        self.encoder = nn.Sequential(

            nn.Conv2d(1, 32, kernel_size=3, padding=1),
            nn.ReLU(True),
            nn.MaxPool2d(2),

            nn.Conv2d(32, 32, kernel_size=3, padding=1),
            nn.ReLU(True),
            nn.MaxPool2d(2),

            nn.Conv2d(32, 32, kernel_size=3, padding=1),
            nn.ReLU(True),
            nn.MaxPool2d(2),

            nn.Conv2d(32, 32, kernel_size=3, padding=1),
            nn.ReLU(True),
            nn.MaxPool2d(2),

            nn.Conv2d(32, 32, kernel_size=3, padding=1),
            nn.ReLU(True),
            nn.MaxPool2d(2)
        )

Using torchsummary package, I get even shapes:
----------------------------------------------------------------
        Layer (type)               Output Shape         Param #
================================================================
            Conv2d-1         [-1, 32, 512, 512]             320
              ReLU-2         [-1, 32, 512, 512]               0
         MaxPool2d-3         [-1, 32, 256, 256]               0
            Conv2d-4         [-1, 32, 256, 256]           9,248
              ReLU-5         [-1, 32, 256, 256]               0
         MaxPool2d-6         [-1, 32, 128, 128]               0
            Conv2d-7         [-1, 32, 128, 128]           9,248
              ReLU-8         [-1, 32, 128, 128]               0
         MaxPool2d-9           [-1, 32, 64, 64]               0
           Conv2d-10           [-1, 32, 64, 64]           9,248
             ReLU-11           [-1, 32, 64, 64]               0
        MaxPool2d-12           [-1, 32, 32, 32]               0
           Conv2d-13           [-1, 32, 32, 32]           9,248
             ReLU-14           [-1, 32, 32, 32]               0
        MaxPool2d-15           [-1, 32, 16, 16]               0
================================================================