Hi,
I’m getting the following error.
RuntimeError: Calculated padded input size per channel: (1017 x 1). 
Kernel size: (3 x 3). 
Kernel size can't greater than actual input size at /opt/conda/conda-bld/pytorch_1524584710464/work/aten/src/THNN/generic/SpatialConvolutionMM.c:48

My input tensor has size [1,1,1025,15]
Following is my Network:
MeeAutoEncoder(
  (encoder): MeeEncoder(
    (en_layer1): Conv2d(1, 12, kernel_size=(3, 3), stride=(1, 1))
    (en_layer2): MaxPool2d(kernel_size=(3, 5), stride=1, padding=0, dilation=1, ceil_mode=False)
    (en_layer3): Conv2d(12, 20, kernel_size=(3, 3), stride=(1, 1))
    (en_layer4): MaxPool2d(kernel_size=(1, 5), stride=1, padding=0, dilation=1, ceil_mode=False)
    (en_layer5): Conv2d(20, 30, kernel_size=(3, 3), stride=(1, 1))
    (en_layer6): Conv2d(30, 40, kernel_size=(3, 3), stride=(1, 1))
    (en_layerReLU): ReLU()
    (encoder): Sequential(
      (0): Conv2d(1, 12, kernel_size=(3, 3), stride=(1, 1))
      (1): ReLU()
      (2): MaxPool2d(kernel_size=(3, 5), stride=1, padding=0, dilation=1, ceil_mode=False)
      (3): Conv2d(12, 20, kernel_size=(3, 3), stride=(1, 1))
      (4): ReLU()
      (5): MaxPool2d(kernel_size=(1, 5), stride=1, padding=0, dilation=1, ceil_mode=False)
      (6): Conv2d(20, 30, kernel_size=(3, 3), stride=(1, 1))
      (7): ReLU()
      (8): Conv2d(30, 40, kernel_size=(3, 3), stride=(1, 1))
    )
  )
  (decoder): MeeDecoder(
    (de_layer1): Conv2d(40, 30, kernel_size=(3, 3), stride=(1, 1))
    (de_layer2): Conv2d(30, 20, kernel_size=(3, 3), stride=(1, 1))
    (de_layer3): Upsample(size=(5, 205), mode=bilinear)
    (de_layer4): Conv2d(20, 12, kernel_size=(3, 3), stride=(1, 1))
    (de_layer5): Upsample(size=(15, 1025), mode=bilinear)
    (de_layer6): Conv2d(12, 1, kernel_size=(3, 3), stride=(1, 1))
    (de_layerReLU): ReLU()
    (decoder): Sequential(
      (0): Conv2d(40, 30, kernel_size=(3, 3), stride=(1, 1))
      (1): ReLU()
      (2): Conv2d(30, 20, kernel_size=(3, 3), stride=(1, 1))
      (3): ReLU()
      (4): Upsample(size=(5, 205), mode=bilinear)
      (5): Conv2d(20, 12, kernel_size=(3, 3), stride=(1, 1))
      (6): ReLU()
      (7): Upsample(size=(15, 1025), mode=bilinear)
      (8): Conv2d(12, 1, kernel_size=(3, 3), stride=(1, 1))
      (9): ReLU()
    )
  )
)