I see! I will try!
But, are you suggesting placing these nn.ConvTranspose2d layers on the model during the training step?
I ask this, because the architecture would be different from the one in the article if I do this.
Would I use it only in the test step? In the test step I would submit grayscale image to the trained model and it would return the 313x64x64 feature maps.
After obtaining the feature maps, would I use the nn.ConvTranspose2d layers to enlarge the image? The problem with this is that the weights present in this layer nn.ConvTranspose2d would not be trained right?