I’m trying to deconvolute a 3d image. I want the z-axis to remain the same while increasing the x,y image dimensions by a multiple of 2, so effectively just doubling the size.
When I am normally convolving and compressing an 8x96x96 (batch of 64 images) like so:
nn.Conv3d(nc, 32, 3, (1,2,2), 1)
nn.Conv3d(32, 32, 3, (1,2,2), 1)

I get a tensors of sizes (respectively):

torch.Size([64, 32, 8, 48, 48])
torch.Size([64, 32, 8, 24, 24])

When I deconvolute the compressed version of this which has a size of 1X3X3, like so:
nn.ConvTranspose3d(256, 64, 3, 2, padding=1, output_padding=1)   
nn.ConvTranspose3d(64, 64, 3, 2, padding=1, output_padding=1)

I get tensors of sizes (respectively):

torch.Size([64, 64, 2, 6, 6])
torch.Size([64, 64, 4, 12, 12])


However, and this is where I’m stuck. When I want to keep my z-axis constant while still increasing the stride of the y and x by 2 in my deconvolution I’m stuck. I’m trying this like so:
nn.ConvTranspose3d(32, 32, 3, (1,2,2), padding=1, output_padding=1),

When I try this, I’m getting the error in the title. Is there a way I can decompress my y and x dimension while keeping the z dimension constant? (preferably using stride and not a pooling layer)