Well not exactly, just time series frames. I know this is asking a lot, I’m pretty new at this, but I have one more question. my current system is working by inputting 64 X 8 X 95 X 95, but I’m getting the error that input and target shapes do not match 256 X 8 X 64 X 64 being the target size.
That is the encoder to my network up top. The decoder looks similar but opposite. Like so:
self.decoder = nn.Sequential(
        nn.Linear(z_dim, 256),               # B, 256
        View((-1, 256, 1, 1)),               # B, 256,  1,  1
        nn.ReLU(True),
        nn.ConvTranspose2d(256, 64, 4),      # B,  64,  4,  4
        nn.ReLU(True),
        nn.ConvTranspose2d(64, 64, 4, 2, 1), # B,  64,  8,  8
        nn.ReLU(True),
        nn.ConvTranspose2d(64, 32, 4, 2, 1), # B,  32, 16, 16
        nn.ReLU(True),
        nn.ConvTranspose2d(32, 32, 4, 2, 1), # B,  32, 32, 32
        nn.ReLU(True),
        nn.ConvTranspose2d(32, nc, 4, 2, 1),  # B, nc, 64, 64
    )

Is there anyway you could explain to me why the output reconstruction loss is being given to me in that dimension? Thanks in advance.