Hi all,
Thank you very much for this repo. Here I have a question. In op.py line 178 FactorizedReduce function, why conv2 layer need to reduce size on dim=2 and 3? In my case this cause dimension mismatch.
out = torch.cat([self.conv1(x), self.conv2(x[:, :, 1:, 1:])], dim=1)
Hi all, Thank you very much for this repo. Here I have a question. In op.py line 178 FactorizedReduce function, why conv2 layer need to reduce size on dim=2 and 3? In my case this cause dimension mismatch. out = torch.cat([self.conv1(x), self.conv2(x[:, :, 1:, 1:])], dim=1)