Hi,
I have been trying to use the CTCLoss function provided with warp_ctc module. I know this is not the right place to ask but help is really appreciated. (Also, is there any official CTC binder with pytorch now?)
            # Segment the image to one row!
            x = images[:, :, row:row+1, :]
            y = labels[:, row]

            # Target size is batch_sizexone
            target_sizes = torch.IntTensor(x.size(0)).zero_()
            target_sizes = Variable(target_sizes, requires_grad=False) + 1
            
            # sequence length is batch_size x 1
            sizes = Variable(torch.IntTensor(x.size(0)).zero_(), requires_grad=False) + 1

            # Forward + Backward + Optimize
            optimizer.zero_grad()
            outputs = model(x)
            print(outputs.size(), y.size(), sizes.size(), target_sizes.size())
            loss = criterion(outputs, y, sizes, target_sizes)

Now the output is:
torch.Size([20, 3]) torch.Size([20]) torch.Size([20]) torch.Size([20])
Variable containing:
0
[torch.FloatTensor of size 1]
torch.Size([20, 3]) torch.Size([20]) torch.Size([20]) torch.Size([20])
fish: ‘python3 train.py 2 --train_file ~…’ terminated by signal SIGSEGV (Address boundary error)
So, the first iteration went through properly but 2nd one got SIGSEGV. Sometimes it would get the same error during the first iteration. Anything I am doing wrong here?