same here,
OS: Win10
python: 3.8.1
torch: 1.4.0
CUDA: 10.1
though, I fixed the problem, by implementing the cat use case that I had.
in my case, this function solved my problem.
this function takes 4 arrays of 4D tensors, and concats them based on dim=1.
this is hardcoded though.
    def cat(arr, device):
        total_depth = 0
        for x in arr:
            total_depth += x.size()[1]
        num_samples = arr[0].size()[0]
        h = arr[0].size()[2]
        w = arr[0].size()[3]
        
        concated = torch.zeros((num_samples, total_depth, h, w), device=device)
        
        last = 0
        concated[:, :arr[0].size()[1], :, :] = arr[0]
        last = arr[0].size()[1]
        concated[:, last:last + arr[1].size()[1], :, :] = arr[1]
        last = last + arr[1].size()[1]
        concated[:, last:last + arr[2].size()[1], :, :] = arr[2]
        last = last + arr[2].size()[1]
        concated[:, last:, :, :] = arr[3]
        
        return concated