Solved by ptrblck in post #2 
              
              
                Internally the output array will be created via: 
ndarr = grid.mul(255).add_(0.5).clamp_(0, 255).permute(1, 2, 0).to('cpu', torch.uint8).numpy()

so you don’t need to multiply your predictions with 255 and can pass it as a float tensor. 
The error is thrown at the .add_(0.5) step. 
The documentation…