b0a156d87b736d90c3e27933e8e4d0114bd5ef36,demo.py,,train_epoch,#,30

Before Change

            input_var = torch.autograd.Variable(input.cuda(async=True))
            target_var = torch.autograd.Variable(target.cuda(async=True))
        else:
            input_var = torch.autograd.Variable(input)
            target_var = torch.autograd.Variable(target)

        // compute output
        output = model(input_var)

After Change

        // Create vaiables
        if torch.cuda.is_available():
            input = input.cuda()
            target = target.cuda()

        // compute output
        output = model(input)
        loss = torch.nn.functional.cross_entropy(output, target)

Instances