d95f630a7b7f88621bc4abb4ac92692647f03781,main.py,,validate,#,270

Before Change

    end = time.time()
    for i, (input, target) in enumerate(val_loader):
        target = target.cuda(async=True)
        input_var = torch.autograd.Variable(torch.cat(input,1).cuda(), volatile=True)
        target_var = torch.autograd.Variable(target, volatile=True)

        // compute output
        output = model(input_var)

After Change

    end = time.time()
    for i, (input, target) in enumerate(val_loader):
        target = target.to(device)
        input = torch.cat(input,1).to(device)

        // compute output
        output = model(input)
        flow2_EPE = args.div_flow*realEPE(output, target, sparse=args.sparse)

Instances