87b7e56093996e908d310ccd852e7df0a88f2f19,example/main.py,,train,#Any#Any#Any#Any#Any#Any#,164

Before Change

        output = model(input)
        if type(output) == list:  // multiple output

            loss = criterion(output[0], target)
            for j in range(1, len(output)):
                loss += criterion(output[j], target)
            output = output[0]
        else:  // single output
            loss = criterion(output, target)
        acc = accuracy(output, target, idx)

After Change

        data_time.update(time.time() - end)

        input, target = input.to(device), target.to(device, non_blocking=True)
        target_weight = meta["target_weight"].to(device, non_blocking=True)

        // compute output
        output = model(input)
        if type(output) == list:  // multiple output
            loss = 0
            for o in output:
                loss += criterion(o, target, target_weight)
            output = output[-1]
        else:  // single output
            loss = criterion(output, target, target_weight)
        acc = accuracy(output, target, idx)

Instances