| class AverageMeter: | |
| def __init__(self): | |
| self.reset() | |
| def reset(self): | |
| self.val = 0 | |
| self.avg = 0 | |
| self.sum = 0 | |
| self.count = 0 | |
| def update(self, val, n=1): | |
| self.val = val | |
| self.sum += val * n | |
| self.count += n | |
| self.avg = self.sum / self.count | |
| def calc_cls_accuracy(output, target, topk=(1,)): | |
| maxk = min(max(topk), output.size()[1]) | |
| batch_size = target.size(0) | |
| _, pred = output.topk(maxk, 1, True, True) | |
| pred = pred.t() | |
| correct = pred.eq(target.reshape(1, -1).expand_as(pred)) | |
| return [ | |
| correct[: min(k, maxk)].reshape(-1).float().sum(0) * 100.0 / batch_size | |
| for k in topk | |
| ] | |