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- from __future__ import absolute_import
- from ..utils import to_torch
- def accuracy(output, target, topk=(1,)):
- output, target = to_torch(output), to_torch(target)
- maxk = max(topk)
- batch_size = target.size(0)
- _, pred = output.topk(maxk, 1, True, True)
- pred = pred.t()
- correct = pred.eq(target.view(1, -1).expand_as(pred))
- ret = []
- for k in topk:
- correct_k = correct[:k].view(-1).float().sum(dim=0, keepdim=True)
- ret.append(correct_k.mul_(1. / batch_size))
- return ret
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