Source code for torchreid.metrics.accuracy

from __future__ import division, print_function, absolute_import


[docs]def accuracy(output, target, topk=(1, )): """Computes the accuracy over the k top predictions for the specified values of k. Args: output (torch.Tensor): prediction matrix with shape (batch_size, num_classes). target (torch.LongTensor): ground truth labels with shape (batch_size). topk (tuple, optional): accuracy at top-k will be computed. For example, topk=(1, 5) means accuracy at top-1 and top-5 will be computed. Returns: list: accuracy at top-k. Examples:: >>> from torchreid import metrics >>> metrics.accuracy(output, target) """ maxk = max(topk) batch_size = target.size(0) if isinstance(output, (tuple, list)): output = output[0] _, pred = output.topk(maxk, 1, True, True) pred = pred.t() correct = pred.eq(target.view(1, -1).expand_as(pred)) res = [] for k in topk: correct_k = correct[:k].view(-1).float().sum(0, keepdim=True) acc = correct_k.mul_(100.0 / batch_size) res.append(acc) return res