references/classification/utils.py
def accuracy(output, target, topk=(1,)):
    """Computes the accuracy over the k top predictions for the specified values of k"""
    with torch.no_grad():
        maxk = max(topk)
        batch_size = target.size(0)

        _, pred = output.topk(maxk, 1, True, True)
        pred = pred.t()
        correct = pred.eq(target[None])

        res = []
        for k in topk:
            correct_k = correct[:k].flatten().sum(dtype=torch.float32)
            res.append(correct_k * (100.0 / batch_size))
        return res
def accuracy(output, target, topk=(1,)):
    """Computes the accuracy over the k top predictions for the specified values of k"""
    with torch.no_grad():
        maxk = max(topk)
        batch_size = target.size(0)

        _, pred = output.topk(maxk, 1, True, True)
        pred = pred.t()
        correct = pred.eq(target[None])

        res = []
        for k in topk:
            correct_k = correct[:k].flatten().sum(dtype=torch.float32)
            res.append(correct_k * (100.0 / batch_size))
        return res
Computes the accuracy over the k top predictions for the specified values of k