"""
Modified from https://github.com/rwightman/pytorch-image-models/blob/master/timm/utils/metrics.py
"""
[docs]class AverageMeter:
"""Computes and stores the average and current value"""
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
[docs]def accuracy(output, target, topk=(1,)):
"""Computes the accuracy over the k top predictions for the specified values of k"""
maxk = min(max(topk), output.size()[1])
batch_size = target.size(0)
_, pred = output.topk(maxk, 1, True, True)
# TODO: add tensor.t() method
pred = pred.transpose(-1, -2)
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
]