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| import torch | |
| class AverageMeter(object): | |
| """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 | |
| def accuracy(output, target): | |
| """Computes the Top-1 accuracy for a single prediction""" | |
| with torch.no_grad(): | |
| pred = output.argmax(dim=1) # Get the highest scoring class | |
| correct = pred.eq(target).sum().item() # Compare with the actual target | |
| return correct * 100.0 # Convert to percentage | |