utils.py

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