pytorch函数详解之AverageMeter

源码：
class AverageMeter(object):
    """Computes and stores the average and current value"""
    def __init__(self, name, fmt=':f'):
        self.name = name
        self.fmt = fmt
        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 __str__(self):
        fmtstr = '{name} {val' + self.fmt + '} ({avg' + self.fmt + '})'
        return fmtstr.format(**self.__dict__)

if __name__ == "__main__":
    losses = AverageMeter('AverageMeter')
    loss_list = [0.5,0.4,0.5,0.6,1]
    batch_size = 2
    for los in loss_list:
        losses.update(los,batch_size)
        print(losses.avg)
    print(losses)

总结：本质上还是对所有batch_size的损失取平均，batch_size会在计算中被消除，并没有啥用

reference:https://blog.csdn.net/qq_39783265/article/details/105398427