losses = AverageMeter()
时间: 2024-05-21 12:16:58 浏览: 14
`AverageMeter()` is a class used to keep track of the average value of some variable over multiple iterations during training. It has two main methods:
1. `update(val, n=1)`: This method is called at each iteration with the value of the variable being tracked and the number of samples seen in that iteration. It updates the running average and the total number of samples seen so far.
2. `avg`: This method returns the current average value of the variable being tracked.
For example, if we are tracking the loss during training, we can create an `AverageMeter()` object called `losses` and call `losses.update(loss)` at each iteration with the current loss value. Then, we can log the average loss so far by calling `losses.avg`.
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