3-提前结束训练

一、核心类

class EarlyStopping:
    # YOLOv5 simple early stopper
    def __init__(self, patience=30):
        self.best_fitness = 0.0  # i.e. mAP
        self.best_epoch = 0
        self.patience = patience or float('inf')  # epochs to wait after fitness stops improving to stop
        self.possible_stop = False  # possible stop may occur next epoch

    def __call__(self, epoch, fitness):#fitness最佳参数，
        if fitness >= self.best_fitness:  # >= 0 to allow for early zero-fitness stage of training
            self.best_epoch = epoch
            self.best_fitness = fitness
        delta = epoch - self.best_epoch  # epochs without improvement 当前epoch与最优epoch的差值，大于patience则提前结束  重点
        self.possible_stop = delta >= (self.patience - 1)  # possible stop may occur next epoch
        stop = delta >= self.patience  # stop training if patience exceeded
        if stop:
            LOGGER.info(f'Stopping training early as no improvement observed in last {self.patience} epochs. '
                        f'Best results observed at epoch {self.best_epoch}, best model saved as best.pt.\n'
                        f'To update EarlyStopping(patience={self.patience}) pass a new patience value, '
                        f'i.e. `python train.py --patience 300` or use `--patience 0` to disable EarlyStopping.')
        return stop

二、创建对象
stopper, stop = EarlyStopping(patience=opt.patience), False

三、提前结束判断

...
    for epoch in range(start_epoch, epochs):  # epoch ------------------------------------------------------------------
        callbacks.run('on_train_epoch_start')
        model.train()
        .....
        #最佳参数判断
		fi = fitness(np.array(results).reshape(1, -1))  # weighted combination of [P, R, mAP@.5, mAP@.5-.95]
        stop = stopper(epoch=epoch, fitness=fi)  # early stop check
		....
		if stop:
            break  # must break all DDP ranks