ubteacher/engine/trainer.py [182:220]:
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    @classmethod
    def build_test_loader(cls, cfg, dataset_name):
        """
        Returns:
            iterable
        """
        return build_detection_test_loader(cfg, dataset_name)

    def build_hooks(self):
        """
        Build a list of default hooks, including timing, evaluation,
        checkpointing, lr scheduling, precise BN, writing events.

        Returns:
            list[HookBase]:
        """
        cfg = self.cfg.clone()
        cfg.defrost()
        cfg.DATALOADER.NUM_WORKERS = 0

        ret = [
            hooks.IterationTimer(),
            hooks.LRScheduler(self.optimizer, self.scheduler),
            hooks.PreciseBN(
                cfg.TEST.EVAL_PERIOD,
                self.model,
                self.build_train_loader(cfg),
                cfg.TEST.PRECISE_BN.NUM_ITER,
            )
            if cfg.TEST.PRECISE_BN.ENABLED and get_bn_modules(self.model)
            else None,
        ]

        if comm.is_main_process():
            ret.append(
                hooks.PeriodicCheckpointer(
                    self.checkpointer, cfg.SOLVER.CHECKPOINT_PERIOD
                )
            )
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ubteacher/engine/trainer.py [663:696]:
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    @classmethod
    def build_test_loader(cls, cfg, dataset_name):
        return build_detection_test_loader(cfg, dataset_name)

    def build_hooks(self):
        cfg = self.cfg.clone()
        cfg.defrost()
        cfg.DATALOADER.NUM_WORKERS = 0  # save some memory and time for PreciseBN

        ret = [
            hooks.IterationTimer(),
            hooks.LRScheduler(self.optimizer, self.scheduler),
            hooks.PreciseBN(
                # Run at the same freq as (but before) evaluation.
                cfg.TEST.EVAL_PERIOD,
                self.model,
                # Build a new data loader to not affect training
                self.build_train_loader(cfg),
                cfg.TEST.PRECISE_BN.NUM_ITER,
            )
            if cfg.TEST.PRECISE_BN.ENABLED and get_bn_modules(self.model)
            else None,
        ]

        # Do PreciseBN before checkpointer, because it updates the model and need to
        # be saved by checkpointer.
        # This is not always the best: if checkpointing has a different frequency,
        # some checkpoints may have more precise statistics than others.
        if comm.is_main_process():
            ret.append(
                hooks.PeriodicCheckpointer(
                    self.checkpointer, cfg.SOLVER.CHECKPOINT_PERIOD
                )
            )
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