    def _build_dataloader(self):
        """Build dataloader which merges a series of datasets."""
        # Build dataset instance for each dataset and combine them by ConcatDataset
        Dataset, Collator = self._build_dataset()

        # Build train set
        datasets_list = []
        for dataset in self.cfg.dataset:
            subdataset = Dataset(self.cfg, dataset, is_valid=False)
            datasets_list.append(subdataset)
        train_dataset = ConcatDataset(datasets_list)
        train_collate = Collator(self.cfg)
        _, batch_sampler = build_samplers(train_dataset, self.cfg, self.logger, "train")
        train_loader = DataLoader(
            train_dataset,
            collate_fn=train_collate,
            batch_sampler=batch_sampler,
            num_workers=self.cfg.train.dataloader.num_worker,
            pin_memory=self.cfg.train.dataloader.pin_memory,
        )

        # Build test set
        datasets_list = []
        for dataset in self.cfg.dataset:
            subdataset = Dataset(self.cfg, dataset, is_valid=True)
            datasets_list.append(subdataset)
        valid_dataset = ConcatDataset(datasets_list)
        valid_collate = Collator(self.cfg)
        _, batch_sampler = build_samplers(valid_dataset, self.cfg, self.logger, "valid")
        valid_loader = DataLoader(
            valid_dataset,
            collate_fn=valid_collate,
            batch_sampler=batch_sampler,
            num_workers=self.cfg.train.dataloader.num_worker,
            pin_memory=self.cfg.train.dataloader.pin_memory,
        )
        return train_loader, valid_loader
Build dataloader which merges a series of datasets.
models/tts/base/tts_trainer.py