def train_dataloader(self): multi_dataloader = { task: torch.utils.data.DataLoader(task_dataset, batch_size=None, num_workers=self.hparams.num_workers, pin_memory=True) for task, task_dataset in distill_datasets.items() } res = MultiTaskDataloader(tau=self.hparams.tau, **multi_dataloader) return res
def train_dataloader(self): multi_dataloader = { task: torch.utils.data.DataLoader(task_dataset[datasets.Split.TRAIN], batch_size=self.hparams.batch_size, collate_fn=collate, num_workers=self.hparams.num_workers, pin_memory=True) for task, task_dataset in multi_dataset.items() } res = MultiTaskDataloader(tau=self.hparams.tau, **multi_dataloader) return res