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