def get_data_loader(self, dataset, sampler):
pad_collate = PadCollate(dim=-1, sp_dim=-2, sp_item_idx=[
3, 8, 12, 14
]) # nwp_index, spt_tgt need special padding
data_loader = DataLoader(dataset,
sampler=sampler,
batch_size=self.batch_size,
collate_fn=pad_collate)
return data_loader
def get_data_loader(self, features):
dataset = FewShotDataset([self.unpack_feature(f) for f in features])
if self.opt.local_rank == -1:
sampler = SequentialSampler(dataset)
else:
sampler = DistributedSampler(dataset)
pad_collate = PadCollate(dim=-1, sp_dim=-2, sp_item_idx=[3, 8, 12]) # nwp_index, spt_tgt need special padding
data_loader = DataLoader(dataset, sampler=sampler, batch_size=self.batch_size, collate_fn=pad_collate)
return data_loader
def get_data_loader(self, dataset, sampler):
""" add label index into special padding """
pad_collate = PadCollate(dim=-1, sp_dim=-2, sp_item_idx=[3, 9, 14, 16, 20, 25]) # nwp_index, spt_tgt need sp-padding
data_loader = DataLoader(dataset, sampler=sampler, batch_size=self.batch_size, collate_fn=pad_collate)
return data_loader