Here’s what I’m trying to do …
train_sampler = RandomSampler(train_ds) valid_sampler = SequentialSampler(valid_ds) collate_fn = partial(hft_sum_collate, tokenizer=hft_tokenizer, block_size=max_seq_len) dls = DataLoaders.from_dsets(train_ds, valid_ds, path=PATH, dl_type=SortedDL, batch_size=(bsz,bsz*2), sampler=(train_sampler, valid_sampler), #???? create_batch=collate_fn)
I’m not sure how to pass the samplers in … or even if we can in v2. Either way, what is the v2 approach?
Also, is there a way to specify a different
dl_type for the training vs. the validation dataloader here?