|
|
|
|
|
from litgpt.data import LongForm |
|
|
from litgpt.prompts import Longform as LongFormPromptStyle |
|
|
|
|
|
|
|
|
def test_longform(mock_tokenizer, longform_path): |
|
|
longform = LongForm(download_dir=longform_path, num_workers=0) |
|
|
assert isinstance(longform.prompt_style, LongFormPromptStyle) |
|
|
longform.connect(mock_tokenizer, batch_size=2, max_seq_length=10) |
|
|
longform.prepare_data() |
|
|
longform.setup() |
|
|
|
|
|
train_dataloader = longform.train_dataloader() |
|
|
val_dataloader = longform.val_dataloader() |
|
|
|
|
|
assert len(train_dataloader) == 9 |
|
|
assert len(val_dataloader) == 5 |
|
|
|
|
|
train_batch = next(iter(train_dataloader)) |
|
|
val_batch = next(iter(val_dataloader)) |
|
|
|
|
|
assert train_batch.keys() == val_batch.keys() == {"input_ids", "labels", "token_counts"} |
|
|
for key in ["input_ids", "labels"]: |
|
|
assert train_batch[key].shape == (2, 10), f"Unexpected shape for train_batch[{key}]" |
|
|
assert val_batch[key].shape == (2, 10), f"Unexpected shape for val_batch[{key}]" |
|
|
|
|
|
assert isinstance(train_dataloader.dataset.prompt_style, LongFormPromptStyle) |
|
|
assert isinstance(val_dataloader.dataset.prompt_style, LongFormPromptStyle) |
|
|
|
|
|
|
|
|
assert longform.prepare_data_per_node |
|
|
|
