| | |
| | 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 |
| |
|
