| """Module for testing dataset sequence packing""" |
|
|
| import unittest |
| from pathlib import Path |
|
|
| from datasets import Dataset, load_dataset |
| from transformers import AutoTokenizer |
|
|
| from axolotl.datasets import ConstantLengthDataset, TokenizedPromptDataset |
| from axolotl.prompt_tokenizers import AlpacaPromptTokenizingStrategy |
| from axolotl.prompters import AlpacaPrompter |
|
|
|
|
| class TestPacking(unittest.TestCase): |
| """ |
| Test class for packing dataset sequences |
| """ |
|
|
| def setUp(self) -> None: |
| |
| self.tokenizer = AutoTokenizer.from_pretrained("huggyllama/llama-7b") |
| self.tokenizer.add_special_tokens( |
| { |
| "bos_token": "<s>", |
| "eos_token": "</s>", |
| "unk_token": "<unk>", |
| } |
| ) |
|
|
| def test_increments_attention(self): |
| prompter = AlpacaPrompter("chat") |
| strat = AlpacaPromptTokenizingStrategy( |
| prompter, |
| self.tokenizer, |
| False, |
| 2048, |
| ) |
| dateset = load_dataset( |
| "json", |
| data_files=str(Path(__file__).parent / "fixtures/alpaca/alpaca.json"), |
| )["train"] |
| dataset = Dataset.from_list(list(TokenizedPromptDataset(strat, dateset))) |
|
|
| constant_len_dataset = ConstantLengthDataset( |
| self.tokenizer, |
| [dataset], |
| seq_length=2048, |
| ) |
| packed_dataset = Dataset.from_list(list(constant_len_dataset)) |
| example = packed_dataset[0] |
| next_bos_index = ( |
| example["input_ids"][1:].index(self.tokenizer.bos_token_id) + 1 |
| ) |
|
|
| |
| assert example["input_ids"][0] == self.tokenizer.bos_token_id |
| assert example["attention_mask"][0] == 1 |
| assert example["position_ids"][0] == 0 |
| assert example["position_ids"][1] == 1 |
|
|
| |
| assert example["input_ids"][next_bos_index] == self.tokenizer.bos_token_id |
| assert example["attention_mask"][next_bos_index] == 2 |
| assert example["position_ids"][next_bos_index] == 0 |
| assert example["position_ids"][next_bos_index + 1] == 1 |
|
|
|
|
| if __name__ == "__main__": |
| unittest.main() |
|
|