| from __future__ import annotations |
|
|
| import numpy as np |
| import torch |
|
|
| from kawk50m.chat import build_assistant_examples, format_generation_prompt, parse_chatml |
| from kawk50m.sft_dataset import SFTPackedDataset |
|
|
|
|
| class CharacterTokenizer: |
| bos_token_id = 1 |
| eos_token_id = 2 |
|
|
| def __call__(self, text: str, **_: object) -> dict[str, list[int]]: |
| return {"input_ids": [10 + ord(character) % 200 for character in text]} |
|
|
|
|
| def test_chatml_examples_mask_only_current_assistant_response() -> None: |
| blocks = parse_chatml( |
| "<|im_start|>user\n질문입니다.<|im_end|>" |
| "<|im_start|>assistant\n답변입니다.<|im_end|>" |
| ) |
| examples = list( |
| build_assistant_examples(blocks, CharacterTokenizer(), max_length=128) |
| ) |
| assert len(examples) == 1 |
| input_ids, loss_mask = examples[0] |
| assert len(input_ids) == len(loss_mask) |
| assert loss_mask[-1] == 1 |
| assert input_ids[-1] == CharacterTokenizer.eos_token_id |
| assert 0 in loss_mask and 1 in loss_mask |
| assert format_generation_prompt("질문") .endswith("### 도우미:\n") |
|
|
|
|
| def test_sft_dataset_applies_ignore_index(tmp_path) -> None: |
| prefix = tmp_path / "train" |
| np.asarray([1, 10, 11, 2, 1, 20, 21, 2], dtype=np.uint16).tofile( |
| str(prefix) + ".input_ids.bin" |
| ) |
| np.asarray([0, 0, 1, 1, 0, 0, 1, 1], dtype=np.uint8).tofile( |
| str(prefix) + ".loss_mask.bin" |
| ) |
| dataset = SFTPackedDataset(prefix, sequence_length=4) |
| inputs, labels = dataset.evaluation_batch( |
| batch_index=0, |
| batch_size=1, |
| rank=0, |
| world_size=1, |
| device=torch.device("cpu"), |
| ) |
| assert inputs.tolist() == [[1, 10, 11, 2]] |
| assert labels.tolist() == [[-100, -100, 11, 2]] |
|
|
