00cda8cc70
* data loading refactor (wip) * updates * progress * pytest * pytest fix * lint * zero_first -> filelock, more simplifications * small simplification * import change * nit * lint * simplify dedup * couldnt resist * review comments WIP * continued wip * minor changes * fix; remove contrived test * further refactor * set default seed in pydantic config * lint * continued simplication * lint * renaming and nits * filelock tests * fix * fix * lint * remove nullable arg * remove unnecessary code * moving dataset save fn to shared module * remove debug print * matching var naming * fn name change * coderabbit comments * naming nit * fix test
69 lines
1.9 KiB
Python
69 lines
1.9 KiB
Python
"""
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Tests for loading DPO preference datasets with chatml formatting
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"""
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import unittest
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import pytest
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from axolotl.loaders.tokenizer import load_tokenizer
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from axolotl.prompt_strategies.dpo import load as load_dpo
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from axolotl.utils.data.rl import prepare_preference_datasets
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from axolotl.utils.dict import DictDefault
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from tests.hf_offline_utils import enable_hf_offline
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@pytest.fixture(name="minimal_dpo_cfg")
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def fixture_cfg():
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return DictDefault(
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{
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"base_model": "HuggingFaceTB/SmolLM2-135M",
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"tokenizer_config": "HuggingFaceTB/SmolLM2-135M",
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"rl": "dpo",
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"learning_rate": 0.000001,
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"micro_batch_size": 1,
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"gradient_accumulation_steps": 1,
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"special_tokens": {
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"pad_token": "<|endoftext|>",
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},
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"sequence_len": 2048,
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}
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)
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class TestDPOChatml:
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"""
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Test loading DPO preference datasets with chatml formatting
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"""
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@pytest.mark.skip(reason="TODO: fix hf hub offline to work with HF rate limits")
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@enable_hf_offline
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def test_default(self, minimal_dpo_cfg):
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cfg = DictDefault(
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{
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"datasets": [
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{
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"path": "argilla/distilabel-intel-orca-dpo-pairs",
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"type": "chatml",
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"split": "train[:1%]",
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}
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]
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}
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| minimal_dpo_cfg
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)
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# test that dpo.load works
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load_dpo("chatml", cfg)
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# now actually load the datasets with the strategy
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tokenizer = load_tokenizer(cfg)
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train_ds, _ = prepare_preference_datasets(cfg, tokenizer)
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assert train_ds[0]["prompt"].startswith("<|im_start|>")
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assert train_ds[0]["prompt"].endswith("<|im_start|>assistant\n")
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assert "chosen" in train_ds[0]
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assert "rejected" in train_ds[0]
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if __name__ == "__main__":
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unittest.main()
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