cf0c79d52e
* fix: update chat_template * fix: handle gemma3 showing a lot of no content for turn 0 * fix: remove unknown config from examples * fix: test * fix: temporary disable gemma2 test * fix: stop overwriting config.text_config unnecessarily * fix: handling of set cache to the text_config section * feat: add liger gemma support and bump liger to 0.5.5 * fix: add double use_cache setting * fix: add support for final_logit_softcap in CCE for gemma2/3 * fix: set use_cache before model load * feat: add missing layernorm override * fix: handle gemma3 rmsnorm * fix: use wrapper to pass dim as hidden_size * fix: change dim to positional * fix: patch with wrong mlp * chore: refactor use_cache handling * fix import issues * fix tests.e2e.utils import --------- Co-authored-by: Wing Lian <wing@axolotl.ai>
67 lines
1.8 KiB
Python
67 lines
1.8 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.prompt_strategies.dpo import load as load_dpo
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from axolotl.utils.data.rl import load_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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train_ds, _ = load_prepare_preference_datasets(cfg)
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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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