05f03b541a
* hf offline decorator for tests to workaround rate limits * fail quicker so we can see logs * try new cache name * limit files downloaded * phi mini predownload * offline decorator for phi tokenizer * handle meta llama 8b offline too * make sure to return fixtures if they are wrapped too * more fixes * more things offline * more offline things * fix the env var * fix the model name * handle gemma also * force reload of modules to recheck offline status * prefetch mistral too * use reset_sessions so hub picks up offline mode * more fixes * rename so it doesn't seem like a context manager * fix backoff * switch out tinyshakespeare dataset since it runs a py script to fetch data and doesn't work offline * include additional dataset * more fixes * more fixes * replace tiny shakespeaere dataset * skip some tests for now * use more robust check using snapshot download to determine if a dataset name is on the hub * typo for skip reason * use local_files_only * more fixtures * remove local only * use tiny shakespeare as pretrain dataset and streaming can't be offline even if precached * make sure fixtures aren't offline improve the offline reset try bumping version of datasets reorder reloading and setting prime a new cache run the tests now with fresh cache try with a static cache * now run all the ci again with hopefully a correct cache * skip wonky tests for now * skip wonky tests for now * handle offline mode for model card creation
66 lines
1.8 KiB
Python
66 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 utils import enable_hf_offline
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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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@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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