CLI cleanup and documentation (#2244)
* CLI init refactor * fix * cleanup and (partial) docs * Adding documentation and continuing cleanup (in progress) * remove finetune.py script * continued cleanup and documentation * pytest fixes * review comments * fix * Fix * typing fixes * make sure the batch dataset patcher for multipack is always loaded when handling datasets * review comments * fix --------- Co-authored-by: Dan Saunders <dan@axolotl.ai> Co-authored-by: Wing Lian <wing@axolotl.ai>
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"""Prepare and train a model on a dataset. Can also infer from a model or merge lora"""
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import logging
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from pathlib import Path
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import fire
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import transformers
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from axolotl.cli import (
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check_accelerate_default_config,
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check_user_token,
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do_inference,
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do_merge_lora,
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load_cfg,
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load_datasets,
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print_axolotl_text_art,
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)
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from axolotl.cli.shard import shard
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from axolotl.common.cli import TrainerCliArgs
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from axolotl.train import train
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LOG = logging.getLogger("axolotl.scripts.finetune")
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def do_cli(config: Path = Path("examples/"), **kwargs):
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print_axolotl_text_art()
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LOG.warning(
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str(
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PendingDeprecationWarning(
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"scripts/finetune.py will be replaced with calling axolotl.cli.train"
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)
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)
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)
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parsed_cfg = load_cfg(config, **kwargs)
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check_accelerate_default_config()
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check_user_token()
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parser = transformers.HfArgumentParser((TrainerCliArgs))
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parsed_cli_args, _ = parser.parse_args_into_dataclasses(
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return_remaining_strings=True
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)
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if parsed_cli_args.inference:
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do_inference(cfg=parsed_cfg, cli_args=parsed_cli_args)
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elif parsed_cli_args.merge_lora:
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do_merge_lora(cfg=parsed_cfg, cli_args=parsed_cli_args)
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elif parsed_cli_args.shard:
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shard(cfg=parsed_cfg, cli_args=parsed_cli_args)
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else:
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dataset_meta = load_datasets(cfg=parsed_cfg, cli_args=parsed_cli_args)
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train(cfg=parsed_cfg, cli_args=parsed_cli_args, dataset_meta=dataset_meta)
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if __name__ == "__main__":
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fire.Fire(do_cli)
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