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deduplicate code

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This commit is contained in:
Wing Lian
2023-08-22 23:17:44 -04:00
parent f20c8deff1
commit 53e739f11e
1 changed files with 16 additions and 23 deletions
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39
scripts/finetune.py
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@@ -155,6 +155,20 @@ def check_not_in(list1: List[str], list2: Union[Dict[str, Any], List[str]]) -> b
return not any(el in list2 for el in list1) return not any(el in list2 for el in list1)
def merge_lora(model, tokenizer, cfg):
LOG.info("running merge of LoRA with base model")
model = model.merge_and_unload()
model.to(dtype=torch.float16)
if cfg.local_rank == 0:
LOG.info("saving merged model")
model.save_pretrained(
str(Path(cfg.output_dir) / "merged"),
safe_serialization=cfg.save_safetensors is True,
)
tokenizer.save_pretrained(str(Path(cfg.output_dir) / "merged"))
def train( def train(
config: Path = Path("configs/"), config: Path = Path("configs/"),
prepare_ds_only: bool = False, prepare_ds_only: bool = False,
@@ -214,17 +228,7 @@ def train(
safe_serialization = cfg.save_safetensors is True safe_serialization = cfg.save_safetensors is True
if "merge_lora" in kwargs and cfg.adapter is not None: if "merge_lora" in kwargs and cfg.adapter is not None:
LOG.info("running merge of LoRA with base model") merge_lora(model, tokenizer, cfg)
model = model.merge_and_unload()
model.to(dtype=torch.float16)
if cfg.local_rank == 0:
LOG.info("saving merged model")
model.save_pretrained(
str(Path(cfg.output_dir) / "merged"),
safe_serialization=safe_serialization,
)
tokenizer.save_pretrained(str(Path(cfg.output_dir) / "merged"))
return return
if cfg.inference: if cfg.inference:
@@ -311,18 +315,7 @@ def train(
model.save_pretrained(cfg.output_dir, safe_serialization=safe_serialization) model.save_pretrained(cfg.output_dir, safe_serialization=safe_serialization)
if cfg.adapter is not None: if cfg.adapter is not None:
# pylint: disable=duplicate-code merge_lora(model, tokenizer, cfg)
LOG.info("running merge of LoRA with base model")
model = model.merge_and_unload()
model.to(dtype=torch.float16)
if cfg.local_rank == 0:
LOG.info("saving merged model")
model.save_pretrained(
str(Path(cfg.output_dir) / "merged"),
safe_serialization=safe_serialization,
)
tokenizer.save_pretrained(str(Path(cfg.output_dir) / "merged"))
if __name__ == "__main__": if __name__ == "__main__":