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https://github.com/hiyouga/LLaMA-Factory.git
synced 2025-08-04 12:42:51 +08:00
fix ppo runtime error
Former-commit-id: cdb7f82869b07d9d5d31b7b2aaf6b033bd00e32e
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@ -61,7 +61,7 @@ def load_model(
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"""
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init_kwargs = _get_init_kwargs(model_args)
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config = AutoConfig.from_pretrained(model_args.model_name_or_path, **init_kwargs)
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patch_config(config, tokenizer, model_args, init_kwargs, is_trainable)
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patch_config(config, tokenizer, model_args,finetuning_args, init_kwargs, is_trainable)
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model = None
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if is_trainable and model_args.use_unsloth:
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@ -264,6 +264,7 @@ def patch_config(
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config: "PretrainedConfig",
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tokenizer: "PreTrainedTokenizer",
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model_args: "ModelArguments",
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finetuning_args: "FinetuningArguments",
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init_kwargs: Dict[str, Any],
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is_trainable: bool,
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) -> None:
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@ -288,7 +289,8 @@ def patch_config(
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if not is_deepspeed_zero3_enabled():
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init_kwargs["low_cpu_mem_usage"] = model_args.low_cpu_mem_usage
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if "device_map" not in init_kwargs: # quant models cannot use auto device map
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init_kwargs["device_map"] = model_args.device_map or {"": get_current_device()}
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if finetuning_args.stage not in ["ppo"]: #ppo stage should not set device map
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init_kwargs["device_map"] = model_args.device_map or {"": get_current_device()}
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def patch_model(
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