bb8d79bae2
* ray init kwargs * Update trainer_utils.py * fix ray args --------- Co-authored-by: hoshi-hiyouga <hiyouga@buaa.edu.cn>
67 lines
2.4 KiB
Python
67 lines
2.4 KiB
Python
# Copyright 2025 the LlamaFactory team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import json
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from dataclasses import dataclass, field
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from typing import Literal, Optional, Union
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from transformers import Seq2SeqTrainingArguments
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from transformers.training_args import _convert_str_dict
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from ..extras.misc import use_ray
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@dataclass
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class RayArguments:
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r"""Arguments pertaining to the Ray training."""
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ray_run_name: Optional[str] = field(
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default=None,
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metadata={"help": "The training results will be saved at `<ray_storage_path>/ray_run_name`."},
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)
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ray_storage_path: str = field(
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default="./saves",
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metadata={"help": "The storage path to save training results to"},
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)
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ray_num_workers: int = field(
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default=1,
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metadata={"help": "The number of workers for Ray training. Default is 1 worker."},
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)
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resources_per_worker: Union[dict, str] = field(
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default_factory=lambda: {"GPU": 1},
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metadata={"help": "The resources per worker for Ray training. Default is to use 1 GPU per worker."},
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)
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placement_strategy: Literal["SPREAD", "PACK", "STRICT_SPREAD", "STRICT_PACK"] = field(
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default="PACK",
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metadata={"help": "The placement strategy for Ray training. Default is PACK."},
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)
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ray_init_kwargs: Optional[dict] = field(
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default=None,
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metadata={"help": "The arguments to pass to ray.init for Ray training. Default is None."},
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)
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def __post_init__(self):
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self.use_ray = use_ray()
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if isinstance(self.resources_per_worker, str) and self.resources_per_worker.startswith("{"):
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self.resources_per_worker = _convert_str_dict(json.loads(self.resources_per_worker))
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@dataclass
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class TrainingArguments(RayArguments, Seq2SeqTrainingArguments):
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r"""Arguments pertaining to the trainer."""
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def __post_init__(self):
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Seq2SeqTrainingArguments.__post_init__(self)
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RayArguments.__post_init__(self)
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