[v1] add v1 launcher (#9236)

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
This commit is contained in:
Yaowei Zheng
2025-10-07 22:34:48 +08:00
committed by GitHub
parent 95b7188090
commit 10146029ba
26 changed files with 661 additions and 452 deletions

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# Copyright 2025 the LlamaFactory team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class DataArguments:
dataset: Optional[str] = field(
default=None,
metadata={"help": "Path to the dataset."},
)
dataset_dir: str = field(
default="data",
metadata={"help": "Path to the folder containing the datasets."},
)
cutoff_len: int = field(
default=2048,
metadata={"help": "Cutoff length for the dataset."},
)

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# Copyright 2025 the LlamaFactory team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from dataclasses import dataclass, field
@dataclass
class ModelArguments:
model: str = field(
metadata={"help": "Path to the model or model identifier from Hugging Face."},
)
trust_remote_code: bool = field(
default=False,
metadata={"help": "Trust remote code from Hugging Face."},
)

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# Copyright 2025 the LlamaFactory team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
import sys
from pathlib import Path
from typing import Any, Optional, Union
from omegaconf import OmegaConf
from transformers import HfArgumentParser
from ...extras.misc import is_env_enabled
from .data_args import DataArguments
from .model_args import ModelArguments
from .sample_args import SampleArguments
from .training_args import TrainingArguments
def get_args(
args: Optional[Union[dict[str, Any], list[str]]] = None,
) -> tuple[DataArguments, ModelArguments, TrainingArguments, SampleArguments]:
"""Parse arguments from command line or config file."""
parser = HfArgumentParser([DataArguments, ModelArguments, TrainingArguments, SampleArguments])
allow_extra_keys = is_env_enabled("ALLOW_EXTRA_KEYS")
if args is None:
if len(sys.argv) > 1 and (sys.argv[1].endswith(".yaml") or sys.argv[1].endswith(".yml")):
override_config = OmegaConf.from_cli(sys.argv[2:])
dict_config = OmegaConf.load(Path(sys.argv[1]).absolute())
args = OmegaConf.to_container(OmegaConf.merge(dict_config, override_config))
elif len(sys.argv) > 1 and sys.argv[1].endswith(".json"):
override_config = OmegaConf.from_cli(sys.argv[2:])
dict_config = OmegaConf.create(json.load(Path(sys.argv[1]).absolute()))
args = OmegaConf.to_container(OmegaConf.merge(dict_config, override_config))
else: # list of strings
args = sys.argv[1:]
if isinstance(args, dict):
(*parsed_args,) = parser.parse_dict(args, allow_extra_keys=allow_extra_keys)
else:
(*parsed_args, unknown_args) = parser.parse_args_into_dataclasses(args, return_remaining_strings=True)
if unknown_args and not allow_extra_keys:
print(parser.format_help())
print(f"Got unknown args, potentially deprecated arguments: {unknown_args}")
raise ValueError(f"Some specified arguments are not used by the HfArgumentParser: {unknown_args}")
return tuple(parsed_args)
if __name__ == "__main__":
print(get_args())

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# Copyright 2025 the LlamaFactory team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from dataclasses import dataclass, field
@dataclass
class SampleArguments:
max_new_tokens: int = field(
default=128,
metadata={"help": "Maximum number of new tokens to generate."},
)

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# Copyright 2025 the LlamaFactory team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from dataclasses import dataclass, field
@dataclass
class TrainingArguments:
output_dir: str = field(
default="",
metadata={"help": "Path to the output directory."},
)
micro_batch_size: int = field(
default=1,
metadata={"help": "Micro batch size for training."},
)
global_batch_size: int = field(
default=1,
metadata={"help": "Global batch size for training."},
)
learning_rate: float = field(
default=1e-4,
metadata={"help": "Learning rate for training."},
)
bf16: bool = field(
default=False,
metadata={"help": "Use bf16 for training."},
)