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[deps] goodbye python 3.9 (#9677)

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Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: hiyouga <16256802+hiyouga@users.noreply.github.com>
Co-authored-by: hiyouga <hiyouga@buaa.edu.cn>
This commit is contained in:
Copilot
2025-12-27 02:50:44 +08:00
committed by GitHub
parent b44f651e09
commit eceec8ab69
48 changed files with 267 additions and 284 deletions
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28
src/llamafactory/hparams/data_args.py
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@@ -16,22 +16,22 @@
# limitations under the License.
from dataclasses import asdict, dataclass, field
from typing import Any, Literal, Optional
from typing import Any, Literal
@dataclass
class DataArguments:
r"""Arguments pertaining to what data we are going to input our model for training and evaluation."""
template: Optional[str] = field(
template: str | None = field(
default=None,
metadata={"help": "Which template to use for constructing prompts in training and inference."},
)
dataset: Optional[str] = field(
dataset: str | None = field(
default=None,
metadata={"help": "The name of dataset(s) to use for training. Use commas to separate multiple datasets."},
)
eval_dataset: Optional[str] = field(
eval_dataset: str | None = field(
default=None,
metadata={"help": "The name of dataset(s) to use for evaluation. Use commas to separate multiple datasets."},
)
@@ -39,7 +39,7 @@ class DataArguments:
default="data",
metadata={"help": "Path to the folder containing the datasets."},
)
media_dir: Optional[str] = field(
media_dir: str | None = field(
default=None,
metadata={"help": "Path to the folder containing the images, videos or audios. Defaults to `dataset_dir`."},
)
@@ -67,7 +67,7 @@ class DataArguments:
default="concat",
metadata={"help": "Strategy to use in dataset mixing (concat/interleave) (undersampling/oversampling)."},
)
interleave_probs: Optional[str] = field(
interleave_probs: str | None = field(
default=None,
metadata={"help": "Probabilities to sample data from datasets. Use commas to separate multiple datasets."},
)
@@ -79,15 +79,15 @@ class DataArguments:
default=1000,
metadata={"help": "The number of examples in one group in pre-processing."},
)
preprocessing_num_workers: Optional[int] = field(
preprocessing_num_workers: int | None = field(
default=None,
metadata={"help": "The number of processes to use for the pre-processing."},
)
max_samples: Optional[int] = field(
max_samples: int | None = field(
default=None,
metadata={"help": "For debugging purposes, truncate the number of examples for each dataset."},
)
eval_num_beams: Optional[int] = field(
eval_num_beams: int | None = field(
default=None,
metadata={"help": "Number of beams to use for evaluation. This argument will be passed to `model.generate`"},
)
@@ -103,7 +103,7 @@ class DataArguments:
default=False,
metadata={"help": "Whether or not to evaluate on each dataset separately."},
)
packing: Optional[bool] = field(
packing: bool | None = field(
default=None,
metadata={"help": "Enable sequences packing in training. Will automatically enable in pre-training."},
)
@@ -111,19 +111,19 @@ class DataArguments:
default=False,
metadata={"help": "Enable sequence packing without cross-attention."},
)
tool_format: Optional[str] = field(
tool_format: str | None = field(
default=None,
metadata={"help": "Tool format to use for constructing function calling examples."},
)
default_system: Optional[str] = field(
default_system: str | None = field(
default=None,
metadata={"help": "Override the default system message in the template."},
)
enable_thinking: Optional[bool] = field(
enable_thinking: bool | None = field(
default=True,
metadata={"help": "Whether or not to enable thinking mode for reasoning models."},
)
tokenized_path: Optional[str] = field(
tokenized_path: str | None = field(
default=None,
metadata={
"help": (