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[misc] upgrade format to py39 (#7256)

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hoshi-hiyouga
2025-03-12 00:08:41 +08:00
committed by GitHub
parent bcd287848c
commit efa86e730c
113 changed files with 984 additions and 1407 deletions
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29
src/llamafactory/hparams/model_args.py
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@@ -17,7 +17,7 @@
import json
from dataclasses import asdict, dataclass, field, fields
from typing import Any, Dict, Literal, Optional, Union
from typing import Any, Literal, Optional, Union
import torch
from transformers.training_args import _convert_str_dict
@@ -28,9 +28,7 @@ from ..extras.constants import AttentionFunction, EngineName, RopeScaling
@dataclass
class BaseModelArguments:
r"""
Arguments pertaining to the model.
"""
r"""Arguments pertaining to the model."""
model_name_or_path: Optional[str] = field(
default=None,
@@ -184,9 +182,7 @@ class BaseModelArguments:
@dataclass
class QuantizationArguments:
r"""
Arguments pertaining to the quantization method.
"""
r"""Arguments pertaining to the quantization method."""
quantization_method: Literal["bitsandbytes", "hqq", "eetq"] = field(
default="bitsandbytes",
@@ -212,9 +208,7 @@ class QuantizationArguments:
@dataclass
class ProcessorArguments:
r"""
Arguments pertaining to the image processor.
"""
r"""Arguments pertaining to the image processor."""
image_max_pixels: int = field(
default=768 * 768,
@@ -244,9 +238,7 @@ class ProcessorArguments:
@dataclass
class ExportArguments:
r"""
Arguments pertaining to the model export.
"""
r"""Arguments pertaining to the model export."""
export_dir: Optional[str] = field(
default=None,
@@ -292,9 +284,7 @@ class ExportArguments:
@dataclass
class VllmArguments:
r"""
Arguments pertaining to the vLLM worker.
"""
r"""Arguments pertaining to the vLLM worker."""
vllm_maxlen: int = field(
default=4096,
@@ -324,8 +314,7 @@ class VllmArguments:
@dataclass
class ModelArguments(VllmArguments, ExportArguments, ProcessorArguments, QuantizationArguments, BaseModelArguments):
r"""
Arguments pertaining to which model/config/tokenizer we are going to fine-tune or infer.
r"""Arguments pertaining to which model/config/tokenizer we are going to fine-tune or infer.
The class on the most right will be displayed first.
"""
@@ -335,7 +324,7 @@ class ModelArguments(VllmArguments, ExportArguments, ProcessorArguments, Quantiz
init=False,
metadata={"help": "Torch data type for computing model outputs, derived from `fp/bf16`. Do not specify it."},
)
device_map: Optional[Union[str, Dict[str, Any]]] = field(
device_map: Optional[Union[str, dict[str, Any]]] = field(
default=None,
init=False,
metadata={"help": "Device map for model placement, derived from training stage. Do not specify it."},
@@ -372,7 +361,7 @@ class ModelArguments(VllmArguments, ExportArguments, ProcessorArguments, Quantiz
return result
def to_dict(self) -> Dict[str, Any]:
def to_dict(self) -> dict[str, Any]:
args = asdict(self)
args = {k: f"<{k.upper()}>" if k.endswith("token") else v for k, v in args.items()}
return args