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[misc] lint (#9710)

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This commit is contained in:
Yaowei Zheng
2026-01-04 13:47:56 +08:00
committed by GitHub
parent 9ae62c6fc0
commit 8600530002
6 changed files with 15 additions and 13 deletions
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5
src/llamafactory/train/fp8_utils.py
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@@ -93,7 +93,10 @@ def create_fp8_kwargs(training_args: "TrainingArguments") -> list[Any]:
return True
# Map FSDP all-gather setting if available (this affects the underlying implementation)
if hasattr(training_args, "fp8_enable_fsdp_float8_all_gather") and training_args.fp8_enable_fsdp_float8_all_gather:
if (
hasattr(training_args, "fp8_enable_fsdp_float8_all_gather")
and training_args.fp8_enable_fsdp_float8_all_gather
):
logger.info_rank0("FSDP float8 all-gather optimization requested")
return [AORecipeKwargs(config=config, module_filter_func=module_filter_func)]

7
src/llamafactory/train/pt/trainer.py
View File

@@ -19,7 +19,6 @@ import torch
from transformers import Trainer
from typing_extensions import override
from ...extras.packages import is_transformers_version_greater_than
from ..callbacks import SaveProcessorCallback
from ..fp8_utils import configure_fp8_environment, patch_accelerator_for_fp8, verify_fp8_status
from ..trainer_utils import create_custom_optimizer, create_custom_scheduler
@@ -28,7 +27,7 @@ from ..trainer_utils import create_custom_optimizer, create_custom_scheduler
if TYPE_CHECKING:
from transformers import ProcessorMixin
from ...hparams import FinetuningArguments, ModelArguments
from ...hparams import FinetuningArguments, ModelArguments, TrainingArguments
class CustomTrainer(Trainer):
@@ -43,7 +42,7 @@ class CustomTrainer(Trainer):
) -> None:
kwargs["processing_class"] = kwargs.pop("tokenizer")
# Configure FP8 environment if enabled
training_args = kwargs.get("args")
training_args: TrainingArguments = kwargs.get("args")
if training_args.fp8:
configure_fp8_environment(training_args)
if getattr(training_args, "fp8_backend", "auto") == "te":
@@ -66,7 +65,7 @@ class CustomTrainer(Trainer):
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.add_callback(BAdamCallback)
if training_args.fp8 and hasattr(self, "accelerator"): # verify FP8 status after trainer initialization
if training_args.fp8 and hasattr(self, "accelerator"): # verify FP8 status after trainer initialization
verify_fp8_status(self.accelerator, training_args)
@override

9
src/llamafactory/train/sft/trainer.py
View File

@@ -27,7 +27,6 @@ from typing_extensions import override
from ...extras import logging
from ...extras.constants import IGNORE_INDEX
from ...extras.packages import is_transformers_version_greater_than
from ..callbacks import SaveProcessorCallback
from ..fp8_utils import configure_fp8_environment, patch_accelerator_for_fp8, verify_fp8_status
from ..trainer_utils import create_custom_optimizer, create_custom_scheduler
@@ -35,10 +34,10 @@ from ..trainer_utils import create_custom_optimizer, create_custom_scheduler
if TYPE_CHECKING:
from torch.utils.data import Dataset
from transformers import PreTrainedTokenizer, ProcessorMixin
from transformers import ProcessorMixin
from transformers.trainer import PredictionOutput
from ...hparams import FinetuningArguments, ModelArguments
from ...hparams import FinetuningArguments, ModelArguments, TrainingArguments
logger = logging.get_logger(__name__)
@@ -57,7 +56,7 @@ class CustomSeq2SeqTrainer(Seq2SeqTrainer):
) -> None:
kwargs["processing_class"] = kwargs.pop("tokenizer")
# Configure FP8 environment if enabled
training_args = kwargs.get("args")
training_args: TrainingArguments = kwargs.get("args")
if training_args.fp8:
configure_fp8_environment(training_args)
if getattr(training_args, "fp8_backend", "auto") == "te":
@@ -88,7 +87,7 @@ class CustomSeq2SeqTrainer(Seq2SeqTrainer):
self.compute_loss_func = dft_loss_func
if training_args.fp8 and hasattr(self, "accelerator"): # verify FP8 status after trainer initialization
if training_args.fp8 and hasattr(self, "accelerator"): # verify FP8 status after trainer initialization
verify_fp8_status(self.accelerator, training_args)
@override