训练卡住不动，等了几分钟也没反应。

[leon2235]

Describe the bug
What the bug is, and how to reproduce, better with screenshots(描述bug以及复现过程，最好有截图)

运行的sh:

CUDA_VISIBLE_DEVICES=0,1,2,3
NPROC_PER_NODE=4
swift rlhf
--rlhf_type grpo
--model '/public/home/202420164005/model/Qwen/Qwen2.5-Omni-7B'
--adapters '/public/home/202420164005/code/ms-swift/SFT/checkpoints/v3-20251203-105243/checkpoint-180'
--external_plugins '/public/home/202420164005/code/ms-swift/GRPO/reward.py'
--reward_funcs external_ad_content_llm_remote
--train_type lora
--lora_rank 8
--lora_alpha 32
--target_modules all-linear
--torch_dtype bfloat16
--dataset '/public/home/202420164005/code/ms-swift/GRPO/data/train_gemini_rewrite.jsonl'
--val_dataset '/public/home/202420164005/code/ms-swift/GRPO/data/val_gemini_rewrite.jsonl'
--max_length 4096
--max_completion_length 800
--num_train_epochs 5
--per_device_train_batch_size 4
--per_device_eval_batch_size 4
--learning_rate 1e-5
--gradient_accumulation_steps 1
--eval_steps 20
--save_steps 20
--save_total_limit 2
--logging_steps 5
--output_dir '/public/home/202420164005/code/ms-swift/GRPO/checkpoint_1128'
--warmup_ratio 0.05
--dataloader_num_workers 4
--num_generations 4
--temperature 0.9
--system '你是一名顶尖的语音语言学和认知神经科学专家。'
--log_completions true

终端输出：

run sh: /public/home/202420164005/miniconda3/envs/swift-env/bin/python3.10 -m torch.distributed.run --nproc_per_node 4 /public/home/202420164005/code/ms-swift/swift/cli/rlhf.py --rlhf_type grpo --model /public/home/202420164005/model/Qwen/Qwen2.5-Omni-7B --adapters /public/home/202420164005/code/ms-swift/SFT/checkpoints/v3-20251203-105243/checkpoint-180 --external_plugins /public/home/202420164005/code/ms-swift/GRPO/reward.py --reward_funcs external_ad_content_llm_remote --train_type lora --lora_rank 8 --lora_alpha 32 --target_modules all-linear --torch_dtype bfloat16 --dataset /public/home/202420164005/code/ms-swift/GRPO/data/train_gemini_rewrite.jsonl --val_dataset /public/home/202420164005/code/ms-swift/GRPO/data/val_gemini_rewrite.jsonl --max_length 4096 --max_completion_length 800 --num_train_epochs 5 --per_device_train_batch_size 4 --per_device_eval_batch_size 4 --learning_rate 1e-5 --gradient_accumulation_steps 1 --eval_steps 20 --save_steps 20 --save_total_limit 2 --logging_steps 5 --output_dir /public/home/202420164005/code/ms-swift/GRPO/checkpoint_1128 --warmup_ratio 0.05 --dataloader_num_workers 4 --num_generations 4 --temperature 0.9 --system 你是一名顶尖的语音语言学和认知神经科学专家。 --log_completions true
[INFO:swift] Successfully registered /public/home/202420164005/code/ms-swift/swift/llm/dataset/data/dataset_info.json.
[INFO:swift] Setting args.remove_unused_columns: False
[INFO] Using scorer model: gemini-2.5-flash
[INFO] API endpoint: https://api.apiyi.com/v1/chat/completions
[INFO] Using scorer model: gemini-2.5-flash
[INFO] API endpoint: https://api.apiyi.com/v1/chat/completions
[INFO] Using scorer model: gemini-2.5-flash
[INFO] API endpoint: https://api.apiyi.com/v1/chat/completions
[INFO] Using scorer model: gemini-2.5-flash
[INFO] API endpoint: https://api.apiyi.com/v1/chat/completions
[INFO:swift] Successfully imported external_plugins: ['/public/home/202420164005/code/ms-swift/GRPO/reward.py'].
[INFO:swift] rank: 0, local_rank: 0, world_size: 4, local_world_size: 4
Unrecognized keys in rope_scaling for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in rope_scaling for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in rope_scaling for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in rope_scaling for 'rope_type'='default': {'mrope_section'}
torch_dtype is deprecated! Use dtype instead!
torch_dtype is deprecated! Use dtype instead!
torch_dtype is deprecated! Use dtype instead!
torch_dtype is deprecated! Use dtype instead!
[INFO:swift] Because len(args.val_dataset) > 0, setting split_dataset_ratio: 0.0
[INFO:swift] Setting args.lazy_tokenize: True

Your hardware and system info
Write your system info like CUDA version/system/GPU/torch version here(在这里给出硬件信息和系统信息，如CUDA版本，系统，GPU型号和torch版本等)

Additional context
Add any other context about the problem here(在这里补充其他信息)

[hjh0119]

run normally on my end, plz provide pip list

CUDA_VISIBLE_DEVICES=0,1,2,3 \
NPROC_PER_NODE=4 \
swift rlhf \
    --rlhf_type grpo \
    --model 'Qwen/Qwen2.5-Omni-7B' \
    --reward_funcs format \
    --train_type lora \
    --lora_rank 8 \
    --lora_alpha 32 \
    --target_modules all-linear \
    --torch_dtype bfloat16 \
    --dataset 'AI-ModelScope/clevr_cogen_a_train#1000' \
    --max_length 4096 \
    --max_completion_length 800 \
    --num_train_epochs 5 \
    --per_device_train_batch_size 4 \
    --per_device_eval_batch_size 4 \
    --learning_rate 1e-5 \
    --gradient_accumulation_steps 1 \
    --eval_steps 20 \
    --save_steps 20 \
    --save_total_limit 2 \
    --logging_steps 5 \
    --warmup_ratio 0.05 \
    --dataloader_num_workers 4 \
    --num_generations 4 \
    --temperature 0.9 \
    --system '你是一名顶尖的语音语言学和认知神经科学专家。' \
    --log_completions true

[leon2235]

run normally on my end, plz provide pip list

CUDA_VISIBLE_DEVICES=0,1,2,3 \
NPROC_PER_NODE=4 \
swift rlhf \
    --rlhf_type grpo \
    --model 'Qwen/Qwen2.5-Omni-7B' \
    --reward_funcs format \
    --train_type lora \
    --lora_rank 8 \
    --lora_alpha 32 \
    --target_modules all-linear \
    --torch_dtype bfloat16 \
    --dataset 'AI-ModelScope/clevr_cogen_a_train#1000' \
    --max_length 4096 \
    --max_completion_length 800 \
    --num_train_epochs 5 \
    --per_device_train_batch_size 4 \
    --per_device_eval_batch_size 4 \
    --learning_rate 1e-5 \
    --gradient_accumulation_steps 1 \
    --eval_steps 20 \
    --save_steps 20 \
    --save_total_limit 2 \
    --logging_steps 5 \
    --warmup_ratio 0.05 \
    --dataloader_num_workers 4 \
    --num_generations 4 \
    --temperature 0.9 \
    --system '你是一名顶尖的语音语言学和认知神经科学专家。' \
    --log_completions true

my pip list:
(swift-env) [202420164005@admin model]$ pip list
Package Version

---

absl-py 2.3.1
accelerate 1.11.0
addict 2.4.0
aiofiles 24.1.0
aiohappyeyeballs 2.6.1
aiohttp 3.13.2
aiosignal 1.4.0
aliyun-python-sdk-core 2.16.0
aliyun-python-sdk-kms 2.16.5
annotated-doc 0.0.3
annotated-types 0.7.0
antlr4-python3-runtime 4.13.2
anyio 4.11.0
astor 0.8.1
async-timeout 5.0.1
attrdict 2.0.1
attrs 25.4.0
audioread 3.1.0
av 16.0.1
binpacking 1.5.2
blake3 1.0.8
Brotli 1.1.0
cachetools 6.2.1
cbor2 5.7.1
certifi 2025.10.5
cffi 2.0.0
charset-normalizer 3.4.4
click 8.2.1
cloudpickle 3.1.2
compressed-tensors 0.11.0
contourpy 1.3.2
cpm-kernels 1.0.11
crcmod 1.7
cryptography 46.0.3
cupy-cuda12x 13.6.0
cycler 0.12.1
dacite 1.9.2
datasets 3.6.0
decorator 5.2.1
decord 0.6.0
depyf 0.19.0
dill 0.3.8
diskcache 5.6.3
distro 1.9.0
dnspython 2.8.0
einops 0.8.1
email-validator 2.3.0
exceptiongroup 1.3.0
fastapi 0.121.0
fastapi-cli 0.0.14
fastapi-cloud-cli 0.3.1
fastrlock 0.8.3
ffmpy 0.6.4
filelock 3.20.0
fonttools 4.60.1
frozendict 2.4.6
frozenlist 1.8.0
fsspec 2025.3.0
future 1.0.0
gguf 0.17.1
gradio 5.49.1
gradio_client 1.13.3
groovy 0.1.2
grpcio 1.76.0
h11 0.16.0
hf-xet 1.2.0
httpcore 1.0.9
httptools 0.7.1
httpx 0.28.1
huggingface-hub 0.36.0
idna 3.11
importlib_metadata 8.7.0
interegular 0.3.3
jieba 0.42.1
Jinja2 3.1.6
jiter 0.11.1
jmespath 0.10.0
joblib 1.5.2
json_repair 0.52.4
jsonschema 4.25.1
jsonschema-specifications 2025.9.1
kiwisolver 1.4.9
lark 1.2.2
latex2sympy2_extended 1.0.6
lazy_loader 0.4
librosa 0.11.0
llguidance 0.7.30
llvmlite 0.44.0
lm-format-enforcer 0.11.3
Markdown 3.9
markdown-it-py 4.0.0
MarkupSafe 3.0.3
math-verify 0.5.2
matplotlib 3.10.7
mdurl 0.1.2
mistral_common 1.8.5
modelscope 1.32.0
mpmath 1.3.0
ms_swift 3.10.0.dev0
msgpack 1.1.2
msgspec 0.19.0
multidict 6.7.0
multiprocess 0.70.16
mutagen 1.47.0
networkx 3.4.2
ninja 1.13.0
nltk 3.9.2
numba 0.61.2
numpy 2.2.6
nvidia-cublas-cu12 12.8.4.1
nvidia-cuda-cupti-cu12 12.8.90
nvidia-cuda-nvrtc-cu12 12.8.93
nvidia-cuda-runtime-cu12 12.8.90
nvidia-cudnn-cu12 9.10.2.21
nvidia-cufft-cu12 11.3.3.83
nvidia-cufile-cu12 1.13.1.3
nvidia-curand-cu12 10.3.9.90
nvidia-cusolver-cu12 11.7.3.90
nvidia-cusparse-cu12 12.5.8.93
nvidia-cusparselt-cu12 0.7.1
nvidia-ml-py 13.580.82
nvidia-nccl-cu12 2.27.3
nvidia-nvjitlink-cu12 12.8.93
nvidia-nvshmem-cu12 3.3.20
nvidia-nvtx-cu12 12.8.90
nvitop 1.5.3
omegaconf 2.3.0
openai 2.6.1
openai-harmony 0.0.8
opencv-python-headless 4.12.0.88
orjson 3.11.4
oss2 2.19.1
outlines_core 0.2.11
packaging 25.0
pandas 2.3.3
partial-json-parser 0.2.1.1.post6
peft 0.17.1
pillow 11.3.0
pip 25.2
platformdirs 4.5.0
pooch 1.8.2
prometheus_client 0.23.1
prometheus-fastapi-instrumentator 7.1.0
propcache 0.4.1
protobuf 6.33.0
psutil 7.1.3
py-cpuinfo 9.0.0
pyarrow 22.0.0
pybase64 1.4.2
pycountry 24.6.1
pycparser 2.23
pycryptodome 3.23.0
pydantic 2.11.10
pydantic_core 2.33.2
pydantic-extra-types 2.10.6
pydub 0.25.1
Pygments 2.19.2
pyparsing 3.2.5
python-dateutil 2.9.0.post0
python-dotenv 1.2.1
python-json-logger 4.0.0
python-multipart 0.0.20
pytz 2025.2
PyYAML 6.0.3
pyzmq 27.1.0
qwen-omni-utils 0.0.8
ray 2.51.1
referencing 0.37.0
regex 2025.10.23
requests 2.32.5
rich 14.2.0
rich-toolkit 0.15.1
rignore 0.7.6
rouge 1.0.1
rpds-py 0.28.0
ruff 0.14.3
safehttpx 0.1.7
safetensors 0.6.2
scikit-learn 1.7.2
scipy 1.15.3
semantic-version 2.10.0
sentencepiece 0.2.1
sentry-sdk 2.43.0
setproctitle 1.3.7
setuptools 80.9.0
shellingham 1.5.4
simplejson 3.20.2
six 1.17.0
sniffio 1.3.1
sortedcontainers 2.4.0
soundfile 0.13.1
soxr 1.0.0
starlette 0.49.3
sympy 1.14.0
tensorboard 2.20.0
tensorboard-data-server 0.7.2
threadpoolctl 3.6.0
tiktoken 0.12.0
tokenizers 0.22.1
tomlkit 0.13.3
torch 2.8.0
torchaudio 2.8.0
torchvision 0.23.0
tqdm 4.67.1
transformers 4.57.1
transformers-stream-generator 0.0.5
triton 3.4.0
trl 0.24.0
typer 0.20.0
typing_extensions 4.15.0
typing-inspection 0.4.2
tzdata 2025.2
urllib3 2.5.0
uvicorn 0.38.0
uvloop 0.22.1
vllm 0.11.0
watchfiles 1.1.1
websockets 15.0.1
Werkzeug 3.1.3
wheel 0.45.1
xformers 0.0.32.post1
xgrammar 0.1.25
xxhash 3.6.0
yarl 1.22.0
zipp 3.23.0
zstandard 0.25.0

[hjh0119]

pip install -U ms-swift

[leon2235]

pip install -U ms-swift

刚刚试了一下单卡，是没问题的，我在找找原因