微调seaco_paraformer模型单机多卡出现错误

[gzqqqqqq]

🐛 Bug

funasr1.1.5 微调热词模型，单机多卡报错，单机单卡可以跑通

To Reproduce

workspace=pwd

which gpu to train or finetune

export CUDA_VISIBLE_DEVICES="0,1,2,3" gpu_num=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')

model_name from model_hub, or model_dir in local path

option 1, download model automatically

model_name_or_model_dir="speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"

data dir, which contains: train.json, val.json

data_dir="data"

train_data="${data_dir}/train.jsonl" val_data="${data_dir}/val.jsonl"

output_dir="./outputs" log_file="${output_dir}/log.txt"

mkdir -p ${output_dir} echo "log_file: ${log_file}"

DISTRIBUTED_ARGS=" --nnodes ${WORLD_SIZE:-1} \ --nproc_per_node $gpu_num \ --node_rank ${RANK:-0} \ --master_addr ${MASTER_ADDR:-127.0.0.1} \ --master_port ${MASTER_PORT:-26669} "

echo $DISTRIBUTED_ARGS

torchrun $DISTRIBUTED_ARGS \ ../../../funasr/bin/train_ds.py \ ++model="${model_name_or_model_dir}" \ ++train_data_set_list="${train_data}" \ ++valid_data_set_list="${val_data}" \ ++dataset="AudioDatasetHotword" \ ++dataset_conf.index_ds="IndexDSJsonl" \ ++dataset_conf.data_split_num=1 \ ++dataset_conf.batch_sampler="BatchSampler" \ ++dataset_conf.batch_size=6000 \ ++dataset_conf.sort_size=1024 \ ++dataset_conf.batch_type="token" \ ++dataset_conf.num_workers=4 \ ++train_conf.max_epoch=50 \ ++train_conf.log_interval=1 \ ++train_conf.resume=true \ ++train_conf.validate_interval=8000 \ ++train_conf.save_checkpoint_interval=8000 \ ++train_conf.avg_keep_nbest_models_type='loss' \ ++train_conf.keep_nbest_models=20 \ ++train_conf.avg_nbest_model=10 \ ++train_conf.use_deepspeed=false \ ++train_conf.deepspeed_config=${deepspeed_config} \ ++optim_conf.lr=0.0002 \ ++output_dir="${output_dir}" &> ${log_file}

环境安装：​ python==3.12.3 torch==2.3.1 funasr==1.1.5 GPU：A800*4 CUDA：12.1

Expected behavior

正常训练

[smengfei]

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