cen_run.sh

#!/bin/bash
# shellcheck disable=SC2068
# 读取参数
idx=0
for i in $@
do
  args[${idx}]=$i
  let "idx=${idx}+1"
done

# 分离参数
run_dirs=${args[0]}
task_name=${args[1]}
fl_algorithm=${args[2]}
config_path=${args[3]}  # relative in this project
port=${args[4]}

idx=0
for(( i=5;i<${#args[@]};i++ ))
do
  device[${idx}]=${args[i]}
  let "idx=${idx}+1"
done

world_size=${#device[@]}
echo "world_size is ${world_size}"
echo "run_dirs: ${run_dirs}"

max_seq=512
# dataset_name = "legal"
# metric_name = "legal"
model_name='roberta-wwm-ext'
data_file='legal/silo'
if [ ${task_name} == "LCP" ];
then
  model_output_mode="seq_classification"
elif [ ${task_name} == "LJP" ];
then
  model_output_mode='seq_regression'
elif [ ${task_name} == "LAM" ];
then
  model_output_mode='multi_seq_classification'
elif [ ${task_name} == "LER" ];
then
  model_output_mode='token_classification_crf'
elif [ ${task_name} == "LRE" ];
then
  model_output_mode='seq_classification'
elif [ ${task_name} == "LDG" ];
then
  model_output_mode='seq_generation'
  model_name='gpt2-chinese-cluecorpussmall'
  max_seq=1024
else
  echo "Don't support ${task_name}"
  exit 1
fi
echo "${task_name}'s max_seq is ${max_seq}"


CUDA_VISIBLE_DEVICES=${device[0]} python main.py \
--model_name_or_path ${run_dirs}/pretrain/nlp/${model_name}/ \
--output_dir ${run_dirs}/output/${data_file}  \
--task_name ${task_name} \
--fl_algorithm ${fl_algorithm} \
--raw_dataset_path ${run_dirs}/datasets/${data_file} \
--partition_dataset_path ${run_dirs}/datasets/${data_file} \
--max_seq_length ${max_seq}  \
--world_size ${world_size}  \
--config_path ${config_path}

wait