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single_d4rl_run_file.sh
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single_d4rl_run_file.sh
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algo="iqln"
n_ensemble="10"
n_steps="5000"
weight_temp="3.0"
expectile="0.7"
expectile_min="0.7"
expectile_max="0.7"
update_ratio="0.3"
alpha="2"
dataset="halfcheetah"
dataset_nums="3000-0"
mix_type="random"
clone_actor=""
clear_network=""
max_save_num="10"
actor_replay_type="orl"
actor_replay_lambda="1"
critic_replay_type="orl"
critic_replay_lambda="1"
entropy_time="0"
test_=""
gpu=0
echo original parameters=[$@]
ARGS=`getopt -o a:s:d:m: --long algo:,n_ensemble:,n_steps:,weight_temp:,expectile:,expectile_min:,expectile_max:,update_ratio:,alpha:,dataset:,dataset_nums:,mix_type:,clone_actor,clear_network,max_save_num:,actor_replay_type:,actor_replay_lambda:,critic_replay_type:,critic_replay_lambda:,entropy_time:,gpu:,test_ -n "$0" -- "$@"`
if [ $? != 0 ]; then
echo "Terminating..."
exit 1
fi
echo ARGS=[$ARGS]
#将规范化后的命令行参数分配至位置参数（$1,$2,...)
eval set -- "${ARGS}"
echo formatted parameters=[$@]
while true
do
case "$1" in
-a|--algo)
algo=$2
shift 2
;;
--n_ensemble)
n_ensemble=$2
shift 2
;;
-s|--n_steps)
n_steps=$2
shift 2
;;
--weight_temp)
weight_temp=$2
shift 2
;;
--expectile)
expectile=$2
shift 2
;;
--expectile_min)
expectile_min=$2
shift 2
;;
--expectile_max)
expectile_max=$2
shift 2
;;
--update_ratio)
update_ratio=$2
shift 2
;;
--alpha)
alpha=$2
shift 2
;;
--dataset)
dataset=$2
shift 2
;;
--dataset_nums)
dataset_nums=$2
shift 2
;;
--mix_type)
mix_type=$2
shift 2
;;
--max_save_num)
max_save_num=$2
shift 2
;;
--actor_replay_type)
actor_replay_type=$2
shift 2
;;
--actor_replay_lambda)
actor_replay_lambda=$2
shift 2
;;
--critic_replay_type)
critic_replay_type=$2
shift 2
;;
--critic_replay_lambda)
critic_replay_lambda=$2
shift 2
;;
--entropy_time)
entropy_time=$2
shift 2
;;
--gpu)
gpu=$2
shift 2
;;
--clone_actor)
clone_actor="--clone_actor"
shift;
;;
--clear_network)
clear_network="--clear_network"
shift;
;;
--test_)
test_="--test"
shift;
;;
--)
shift
break
;;
*)
echo "Internal error!"
exit 1
;;
esac
done
if [[ $clone_actor == "--clone_actor" ]]
then
clone_actor_str="cloneactor"
else
clone_actor_str=""
fi
if [[ $clear_network == "--clear_network" ]]
then
clear_network_str="_clearnetwork"
else
clear_network_str=""
fi
if [[ $algo == "sql" || $algo == "sqln" ]]
then
if [[ $test_ == "--test" ]]
then
task_id=${algo}_${n_ensemble}_${alpha}_${dataset}_${dataset_nums}_${n_steps}_${actor_replay_type}_${actor_replay_lambda}_${critic_replay_type}_${critic_replay_lambda}_${entropy_time}_${clone_actor_str}_${mix_type}_${max_save_num}${clear_network_str}_0_test
output_file=single_output_files/output_${algo}_${n_ensemble}_${alpha}_${dataset}_${dataset_nums}_${n_steps}_${actor_replay_type}_${actor_replay_lambda}_${critic_replay_type}_${critic_replay_lambda}_${entropy_time}_${clone_actor_str}_${mix_type}_${max_save_num}${clear_network_str}_test.txt
else
task_id=${algo}_${n_ensemble}_${alpha}_${dataset}_${dataset_nums}_${n_steps}_${actor_replay_type}_${actor_replay_lambda}_${critic_replay_type}_${critic_replay_lambda}_${entropy_time}_${clone_actor_str}_${mix_type}_${max_save_num}${clear_network_str}_0
output_file=single_output_files/output_${algo}_${n_ensemble}_${alpha}_${dataset}_${dataset_nums}_${n_steps}_${actor_replay_type}_${actor_replay_lambda}_${critic_replay_type}_${critic_replay_lambda}_${entropy_time}_${clone_actor_str}_${mix_type}_${max_save_num}${clear_network_str}_0_$(date +%Y%m%d%H%M%S).txt
fi
else
if [[ $test_ == "--test" ]]
then
task_id=${algo}_${n_ensemble}_${weight_temp}_${expectile}_${expectile_min}_${expectile_max}_${dataset}_${dataset_nums}_${n_steps}_${actor_replay_type}_${actor_replay_lambda}_${critic_replay_type}_${critic_replay_lambda}_${entropy_time}_${clone_actor_str}_${mix_type}_${max_save_num}${clear_network_str}_0_test
output_file=single_output_files/output_${algo}_${n_ensemble}_${weight_temp}_${expectile}_${expectile_min}_${expectile_max}_${dataset}_${dataset_nums}_${n_steps}_${actor_replay_type}_${actor_replay_lambda}_${critic_replay_type}_${critic_replay_lambda}_${entropy_time}_${clone_actor_str}_${mix_type}_${max_save_num}${clear_network_str}_test.txt
else
task_id=${algo}_${n_ensemble}_${expectile}_${expectile_min}_${expectile_max}_${dataset}_${dataset_nums}_${n_steps}_${actor_replay_type}_${actor_replay_lambda}_${critic_replay_type}_${critic_replay_lambda}_${entropy_time}_${clone_actor_str}_${mix_type}_${max_save_num}${clear_network_str}_0
output_file=single_output_files/output_${algo}_${n_ensemble}_${weight_temp}_${expectile}_${expectile_min}_${expectile_max}_${dataset}_${dataset_nums}_${n_steps}_${actor_replay_type}_${actor_replay_lambda}_${critic_replay_type}_${critic_replay_lambda}_${entropy_time}_${clone_actor_str}_${mix_type}_${max_save_num}${clear_network_str}_0_$(date +%Y%m%d%H%M%S).txt
fi
fi
echo "output_file is $output_file"
python continual_single.py --algo ${algo} --alpha ${alpha} --update_ratio ${update_ratio} --n_ensemble ${n_ensemble} --experience_type random_episode --dataset ${dataset} --dataset_nums ${dataset_nums} --max_save_num ${max_save_num} --critic_replay_type ${critic_replay_type} --critic_replay_lambda ${critic_replay_lambda} --actor_replay_type ${actor_replay_type} --actor_replay_lambda ${actor_replay_lambda} ${clone_actor} ${clear_network} --mix_type ${mix_type} --weight_temp ${weight_temp} --expectile ${expectile} --expectile_min ${expectile_min} --expectile_max ${expectile_max} --entropy_time ${entropy_time} --n_steps=${n_steps} --seed 0 --read_policy -1 --gpu ${gpu} | tee $output_file