set -eux source $1 source ./env.sh export FLAGS_eager_delete_tensor_gb=1.0 export FLAGS_sync_nccl_allreduce=1 export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7" # check check_iplist mkdir -p ./log mkdir -p ./checkpoints mkdir -p ./tmpdir export TMPDIR=`pwd`/tmpdir export TASK_DATA_PATH=${data_path} export EVAL_SCRIPT_LOG=`pwd`"/log/eval.log" export DEV_PREFIX=`echo ${dev_set:-"dev.tsv"} | sed 's/\.tsv$//'` export TEST_PREFIX=`echo ${test_set:-"test.tsv"} | sed 's/\.tsv$//'` export PRED_PREFIX=`echo ${pred_set:-"pred.tsv"} | sed 's/\.tsv$//'` distributed_args="--node_ips ${PADDLE_TRAINERS} \ --node_id ${PADDLE_TRAINER_ID} \ --current_node_ip ${POD_IP}" python -u ./utils/finetune_launch.py ${distributed_args} \ ./run_seq2seq.py --use_cuda true \ --do_train $do_train \ --do_val $do_val \ --do_test $do_test \ --do_pred ${do_pred:-"false"} \ --train_set ${TASK_DATA_PATH}/${train_set:-""} \ --dev_set ${TASK_DATA_PATH}/${dev_set:-""} \ --test_set ${TASK_DATA_PATH}/${test_set:-""} \ --pred_set ${TASK_DATA_PATH}/${pred_set:-""} \ --epoch ${epoch} \ --tokenizer ${tokenizer:-"FullTokenizer"} \ --tokenized_input ${tokenized_input:-"False"} \ --task_type ${task_type:-"normal"} \ --role_type_size ${role_type_size:-0} \ --turn_type_size ${turn_type_size:-0} \ --max_src_len $max_src_len \ --max_tgt_len $max_tgt_len \ --max_dec_len $max_dec_len \ --hidden_dropout_prob ${hidden_dropout_prob:--1} \ --attention_probs_dropout_prob ${attention_probs_dropout_prob:--1} \ --random_noise ${random_noise:-"False"} \ --noise_prob ${noise_prob:-0.0} \ --continuous_position ${continuous_position:-"false"} \ --tgt_type_id ${tgt_type_id:-1}\ --batch_size $batch_size \ --learning_rate $learning_rate \ --lr_scheduler ${lr_scheduler:-"linear_warmup_decay"} \ --warmup_proportion ${warmup_proportion:-0.0} \ --weight_decay ${weight_decay:-0.0} \ --weight_sharing ${weight_sharing:-"True"} \ --label_smooth ${label_smooth:-0.0} \ --do_decode ${do_decode:-"True"} \ --beam_size ${beam_size:-5} \ --length_penalty ${length_penalty:-"0.0"} \ --init_pretraining_params ${init_model:-""} \ --vocab_path ${vocab_path} \ --ernie_config_path ${config_path} \ --checkpoints ./checkpoints \ --save_and_valid_by_epoch ${save_and_valid_by_epoch:-"True"} \ --eval_script ${eval_script:-""} \ --eval_mertrics ${eval_mertrics:-"bleu"} \ --random_seed ${random_seed:-"-1"} > log/lanch.log 2>&1 &