Spaces:
Runtime error
Runtime error
File size: 3,108 Bytes
50f0fbb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 |
#!/bin/bash
#SBATCH --job-name=bart_summary
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=4
#SBATCH --gres=gpu:4 # number of gpus
#SBATCH -o %x-%j.log
set -x -e
echo "START TIME: $(date)"
MODEL_NAME=bart-base
MICRO_BATCH_SIZE=16
ROOT_DIR=/cognitive_comp/dongxiaoqun/finetune/${MODEL_NAME}
ZERO_STAGE=1
export TORCH_EXTENSIONS_DIR=/cognitive_comp/dongxiaoqun/torch_extendsions
config_json="./ds_config.${MODEL_NAME}.json"
# Deepspeed figures out GAS dynamically from dynamic GBS via set_train_batch_size()
cat <<EOT > $config_json
{
"train_micro_batch_size_per_gpu": ${MICRO_BATCH_SIZE},
"steps_per_print": 100,
"gradient_clipping": 1.0,
"zero_optimization": {
"stage": $ZERO_STAGE,
"contiguous_gradients": false,
"overlap_comm": true,
"reduce_scatter": true,
"reduce_bucket_size": 50000000,
"allgather_bucket_size": 500000000
},
"optimizer": {
"type": "Adam",
"params": {
"lr": 1e-4,
"betas": [
0.9,
0.95
],
"eps": 1e-8,
"weight_decay": 5e-2
}
},
"scheduler": {
"type": "WarmupLR",
"params":{
"warmup_min_lr": 5e-6,
"warmup_max_lr": 1e-4
}
},
"zero_allow_untested_optimizer": false,
"fp16": {
"enabled": true,
"loss_scale": 0,
"loss_scale_window": 1000,
"hysteresis": 2,
"min_loss_scale": 1
},
"activation_checkpointing": {
"partition_activations": false,
"contiguous_memory_optimization": false
},
"wall_clock_breakdown": false
}
EOT
# export PL_DEEPSPEED_CONFIG_PATH=$config_json
TRAINER_ARGS="
--max_epochs 2 \
--gpus 1 \
--num_nodes 1 \
--strategy deepspeed_stage_${ZERO_STAGE} \
--default_root_dir $ROOT_DIR \
--dirpath $ROOT_DIR/ckpt \
--save_top_k 3 \
--monitor val_loss \
--mode min \
--save_last \
--every_n_train_steps 0 \
--val_check_interval 0.1 \
"
prompt='"'
DATA_ARGS="
--datasets_name lcsts \
--num_workers 8 \
--train_batchsize $MICRO_BATCH_SIZE \
--val_batchsize $MICRO_BATCH_SIZE \
--test_batchsize $MICRO_BATCH_SIZE \
--max_enc_length 128 \
--max_dec_length 64 \
--val_datasets_field val \
--prompt $prompt \
"
MODEL_ARGS="
--pretrained_model_path /cognitive_comp/gaoxinyu/pretrained_model/bart-base \
--output_save_path $ROOT_DIR/${MODEL_NAME}_predict_lcsts.json \
--learning_rate 1e-4 \
--weight_decay 0.1 \
--precision 16 \
"
SCRIPTS_PATH=seq2seq_summary.py
export CMD=" \
$SCRIPTS_PATH \
$TRAINER_ARGS \
$MODEL_ARGS \
$DATA_ARGS \
"
echo $CMD
#singularity exec --nv -B /cognitive_comp/ganruyi/Megatron/:/cognitive_comp/ganruyi/Megatron/,/cognitive_comp/gaoxinyu/:/cognitive_comp/gaoxinyu/ $SINGULARITY_PATH python $CMD
# to debug - add echo (it exits and prints what it would have launched)
#run_cmd="$PY_LAUNCHER $CMD"
# srun --nodes=1 --gres=gpu:4 --ntasks-per-node=4 --cpus-per-gpu=20
source activate
conda activate torchnew
srun --nodes=1 --ntasks-per-node=1 --gres=gpu:1 --cpus-per-task=30 -o ${MODEL_NAME}-%J.log --jobid=229623 bash -c 'python3 $SCRIPT_PATH $CMD'
|