60 lines
1.7 KiB
Bash
60 lines
1.7 KiB
Bash
#! /bin/bash
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#SBATCH --nodes=1
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#SBATCH --ntasks-per-node=8
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#SBATCH --gres=gpu:8
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#SBATCH --cpus-per-task=8
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# use 8 GPU for example, pretrain may need 32 GPU
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export MASTER_ADDR=`hostname`
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export MASTER_PORT=12345
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mkdir -p /home/${USERNAME}/logs/debug
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mkdir -p /home/${USERNAME}/logs/tensorboard/cpm9g/
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cd apps/cpm9g
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CONFIG_NAME="config/7b"
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# --------------- 运行参数 ---------------
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OPTS=""
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OPTS+=" --model-config ${CONFIG_NAME}/config.json"
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OPTS+=" --vocab ${CONFIG_NAME}/vocab.txt"
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OPTS+=" --batch-size 4"
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OPTS+=" --train-iters 400000"
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OPTS+=" --save-iters 250"
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OPTS+=" --save-name cpm9g_checkpoint"
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OPTS+=" --max-length 4096"
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OPTS+=" --lr 1.5e-5"
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OPTS+=" --inspect-iters 100"
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OPTS+=" --warmup-iters 2000"
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OPTS+=" --lr-decay-style noam"
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OPTS+=" --weight-decay 0.1"
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OPTS+=" --clip-grad 1.0"
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OPTS+=" --loss-scale 1048576"
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OPTS+=" --loss-scale-steps 32"
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OPTS+=" --offload"
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OPTS+=" --flash cuda"
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# OPTS+=" --load-grad"
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# --------------- 写文件路径 ---------------
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## checkpoint
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OPTS+=" --save /home/${USERNAME}/checkpoints/cpm9g/"
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OPTS+=" --save-model /home/${USERNAME}/models/cpm9g/"
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## logs，/local/logs 等价于 /data/logs（软链）
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OPTS+=" --log-dir /home/${USERNAME}/logs/train/"
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OPTS+=" --tensorboard /home/${USERNAME}/tensorboard/cpm9g/"`date +"%Y%m%d%H%M%S"`
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# --------------- 读文件路径 ---------------
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OPTS+=" --dataset config/datasets.json"
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OPTS+=" --load ${CHECKPOINT}"
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OPTS+=" --start-step 1"
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# --------------- 透传参数 ---------------
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OPTS+=" $@"
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# --------------- 最终指令 ---------------
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CMD="torchrun --nnodes=1 --nproc_per_node=8 --rdzv_id=1 --rdzv_backend=c10d --rdzv_endpoint=${MASTER_ADDR}:${MASTER_PORT} pretrain_cpm9g.py ${OPTS}"
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echo "${CMD}"
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$CMD
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