File size: 4,720 Bytes
3b2d368 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 | #!/bin/bash
# Optional arguments [MODEL_NAME] [NUM_GPUS] [NUM_NODES]
NUM_GPUS=${1:-4} # default 4 GPUs per node
NUM_NODES=${2:-1} # default 1 node
# Clear first 2 args to avoid hydra issues
shift 2
# CPUs and memory automatically determined
CPUS_PER_TASK=8 # 8 CPUs per GPU
TOTAL_CPUS=$((NUM_GPUS * CPUS_PER_TASK))
TOTAL_MEM=$((NUM_GPUS * 32)) # 32gb ram per GPU
# Extract model name from hydra overrides
MODEL_NAME="transformer"
for arg in "$@"; do
if [[ "$arg" == model=* ]]; then
MODEL_NAME="${arg#model=}"
break
fi
done
JOB_NAME="${MODEL_NAME}_train_medium"
DATE=$(date +%F)
echo "Launching training job: $JOB_NAME"
echo "Nodes: ${NUM_NODES}, GPUs per node: ${NUM_GPUS}"
echo "Resources per node: ${TOTAL_CPUS} CPUs, ${TOTAL_MEM} GB memory"
SBATCH_ARGS="--job-name=${JOB_NAME} \
--nodes=${NUM_NODES} \
--gres=gpu:h200:${NUM_GPUS} \
--ntasks-per-node=${NUM_GPUS} \
--cpus-per-task=${CPUS_PER_TASK} \
--mem=${TOTAL_MEM}G \
--output=../../logs/${MODEL_NAME}/${DATE}/%x-%j.out \
--error=../../logs/${MODEL_NAME}/${DATE}/%x-%j.err"
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_1_3b.sh \
# size=1_3b \
# training=1_3b \
# dataset=tinygsm_resume \
# "$@"
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_353M.sh \
# size=medium \
# training=medium \
# dataset=tinygsm_resume \
# "$@" \
# model=transformer_1_3B
# cp /work/jf381/code/lm-research/main_1_2.py /work/jf381/code/lm-research/main.py
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_353M_bert.sh \
# size=medium \
# training=medium \
# dataset=tinygsm \
# "$@" \
# model=transformer_353M_bert
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_353M_bert.sh \
# size=medium \
# training=medium \
# dataset=slimpajama_6b \
# training.lr=2e-6 \
# "$@" \
# model=transformer_353M_bert
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_353M_bert1.sh \
# size=medium \
# training=medium \
# dataset=slimpajama_6b \
# training.lr=2e-6 \
# "$@" \
# model=transformer_353M_bert
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_353M_bert2.sh \
# size=medium \
# training=medium \
# dataset=slimpajama_6b \
# training.lr=2e-6 \
# "$@" \
# model=transformer_353M_bert
# bert_pretrain
# ork/jf381/code/lm-research/main_1_2.py /work/jf381/code/lm-research/main.py
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_353M_bert.sh \
# size=medium \
# training=medium \
# dataset=slimpajama_6b \
# "$@" \
# model=transformer_353M_bert
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_1_3B.sh \
# size=medium \
# training=medium \
# dataset=tinygsm_resume \
# "$@" \
# model=transformer_1_3B
# cp /work/jf381/code/lm-research/main_1_7.py /work/jf381/code/lm-research/main.py
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_1_3B.sh \
# size=1_3b \
# training=1_3b \
# dataset=tinygsm_resume \
# "$@" \
# model=fst_1_3B
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_353M.sh \
# size=medium \
# training=medium \
# dataset=tinygsm_resume \
# "$@" \
# model=fst_353M
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_353M.sh \
# size=1_3b \
# training=1_3b \
# dataset=tinygsm_resume \
# "$@" \
# model=fst_1_3B
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_353M.sh \
# size=medium \
# training=medium \
# dataset=tinygsm_resume \
# "$@" \
# model=transformer_353M
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_1_3b.sh \
# size=1_3b \
# training=1_3b \
# dataset=tinygsm_resume \
# "$@"
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_generate.sh \
# size=medium \
# training=medium \
# dataset=tinygsm_resume \
# "$@"
## left_small 02-
## 04 big-
## 03 fst big
# # cat << 'EOF' > 1_3b_transformer.txt
# bash /work/jf381/code/lm-research/scripts/jobs/run_job_h200_bash_resume_transformer_1_3b_generate.sh \
# size=1_3b \
# training=1_3b \
# dataset=tinygsm_resume \
# "$@"
# EOF |