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#!/bin/bash
#SBATCH --job-name=hf_ds_gpt2_multi_node
#SBATCH --nodes=2
#SBATCH --ntasks-per-node=1 # crucial - only 1 task per dist per node!
#SBATCH --cpus-per-task=40 # number of cores per tasks
#SBATCH --hint=nomultithread # we get physical cores not logical
#SBATCH --gres=gpu:4 # number of gpus
#SBATCH --time 20:00:00 # maximum execution time (HH:MM:SS)
#SBATCH --output=%x-%j.out # output file name
#SBATCH --error=%x-%j.out # error file name (same to watch just one file)
#SBATCH --account=six@gpu
GPUS_PER_NODE=4
NNODES=$SLURM_JOB_NUM_NODES
WORLD_SIZE=$(($GPUS_PER_NODE*$NNODES))
set -x -e
source $six_ALL_CCFRWORK/start-prod
cd $six_ALL_CCFRWORK/code/transformers
export PYTHONPATH=$six_ALL_CCFRWORK/code/transformers
MASTER_ADDR=$(scontrol show hostnames $SLURM_JOB_NODELIST | head -n 1)
MASTER_PORT=13370
export LAUNCHER=" \
python -u -m torch.distributed.launch \
--nproc_per_node $GPUS_PER_NODE \
--nnodes $NNODES \
--master_addr $MASTER_ADDR \
--master_port $MASTER_PORT \
"
MODEL=$six_ALL_CCFRWORK/models-custom/megatron-gpt2/megatron-gpt2-345m
DATASET="stas/openwebtext-10k"
export CMD=" \
`pwd`/examples/pytorch/language-modeling/run_clm.py \
--model_name_or_path $MODEL \
--dataset_name $DATASET \
--output_dir output_dir \
--overwrite_output_dir \
--do_train \
--do_eval \
--max_train_samples 1000 \
--max_eval_samples 200 \
--per_device_train_batch_size 4 \
--per_device_eval_batch_size 4 \
--num_train_epochs 1 \
--warmup_steps 8 \
--block_size 64 \
--fp16 \
--report_to none \
--deepspeed tests/deepspeed/ds_config_zero2.json \
"
export TRANSFORMERS_CACHE=$six_ALL_CCFRWORK/models
export HF_DATASETS_CACHE=$six_ALL_CCFRWORK/datasets
export HF_MODULES_CACHE=$six_ALL_CCFRWORK/modules
export HF_METRICS_CACHE=$six_ALL_CCFRWORK/metrics
export PYTHONPATH=src
export HF_DATASETS_OFFLINE=1
export TRANSFORMERS_OFFLINE=1
# to debug - add echo (it exits and prints what it would have launched)
srun bash -c '$LAUNCHER --node_rank $SLURM_PROCID $CMD'
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