launchers

This commit is contained in:
Robin Rombach 2022-07-28 00:12:03 +02:00
parent 80454667da
commit bf36d63fa6
4 changed files with 138 additions and 0 deletions

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#!/bin/bash
# mpi version for node rank
H=`hostname`
THEID=`echo -e $HOSTNAMES | python3 -c "import sys;[sys.stdout.write(str(i)) for i,line in enumerate(next(sys.stdin).split(' ')) if line.strip() == '$H'.strip()]"`
export NODE_RANK=${THEID}
echo THEID=$THEID
echo "##########################################"
echo MASTER_ADDR=${MASTER_ADDR}
echo MASTER_PORT=${MASTER_PORT}
echo NODE_RANK=${NODE_RANK}
echo WORLD_SIZE=${WORLD_SIZE}
echo "##########################################"
# debug environment worked great so we stick with it
# no magic there, just a miniconda python=3.9, pytorch=1.12, cudatoolkit=11.3
# env with pip dependencies from stable diffusion's requirements.txt
eval "$(/fsx/stable-diffusion/debug/miniconda3/bin/conda shell.bash hook)"
conda activate torch111
cd /fsx/robin/stable-diffusion/stable-diffusion
CONFIG="/fsx/robin/stable-diffusion/stable-diffusion/configs/stable-diffusion/upscaling/upscale-v1-with-f16.yaml"
# debugging
#EXTRA="${EXTRA} -d True lightning.callbacks.image_logger.params.batch_frequency=50"
python main.py --base $CONFIG --gpus 0,1,2,3,4,5,6,7 -t --num_nodes ${WORLD_SIZE} --scale_lr False #$EXTRA

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#!/bin/bash
#SBATCH --partition=compute-od-gpu
#SBATCH --job-name=stable-diffusion-v1-upscaling-f16-pretraining-512-aesthetics
#SBATCH --nodes 8
#SBATCH --ntasks-per-node 1
#SBATCH --cpus-per-gpu=4
#SBATCH --gres=gpu:8
#SBATCH --exclusive
#SBATCH --output=%x_%j.out
#SBATCH --comment "Key=Monitoring,Value=ON"
module load intelmpi
source /opt/intel/mpi/latest/env/vars.sh
export LD_LIBRARY_PATH=/opt/aws-ofi-nccl/lib:/opt/amazon/efa/lib64:/usr/local/cuda-11.0/efa/lib:/usr/local/cuda-11.0/lib:/usr/local/cuda-11.0/lib64:/usr/local/cuda-11.0:/opt/nccl/build/lib:/opt/aws-ofi-nccl-inst
all/lib:/opt/aws-ofi-nccl/lib:$LD_LIBRARY_PATH
export NCCL_PROTO=simple
export PATH=/opt/amazon/efa/bin:$PATH
export LD_PRELOAD="/opt/nccl/build/lib/libnccl.so"
export FI_EFA_FORK_SAFE=1
export FI_LOG_LEVEL=1
export FI_EFA_USE_DEVICE_RDMA=1 # use for p4dn
export NCCL_DEBUG=info
export PYTHONFAULTHANDLER=1
export CUDA_LAUNCH_BLOCKING=0
export OMPI_MCA_mtl_base_verbose=1
export FI_EFA_ENABLE_SHM_TRANSFER=0
export FI_PROVIDER=efa
export FI_EFA_TX_MIN_CREDITS=64
export NCCL_TREE_THRESHOLD=0
# sent to sub script
export HOSTNAMES=`scontrol show hostnames "$SLURM_JOB_NODELIST"`
export MASTER_ADDR=$(scontrol show hostnames "$SLURM_JOB_NODELIST" | head -n 1)
export MASTER_PORT=12802
export COUNT_NODE=`scontrol show hostnames "$SLURM_JOB_NODELIST" | wc -l`
export WORLD_SIZE=$COUNT_NODE
echo go $COUNT_NODE
echo $HOSTNAMES
echo $WORLD_SIZE
mpirun -n $COUNT_NODE -perhost 1 /fsx/robin/stable-diffusion/stable-diffusion/scripts/slurm/v1-upscaling-f16-pretraining-512-aesthetics/launcher.sh

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#!/bin/bash
# mpi version for node rank
H=`hostname`
THEID=`echo -e $HOSTNAMES | python3 -c "import sys;[sys.stdout.write(str(i)) for i,line in enumerate(next(sys.stdin).split(' ')) if line.strip() == '$H'.strip()]"`
export NODE_RANK=${THEID}
echo THEID=$THEID
echo "##########################################"
echo MASTER_ADDR=${MASTER_ADDR}
echo MASTER_PORT=${MASTER_PORT}
echo NODE_RANK=${NODE_RANK}
echo WORLD_SIZE=${WORLD_SIZE}
echo "##########################################"
# debug environment worked great so we stick with it
# no magic there, just a miniconda python=3.9, pytorch=1.12, cudatoolkit=11.3
# env with pip dependencies from stable diffusion's requirements.txt
eval "$(/fsx/stable-diffusion/debug/miniconda3/bin/conda shell.bash hook)"
conda activate torch111
cd /fsx/robin/stable-diffusion/stable-diffusion
CONFIG="/fsx/robin/stable-diffusion/stable-diffusion/configs/stable-diffusion/inpainting/v1-finetune-for-inpainting-laion-aesthetic-larger-masks.yaml"
# debugging
#EXTRA="${EXTRA} -d True lightning.callbacks.image_logger.params.batch_frequency=50"
python main.py --base $CONFIG --gpus 0,1,2,3,4,5,6,7 -t --num_nodes ${WORLD_SIZE} --scale_lr False

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#!/bin/bash
#SBATCH --partition=compute-od-gpu
#SBATCH --job-name=stable-diffusion-v1-v1_inpainting_aesthetics-larger-masks
#SBATCH --nodes 24
#SBATCH --ntasks-per-node 1
#SBATCH --cpus-per-gpu=4
#SBATCH --gres=gpu:8
#SBATCH --exclusive
#SBATCH --output=%x_%j.out
#SBATCH --comment "Key=Monitoring,Value=ON"
module load intelmpi
source /opt/intel/mpi/latest/env/vars.sh
export LD_LIBRARY_PATH=/opt/aws-ofi-nccl/lib:/opt/amazon/efa/lib64:/usr/local/cuda-11.0/efa/lib:/usr/local/cuda-11.0/lib:/usr/local/cuda-11.0/lib64:/usr/local/cuda-11.0:/opt/nccl/build/lib:/opt/aws-ofi-nccl-inst
all/lib:/opt/aws-ofi-nccl/lib:$LD_LIBRARY_PATH
export NCCL_PROTO=simple
export PATH=/opt/amazon/efa/bin:$PATH
export LD_PRELOAD="/opt/nccl/build/lib/libnccl.so"
export FI_EFA_FORK_SAFE=1
export FI_LOG_LEVEL=1
export FI_EFA_USE_DEVICE_RDMA=1 # use for p4dn
export NCCL_DEBUG=info
export PYTHONFAULTHANDLER=1
export CUDA_LAUNCH_BLOCKING=0
export OMPI_MCA_mtl_base_verbose=1
export FI_EFA_ENABLE_SHM_TRANSFER=0
export FI_PROVIDER=efa
export FI_EFA_TX_MIN_CREDITS=64
export NCCL_TREE_THRESHOLD=0
# sent to sub script
export HOSTNAMES=`scontrol show hostnames "$SLURM_JOB_NODELIST"`
export MASTER_ADDR=$(scontrol show hostnames "$SLURM_JOB_NODELIST" | head -n 1)
export MASTER_PORT=12802
export COUNT_NODE=`scontrol show hostnames "$SLURM_JOB_NODELIST" | wc -l`
export WORLD_SIZE=$COUNT_NODE
echo go $COUNT_NODE
echo $HOSTNAMES
echo $WORLD_SIZE
mpirun -n $COUNT_NODE -perhost 1 /fsx/robin/stable-diffusion/stable-diffusion/scripts/slurm/v1_inpainting_aesthetics-larger-masks/launcher.sh