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#!/bin/bash
#SBATCH -A m4717
#SBATCH -J diffusion
#SBATCH -C gpu&hbm80g
#SBATCH -q regular #shared
#SBATCH -N1
#SBATCH --gpus-per-node=4
#SBATCH -t 10:00
#SBATCH --ntasks-per-node=1
#SBATCH -oReport-%j
#SBATCH --mail-type=BEGIN,END,FAIL
#SBATCH --gpu-bind=none
date
#module load anaconda3/2022.05 # Load module dependencies
module load pytorch #/2.0.1
#conda activate diffusers
which python
conda env list
module list
MASTER_ADDR=$(scontrol show hostnames $SLURM_JOB_NODELIST | head -n 1)
MASTER_PORT=$((10000 + RANDOM % 10000)) #12355
#export OMP_NUM_THREADS=1
export MASTER_ADDR=$MASTER_ADDR
export MASTER_PORT=$MASTER_PORT
export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
cat $0
srun python diffusion_test.py \
--num_image 16 \
--batch_size 2 \
--n_epoch 40 \
--channel_mult 1 1 2 2 4 4 \
--num_new_img_per_gpu 4 \
--max_num_img_per_gpu 2 \
--gradient_accumulation_steps 1 \
--autocast 1 \
--use_checkpoint 1 \
--dropout 0.1 \
--lrate 7e-5 \
--train "$SCRATCH/LEN128-DIM64-CUB16-Tvir[4, 6]-zeta[10, 250]-0809-123640.h5" \
#--resume ./outputs/model-N1600-device_count4-node4-epoch9-20051216 \
date
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