research-rainfallradar/aimodel/slurm-train.job

#!/usr/bin/env bash
#SBATCH -J RainAISG
#SBATCH -N 1
#SBATCH -n 14
#SBATCH --gres=gpu:1
#SBATCH -o %j.%N.%a.segment.out.log
#SBATCH -e %j.%N.%a.segment.err.log
#SBATCH -p gpu05
#SBATCH --time=5-00:00:00
#SBATCH --mem=51440
# 61440 = 60GiB memory required

module load utilities/multi
module load readline/7.0
module load gcc/10.2.0
module load cuda/11.5.0

module load python/anaconda/4.6/miniconda/3.7


show_help() {
	echo -e "Usage:" >&2;
	echo -e "    [INPUT='\$HOME/rainfallwater_records_tfrecord'] [POSTFIX='<string>'] [ARGS='<extra-args>'] sbatch slurm-train.job" >&2;
	echo -e "" >&2;
	echo -e "....where:" >&2;
	echo -e "    INPUT     The path to the directory containing the .tfrecord files to use as training data (see the rainfallwrangler for making these)" >&2;
	echo -e "    POSTFIX   Optional. A suffix to apply to the run code name." >&2;
	echo -e "" >&2;
	echo -e "The code used to identify the run is taken automatically from the filename of the config file." >&2;
	exit;
}
INPUT="${INPUT:-$HOME/PhD-Rainfall-Radar/aimodel/output/output/rainfallwater_records_embed_2022-10-06_contrast_embed_umap_d512e19_tfrecord}";

if [[ -z "${INPUT}" ]]; then
	echo -e "Error: No INPUT environment variable specified.\n" >&2;
	show_help;
	exit 0;
fi

if [[ ! -d "${INPUT}" ]]; then
	echo -e "Error: The directory '${INPUT}' containing the input .tfrecord dataset either doesn't exist or isn't a directory.";
	show_help;
	exit 1;
fi


CODE="train_segmenter";

if [[ -n "${POSTFIX}" ]]; then
	echo -e ">>> Applying postfix of ${POSTFIX}" >&2;
	CODE="${CODE}_${POSTFIX}";
fi

echo -e ">>> Input dirpath: ${INPUT}" >&2;
echo -e ">>> Code: ${CODE}" >&2;
echo -e ">>> Additional args: ${ARGS}";

dir_output="output/$(date -u --rfc-3339=date)_${CODE}";

export PATH=$HOME/software/bin:$PATH;

echo ">>> Installing requirements";
conda run -n py38 pip install -r requirements.txt;
echo ">>> Training model";
#shellcheck disable=SC2086
/usr/bin/env time -v conda run -n py38 src/index.py train --input "${INPUT}" --output "${dir_output}" ${ARGS};
src/index.py train --input "${INPUT}" -o "${dir_output}"
# Recommended extra args: --water-size 94 --batch-size 48 --arch convnext_i_xtiny

# Example used for raw testing:
# src/index.py train --input output/rainfallwater_records_embed_2022-10-06_contrast_embed_umap_d512e19_tfrecord_TINY -o output/2022-09-28-segmenter-d512e19-TEST-tiny --water-size 94 --batch-size 48 --arch convnext_i_xtiny
echo ">>> exited with code $?";