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typo; add pretrain slurm job file

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Starbeamrainbowlabs 2022-08-31 16:32:17 +01:00
parent e0162bc70b
commit dbf929325a
Signed by: sbrl
GPG key ID: 1BE5172E637709C2
2 changed files with 69 additions and 1 deletions
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68
aimodel/slurm-pretrain.job Normal file
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@ -0,0 +1,68 @@
#!/usr/bin/env bash
#SBATCH -J TweetAI
#SBATCH -N 1
#SBATCH -n 4
#SBATCH --gres=gpu:1
#SBATCH -o %j.%N.%a.out
#SBATCH -e %j.%N.%a.err
#SBATCH -p gpu05
#SBATCH --time=5-00:00:00
#SBATCH --exclusive
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>'] sbatch slurm-pretrain.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;
}
CONFIG="${CONFIG:-configs/clip.toml}";
if [[ -z "${CONFIG}" ]]; then
echo -e "Error: No CONFIG 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="$(basename "${CONFIG}")";
CODE="${CODE%.*}";
if [[ -n "${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:$PATH;
echo ">>> Installing requirements";
conda run -n py38 pip install -r requirements.txt;
echo ">>> Training model";
#shellcheck disable=SC2086
/usr/bin/env time -v conda run -n py38 src/index.py --input "${CONFIG}" --output "${dir_output}" ${ARGS};
echo ">>> exited with code $?";

2
aimodel/src/subcommands/pretrain.py
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@ -15,7 +15,7 @@ def parse_args():
parser.add_argument("--output", "-o", help="Path to output directory to write output to (will be automatically created if it doesn't exist)", required=True) parser.add_argument("--output", "-o", help="Path to output directory to write output to (will be automatically created if it doesn't exist)", required=True)
parser.add_argument("--feature-dim", help="The size of the output feature dimension of the model [default: 200].", type=int) parser.add_argument("--feature-dim", help="The size of the output feature dimension of the model [default: 200].", type=int)
parser.add_argument("--batch-size", help="Sets the batch size [default: 64].", type=int) parser.add_argument("--batch-size", help="Sets the batch size [default: 64].", type=int)
parser.add_argument("--reads-multiplier", help="Optional. The multiplier for the number of files we should read from at once. Defaults to 1.5, which means read ceil(NUMBER_OF_CORES * 1.5). Set to a higher number of systems with high read latency to avoid starving the GPU of data.") parser.add_argument("--reads-multiplier", help="Optional. The multiplier for the number of files we should read from at once. Defaults to 1.5, which means read ceil(NUMBER_OF_CORES * 1.5) files at once. Set to a higher number of systems with high read latency to avoid starving the GPU of data.")
return parser return parser