add example sbatch script

Author: priyakasimbeg

scoring/utils/slurm/run_jobs.sh

@@ -0,0 +1,83 @@
+#!/bin/bash
+
+#SBATCH --nodes=1 # give it a full node
+#SBATCH --ntasks-per-node=1
+#SBATCH --array=<fill with range of items in config, e.g 0-7 >
+#SBATCH --partition=v100 
+#SBATCH --gpus-per-node=8
+#SBATCH --exclusive #this will not allow other jobs to run on this cluster
+#SBATCH --output=experiments/tests/jit_debug_deepspeech_old_stephint_nadamw/job_%A_%a.out
+#SBATCH --error=experiments/tests/jit_debug_deepspeech_old_stephint_nadamw/job_%A_%a.err
+
+# Usage: sbatch <this file>.sh
+# This script reads config.json and launches a sbatch job using task
+# arrays where each job in the array corresponds to a training run 
+# for a workload given a random seed and tuning trial index.
+# To generate the config.json use make_job_config.py.
+
+set -x
+
+# Pull docker image (ATTENTION: you may want to modify this)
+REPO=""
+IMAGE=""
+y | gcloud auth configure-docker $REPO
+docker pull $IMAGE
+# Job config (ATTENTION: you may want to modify this)
+config_file="" # Replace with your config file path
+LOGS_BUCKET="" # replace with your bucket used for logging
+
+
+# Function to read a JSON file and extract a value by key
+read_json_value() {
+  local json_file="$1"
+  local index="$2"
+  local key="$3"
+  local value=$(jq -r ".[\"$index\"].$key" "$json_file")
+  echo "$value"
+}
+
+# Check if jq is installed
+if ! command -v jq &> /dev/null
+then
+    echo "jq could not be found. Please install it."
+    exit 1
+fi
+
+TASK="$SLURM_ARRAY_TASK_ID"
+FRAMEWORK=$(read_json_value "$config_file" "$TASK" "framework")
+DATASET=$(read_json_value "$config_file" "$TASK" "dataset")
+SUBMISSION_PATH=$(read_json_value "$config_file" "$TASK" "submission_path")
+FRAMEWORK=$(read_json_value "$config_file" "$TASK" "framework")
+TUNING_SEARCH_SPACE=$(read_json_value "$config_file" "$TASK" "tuning_search_space")
+EXPERIMENT_DIR=$(read_json_value "$config_file" "$TASK" "experiment_dir")
+MAX_STEPS=$(read_json_value "$config_file" "$TASK" "max_steps")
+RNG_SEED=$(read_json_value "$config_file" "$TASK" "rng_seed")
+WORKLOAD=$(read_json_value "$config_file" "$TASK" "workload")
+HPARAM_START_INDEX=$(read_json_value "$config_file" "$TASK" "hparam_start_index")
+HPARAM_END_INDEX=$(read_json_value "$config_file" "$TASK" "hparam_end_index")
+NUM_TUNING_TRIALS=$(read_json_value "$config_file" "$TASK" "num_tuning_trials")
+TUNING_RULESET=$(read_json_value "$config_file" "$TASK" "tuning_ruleset")
+MAX_GLOBAL_STEPS=$(read_json_value "$config_file" "$MAX_GLOBAL_STEPS" "max_global_steps")
+
+docker run \
+  -v /opt/data/:/data/ \
+  -v $HOME/submissions_algorithms/:/algorithmic-efficiency/submissions_algorithms \
+  --gpus all \
+  --ipc=host \
+  $IMAGE \
+  -d $DATASET \
+  -f $FRAMEWORK \
+  -s $SUBMISSION_PATH \
+  -w $WORKLOAD \
+  -t $TUNING_SEARCH_SPACE \
+  -e $EXPERIMENT_DIR \
+  -c False \
+  -o True \
+  --rng_seed $RNG_SEED \
+  --hparam_start_index $HPARAM_START_INDEX \
+  --hparam_end_index $HPARAM_END_INDEX \
+  --num_tuning_trials $NUM_TUNING_TRIALS \
+  --tuning_ruleset $TUNING_RULESET \
+  --logs_bucket $LOGS_BUCKET \
+  -i true \
+  -r false