358 lines
9.4 KiB
Bash
358 lines
9.4 KiB
Bash
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#!/usr/bin/env bash
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#
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# Re-run the key DeepHealth experiments with additional random seeds.
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#
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# The selected configurations form a compact evidence chain:
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# 1. FFN + next_token + absolute + exponential
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# Delphi2M reproduction baseline.
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# 2. FFN + all_future + absolute + exponential
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# Isolates the target change from next_token to all_future.
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# 3. TrajMixer + all_future + absolute + exponential
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# Isolates the architecture change from FFN to TrajMixer.
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# 4. TrajMixer + all_future + relative + exponential
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# Isolates the time-mode change and is the current disease-best candidate.
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# 5. TrajMixer + all_future + relative + Weibull
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# Unified disease/death candidate.
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# 6. FFN + all_future + relative + Weibull
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# Current mortality-best control and matched architecture comparison for (5).
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#
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# Each task uses one GPU. Tasks assigned to the same GPU run sequentially,
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# while different GPUs run in parallel.
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#
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# Examples:
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# bash train_key_models_multiseed_linux.sh --gpus 0,1,2,3
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# bash train_key_models_multiseed_linux.sh --gpus 0,1 --seeds 43,44
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#
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set -uo pipefail
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SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
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cd "$SCRIPT_DIR"
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GPU_CSV=""
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SEED_CSV="43,44,45"
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NUM_WORKERS=4
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PYTHON_BIN="${PYTHON_BIN:-python}"
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CAMPAIGN_NAME="key_models_multiseed_smoking_alcohol_bmi"
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DRY_RUN=0
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BATCH_SIZE=256
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EXTRA_INFO_TYPES_FILE="$SCRIPT_DIR/extra_info_types_smoking_alcohol_bmi.txt"
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usage() {
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cat <<'EOF'
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Usage:
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bash train_key_models_multiseed_linux.sh --gpus GPU_LIST [options]
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Required:
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--gpus LIST Comma-separated GPU ids, for example 0,1,2,3.
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Options:
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--seeds LIST Additional seeds (default: 43,44,45).
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Use 43,44 for two additional seeds.
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--num-workers N DataLoader workers per task (default: 4).
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--python PATH Python executable (default: $PYTHON_BIN or python).
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--campaign NAME Output campaign name.
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--dry-run Print all commands without running them.
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-h, --help Show this help message.
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Fixed experiment settings:
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batch_size 256
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extra_info_types extra_info_types_smoking_alcohol_bmi.txt
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model size Defaults from the training entrypoints
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tasks per seed 6
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Outputs:
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runs/<campaign>/seed_<seed>/<architecture>/...
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batch_logs/<campaign>/seed_<seed>/<job>.log
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EOF
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}
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while (($# > 0)); do
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case "$1" in
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--gpus)
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[[ $# -ge 2 ]] || {
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echo "ERROR: --gpus requires a value." >&2
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exit 2
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}
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GPU_CSV="$2"
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shift 2
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;;
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--seeds)
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[[ $# -ge 2 ]] || {
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echo "ERROR: --seeds requires a value." >&2
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exit 2
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}
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SEED_CSV="$2"
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shift 2
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;;
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--num-workers)
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[[ $# -ge 2 ]] || {
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echo "ERROR: --num-workers requires a value." >&2
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exit 2
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}
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NUM_WORKERS="$2"
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shift 2
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;;
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--python)
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[[ $# -ge 2 ]] || {
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echo "ERROR: --python requires a value." >&2
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exit 2
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}
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PYTHON_BIN="$2"
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shift 2
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;;
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--campaign)
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[[ $# -ge 2 ]] || {
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echo "ERROR: --campaign requires a value." >&2
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exit 2
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}
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CAMPAIGN_NAME="$2"
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shift 2
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;;
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--dry-run)
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DRY_RUN=1
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shift
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;;
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-h|--help)
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usage
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exit 0
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;;
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*)
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echo "ERROR: unknown argument: $1" >&2
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usage >&2
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exit 2
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;;
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esac
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done
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[[ -n "$GPU_CSV" ]] || {
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echo "ERROR: --gpus is required." >&2
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usage >&2
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exit 2
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}
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[[ -n "$SEED_CSV" ]] || {
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echo "ERROR: --seeds must not be empty." >&2
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exit 2
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}
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[[ "$NUM_WORKERS" =~ ^[0-9]+$ ]] || {
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echo "ERROR: --num-workers must be a non-negative integer." >&2
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exit 2
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}
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[[ "$CAMPAIGN_NAME" =~ ^[A-Za-z0-9._-]+$ ]] || {
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echo "ERROR: --campaign may contain only letters, numbers, ., _, and -." >&2
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exit 2
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}
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[[ -f "$EXTRA_INFO_TYPES_FILE" ]] || {
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echo "ERROR: missing extra-info file: $EXTRA_INFO_TYPES_FILE" >&2
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exit 2
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}
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command -v "$PYTHON_BIN" >/dev/null 2>&1 || {
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echo "ERROR: Python executable not found: $PYTHON_BIN" >&2
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exit 2
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}
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IFS=',' read -r -a GPU_IDS <<< "$GPU_CSV"
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declare -A SEEN_GPUS=()
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for gpu in "${GPU_IDS[@]}"; do
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[[ -n "$gpu" && "$gpu" =~ ^[A-Za-z0-9._:-]+$ ]] || {
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echo "ERROR: invalid GPU id: $gpu" >&2
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exit 2
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}
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[[ -z "${SEEN_GPUS[$gpu]+x}" ]] || {
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echo "ERROR: duplicate GPU id: $gpu" >&2
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exit 2
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}
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SEEN_GPUS["$gpu"]=1
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done
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IFS=',' read -r -a SEEDS <<< "$SEED_CSV"
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declare -A SEEN_SEEDS=()
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for seed in "${SEEDS[@]}"; do
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[[ "$seed" =~ ^[0-9]+$ ]] || {
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echo "ERROR: invalid seed: $seed" >&2
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exit 2
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}
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[[ -z "${SEEN_SEEDS[$seed]+x}" ]] || {
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echo "ERROR: duplicate seed: $seed" >&2
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exit 2
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}
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SEEN_SEEDS["$seed"]=1
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done
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RUNS_ROOT="$SCRIPT_DIR/runs/$CAMPAIGN_NAME"
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LOG_ROOT="$SCRIPT_DIR/batch_logs/$CAMPAIGN_NAME"
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if ((!DRY_RUN)); then
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mkdir -p "$RUNS_ROOT" "$LOG_ROOT"
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fi
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declare -a JOB_NAMES=()
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declare -a JOB_SEEDS=()
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declare -a JOB_ENTRYPOINTS=()
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declare -a JOB_ARCHITECTURES=()
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declare -a JOB_TIME_MODES=()
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declare -a JOB_DIST_MODES=()
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add_job() {
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JOB_NAMES+=("$1")
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JOB_SEEDS+=("$2")
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JOB_ENTRYPOINTS+=("$3")
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JOB_ARCHITECTURES+=("$4")
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JOB_TIME_MODES+=("$5")
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JOB_DIST_MODES+=("$6")
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}
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for seed in "${SEEDS[@]}"; do
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add_job \
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"ffn_next_token_absolute_exponential" \
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"$seed" \
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"train_next_step.py" \
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"transformer_ffn_v1" \
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"absolute" \
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"exponential"
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add_job \
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"ffn_all_future_absolute_exponential" \
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"$seed" \
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"train_all_future.py" \
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"transformer_ffn_v1" \
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"absolute" \
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"exponential"
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add_job \
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"traj_mixer_all_future_absolute_exponential" \
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"$seed" \
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"train_all_future.py" \
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"traj_mixer_v5" \
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"absolute" \
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"exponential"
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add_job \
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"traj_mixer_all_future_relative_exponential" \
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"$seed" \
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"train_all_future.py" \
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"traj_mixer_v5" \
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"relative" \
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"exponential"
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add_job \
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"traj_mixer_all_future_relative_weibull" \
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"$seed" \
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"train_all_future.py" \
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"traj_mixer_v5" \
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"relative" \
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"weibull"
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add_job \
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"ffn_all_future_relative_weibull" \
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"$seed" \
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"train_all_future.py" \
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"transformer_ffn_v1" \
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"relative" \
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"weibull"
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done
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print_command() {
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printf '%q ' "$@"
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printf '\n'
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}
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run_job() {
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local job_index="$1"
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local gpu="$2"
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local job_name="${JOB_NAMES[$job_index]}"
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local seed="${JOB_SEEDS[$job_index]}"
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local entrypoint="${JOB_ENTRYPOINTS[$job_index]}"
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local architecture="${JOB_ARCHITECTURES[$job_index]}"
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local time_mode="${JOB_TIME_MODES[$job_index]}"
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local dist_mode="${JOB_DIST_MODES[$job_index]}"
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local seed_runs_root="$RUNS_ROOT/seed_$seed"
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local seed_log_root="$LOG_ROOT/seed_$seed"
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local log_file="$seed_log_root/$job_name.log"
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local -a command=(
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"$PYTHON_BIN"
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-u
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"$SCRIPT_DIR/$entrypoint"
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--runs_root "$seed_runs_root"
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--seed "$seed"
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--batch_size "$BATCH_SIZE"
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--extra_info_types_file "$EXTRA_INFO_TYPES_FILE"
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--model_architecture "$architecture"
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--num_workers "$NUM_WORKERS"
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--device cuda
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)
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if ((!DRY_RUN)); then
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mkdir -p "$seed_runs_root" "$seed_log_root"
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fi
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if [[ "$entrypoint" == "train_all_future.py" ]]; then
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command+=(
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--time_mode "$time_mode"
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--dist_mode "$dist_mode"
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)
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fi
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echo "[$(date '+%F %T')] START seed=$seed job=$job_name gpu=$gpu"
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echo " log=$log_file"
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if ((DRY_RUN)); then
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printf ' CUDA_VISIBLE_DEVICES=%q ' "$gpu"
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print_command "${command[@]}"
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return 0
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fi
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if CUDA_VISIBLE_DEVICES="$gpu" PYTHONUNBUFFERED=1 \
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"${command[@]}" >"$log_file" 2>&1; then
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echo "[$(date '+%F %T')] DONE seed=$seed job=$job_name gpu=$gpu"
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return 0
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else
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local exit_code=$?
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echo "[$(date '+%F %T')] FAIL seed=$seed job=$job_name gpu=$gpu exit=$exit_code" >&2
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echo " See: $log_file" >&2
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return "$exit_code"
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fi
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}
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worker() {
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local slot="$1"
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local gpu="${GPU_IDS[$slot]}"
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local job_index
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local failed=0
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for ((job_index = slot; job_index < ${#JOB_NAMES[@]}; job_index += ${#GPU_IDS[@]})); do
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run_job "$job_index" "$gpu" || failed=1
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done
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return "$failed"
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}
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echo "Campaign: $CAMPAIGN_NAME"
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echo "Additional seeds: ${SEEDS[*]}"
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echo "GPUs: ${GPU_IDS[*]}"
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echo "Configurations per seed: 6"
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echo "Total tasks: ${#JOB_NAMES[@]}"
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echo "Runs root: $RUNS_ROOT"
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echo "Log root: $LOG_ROOT"
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echo
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declare -a WORKER_PIDS=()
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for ((slot = 0; slot < ${#GPU_IDS[@]}; slot++)); do
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worker "$slot" &
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WORKER_PIDS+=("$!")
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done
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overall_status=0
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for pid in "${WORKER_PIDS[@]}"; do
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wait "$pid" || overall_status=1
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done
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if ((overall_status != 0)); then
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echo "One or more training tasks failed. Inspect logs under: $LOG_ROOT" >&2
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exit 1
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fi
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if ((DRY_RUN)); then
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echo "Dry run completed successfully."
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else
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echo "All training tasks completed successfully."
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fi
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