SirStone
82eeb53e5c
- generalist_train.sh: CHUNK_SIZE 60→20 for faster opponent cycling - generalist_train.sh: EVAL_ROUNDS 30→50 for more reliable eval - training.env: TRAINING_ROUNDS→30000, removed hardcoded opponent - warm_start.py: TARGET_DIM=57 (already committed, ensure latest)
363 lines
15 KiB
Bash
Executable File
363 lines
15 KiB
Bash
Executable File
#!/usr/bin/env bash
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# generalist_train.sh — adaptive mixed-opponent training for a generalist PPO_Bot.
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#
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# Problem it solves: the sequential curriculum killed earlier skills (catastrophic
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# forgetting). Instead we sample ONE opponent per chunk, weighted by how weak the
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# bot currently is against it (max(FLOOR, 1 - winrate)), and keep the best
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# generalist checkpoint by mean eval winrate across all 8 opponents.
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#
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# State / logs (all plain files, resumable):
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# /tmp/generalist_wr.txt — one line per opponent: "Name winrate"
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# /tmp/generalist_seed.txt — optional starting winrates (same format);
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# wins over wr.txt when both exist
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# /tmp/generalist_best.txt — "mean rounds" of the best generalist eval so far
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# /tmp/generalist_train.log — full run log (tee'd)
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# /tmp/generalist_eval_<Opp>.jsonl — per-opponent eval battles (fresh per eval)
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# /tmp/generalist_train_<Opp>.jsonl — per-opponent training battles (accumulated)
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#
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# Env-overridable config: TOTAL_ROUNDS CHUNK_SIZE EVAL_INTERVAL EVAL_ROUNDS
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# PASS_RATE FLOOR ALPHA (all declared in the config block below).
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#
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# Usage:
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# ./generalist_train.sh — run the full training loop
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# ./generalist_train.sh --selftest — verify the weighted sampler against the
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# expected distribution (no battles, no compilation)
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#
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# Dead-bot resilience is inherited from the harness: RunTraining.java aborts
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# (exit 1) when PPO_Bot's round counter is frozen or short at battle end, and
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# this script retries; a chunk that makes no counter progress across 3 attempts
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# aborts loudly instead of silently burning rounds.
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set -uo pipefail
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export LC_ALL=C
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SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
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REPO_ROOT="$(cd "$SCRIPT_DIR/../.." && pwd)"
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PPO_BOT_SRC="$REPO_ROOT/PPO_Bot"
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ENV_FILE="$SCRIPT_DIR/training.env"
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[ -f "$ENV_FILE" ] && set -a && . "$ENV_FILE" && set +a
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JAR="${TANK_ROYALE_JAR:-/home/davide/Projects/tank-royale/runner/examples/lib/robocode-tankroyale-runner.jar}"
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export PPO_BOT_DIR="$PPO_BOT_SRC"
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export SAMPLE_BOTS_DIR="${SAMPLE_BOTS_DIR:-/home/davide/Projects/tank-royale/sample-bots/java/build/archive}"
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SNAPSHOTS_DIR="$SCRIPT_DIR/snapshots"
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mkdir -p "$SNAPSHOTS_DIR"
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ROUND_COUNTER_FILE="$PPO_BOT_SRC/weights/round_counter.txt"
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LOG="/tmp/generalist_train.log"
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WR_STATE_FILE="/tmp/generalist_wr.txt"
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WR_SEED_FILE="/tmp/generalist_seed.txt"
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BEST_FILE="/tmp/generalist_best.txt"
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SELFTEST_LOG="/tmp/generalist_sampling_selftest.log"
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# ── config (env-overridable) ──────────────────────────────────────────────────
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TOTAL_ROUNDS="${TOTAL_ROUNDS:-40000}"
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CHUNK_SIZE="${CHUNK_SIZE:-20}"
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EVAL_INTERVAL="${EVAL_INTERVAL:-1000}"
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EVAL_ROUNDS="${EVAL_ROUNDS:-50}"
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PASS_RATE="${PASS_RATE:-0.90}"
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FLOOR="${FLOOR:-0.05}" # minimum sampling weight — keeps maintenance sampling alive
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ALPHA="${ALPHA:-0.3}" # winrate EMA smoothing: new = ALPHA*old + (1-ALPHA)*eval
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OPPONENTS=(Fire MyFirstDroid Target MyFirstLeader Crazy Corners PaintingBot MyFirstBot)
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# ── helpers ───────────────────────────────────────────────────────────────────
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# read_counter — PPO_Bot's persisted round counter; robust to a mid-write read
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# (partial/empty file → 0 instead of a garbage/arithmetic error).
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read_counter() {
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local v=0
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[ -f "$ROUND_COUNTER_FILE" ] || { echo 0; return; }
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v=$(cat "$ROUND_COUNTER_FILE" 2>/dev/null || echo 0)
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case "$v" in
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''|*[!0-9]*) echo 0 ;;
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*) echo "$v" ;;
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esac
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}
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count_wins() {
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local f="$1"
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[ -f "$f" ] || { echo 0; return; }
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awk '/"win":true/{c++} END{print c+0}' "$f"
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}
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# sample_opponent — weighted draw: P(opp) ∝ max(FLOOR, 1 - winrate).
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# Cumulative distribution built in awk; random draw via awk's rand() seeded from
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# bash $RANDOM. Deterministic when $RANDOM is pre-seeded (the self-test relies on
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# this). Pass an explicit seed as $1 to override.
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sample_opponent() {
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local seed="${1:-$RANDOM}"
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awk -v seed="$seed" -v floor="$FLOOR" \
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-v names="${OPPONENTS[*]}" -v rates="${WR[*]}" '
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BEGIN {
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srand(seed);
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n = split(names, N, " ");
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split(rates, R, " ");
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total = 0;
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for (i = 1; i <= n; i++) {
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w = 1.0 - R[i] + 0.0;
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if (w < floor) w = floor;
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W[i] = w; total += w;
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}
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r = rand() * total;
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acc = 0;
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for (i = 1; i <= n; i++) {
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acc += W[i];
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if (r < acc) { print N[i]; exit }
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}
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print N[n];
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}'
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}
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# run_chunk <opponent> <rounds> [train|eval] — one battle chunk, with the
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# 3-attempt retry / loud-abort guard from curriculum_retrain.sh. Prints the
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# JSONL path on success; exits the script on a zero-progress chunk.
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run_chunk() {
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local opp="$1" want="$2" mode="${3:-train}"
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local logfile
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if [ "$mode" = "eval" ]; then
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logfile="/tmp/generalist_eval_${opp}.jsonl"
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> "$logfile" # fresh snapshot per eval
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export PPOB_EVAL_ONLY=1 # freeze training (pure evaluation)
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else
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logfile="/tmp/generalist_train_${opp}.jsonl"
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unset PPOB_EVAL_ONLY
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fi
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export TRAINING_OPPONENT="$opp"
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export TRAINING_ROUNDS="$want"
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export PPOB_LOG_FILE="$logfile"
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# Reset the counter so RunTraining's expected-end check (start+rounds) is exact.
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echo 0 > "$ROUND_COUNTER_FILE"
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local remaining="$want" attempts=0 done=0
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while [ "$remaining" -gt 0 ]; do
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attempts=$(( attempts + 1 ))
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[ "$attempts" -gt 1 ] && sleep 2
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# RunTraining.java exits 1 on its own when the counter is frozen ("process
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# dead") or short at battle end ("N rounds never trained ... aborting for
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# restart") — treat that as a retry signal, then re-check the counter.
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java -cp "$SCRIPT_DIR:$JAR" RunTraining "$opp" "$remaining" \
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|| echo ">>> Java exited non-zero (attempt $attempts/3) — crash/restart expected"
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done=$(read_counter)
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remaining=$(( want - done ))
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# Zero counter progress across 3 attempts = dead bot / broken harness.
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# The bot crashed constantly before; a crash must fail loudly now.
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if [ "$attempts" -ge 3 ] && [ "$done" -eq 0 ]; then
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echo "ERROR: round_counter still 0 after $attempts attempts vs $opp — aborting for restart" >&2
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exit 1
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fi
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done
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unset PPOB_EVAL_ONLY
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echo "$logfile"
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}
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persist_wr() {
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local i opp
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: > "$WR_STATE_FILE"
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for i in "${!OPPONENTS[@]}"; do
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printf "%s %.4f\n" "${OPPONENTS[$i]}" "${WR[$i]}" >> "$WR_STATE_FILE"
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done
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}
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load_wr() {
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local src=""
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if [ -f "$WR_SEED_FILE" ]; then
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src="$WR_SEED_FILE"
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echo ">>> Seeding winrates from $WR_SEED_FILE"
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elif [ -f "$WR_STATE_FILE" ]; then
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src="$WR_STATE_FILE"
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echo ">>> Loading winrates from $WR_STATE_FILE"
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else
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echo ">>> No winrate state — starting all at 1.0 (uniform floor sampling until first eval)"
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fi
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local -A from_file=()
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if [ -n "$src" ]; then
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local name val
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while read -r name val _; do
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[ -n "$name" ] || continue
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from_file[$name]="${val:-1.0}"
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done < "$src"
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fi
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local i opp
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for i in "${!OPPONENTS[@]}"; do
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opp="${OPPONENTS[$i]}"
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WR[$i]="${from_file[$opp]:-1.0}"
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done
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}
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load_best() {
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BEST_MEAN=0.0
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BEST_ROUNDS=0
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if [ -f "$BEST_FILE" ]; then
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read -r BEST_MEAN BEST_ROUNDS < "$BEST_FILE" || :
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[ -n "$BEST_MEAN" ] || BEST_MEAN=0.0
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[ -n "$BEST_ROUNDS" ] || BEST_ROUNDS=0
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echo ">>> Best-so-far: mean=$BEST_MEAN at round $BEST_ROUNDS"
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fi
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}
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snap_weights() {
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local rounds="$1"
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local dst="$SNAPSHOTS_DIR/generalist_best_r${rounds}"
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cp -a "$PPO_BOT_SRC/weights/latest" "$dst" # fresh dir per save (rounds strictly increase)
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echo " saved checkpoint -> $dst"
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}
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# do_eval <trained_rounds> — fresh battle per opponent, PPOB_EVAL_ONLY=1,
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# EVAL_ROUNDS each. Updates winrates (eval-only!) and the best generalist
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# checkpoint by mean winrate.
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do_eval() {
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local trained_rounds="$1"
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local i opp w logfile oldwr evwr newwr alert
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local total_wins=0
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local total_possible=$(( ${#OPPONENTS[@]} * EVAL_ROUNDS ))
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local mean
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echo ""
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echo "=== EVAL @ round $trained_rounds ==="
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for i in "${!OPPONENTS[@]}"; do
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opp="${OPPONENTS[$i]}"
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logfile=$(run_chunk "$opp" "$EVAL_ROUNDS" eval) || { echo " $opp: ERR"; continue; }
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w=$(count_wins "$logfile")
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total_wins=$(( total_wins + w ))
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evwr=$(awk -v w="$w" -v n="$EVAL_ROUNDS" 'BEGIN{printf "%.4f", w/n}')
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oldwr="${WR[$i]}"
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newwr=$(awk -v a="$ALPHA" -v o="$oldwr" -v e="$evwr" 'BEGIN{printf "%.4f", a*o + (1-a)*e}')
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WR[$i]="$newwr"
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persist_wr # state survives a crash mid-eval
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alert=""
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if awk -v e="$evwr" -v p="$PASS_RATE" 'BEGIN{exit !(e < p)}'; then
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alert=" <-- BELOW PASS_RATE $PASS_RATE"
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fi
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echo " $opp: $w/$EVAL_ROUNDS (wr $oldwr -> $newwr)$alert"
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done
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mean=$(awk -v n="${#OPPONENTS[@]}" -v rates="${WR[*]}" '
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BEGIN { split(rates, R, " "); s = 0; for (i = 1; i <= n; i++) s += R[i]; printf "%.4f", s / n }')
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echo " mean winrate: $mean (total $total_wins/$total_possible)"
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if awk -v m="$mean" -v b="$BEST_MEAN" 'BEGIN{exit !(m > b)}'; then
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BEST_MEAN="$mean"
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BEST_ROUNDS="$trained_rounds"
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snap_weights "$trained_rounds"
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printf '%s %s\n' "$BEST_MEAN" "$BEST_ROUNDS" > "$BEST_FILE"
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echo " >>> NEW BEST generalist: mean=$mean at $trained_rounds rounds"
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else
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echo " best remains: $BEST_MEAN at $BEST_ROUNDS rounds"
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fi
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}
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# ── self-test ─────────────────────────────────────────────────────────────────
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# Mock winrates: MyFirstBot 0.0, PaintingBot 0.1, 6 strong bots 1.0.
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# Weights: 1.0, 0.9, and 6x FLOOR 0.05 => total 2.2.
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# Expected: MyFirstBot 1.0/2.2=45.5%, PaintingBot 40.9%, each strong 2.27%.
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selftest() {
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local rc=0 i opp d frac
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local -A draws=()
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WR=(1.0 1.0 1.0 1.0 1.0 1.0 0.1 0.0) # order matches OPPONENTS
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RANDOM=12345 # fixed seed -> reproducible draws
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for ((i = 0; i < 10000; i++)); do
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opp=$(sample_opponent)
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draws[$opp]=$(( ${draws[$opp]:-0} + 1 ))
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done
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echo "=== sampling self-test: 10000 draws, seed RANDOM=12345 ==="
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echo "mock winrates: MyFirstBot 0.0, PaintingBot 0.1, strong x6 1.0"
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echo "weights -> MyFirstBot 1.0, PaintingBot 0.9, strong 0.05 each (total 2.2)"
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echo ""
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echo "actual draw distribution:"
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for opp in "${OPPONENTS[@]}"; do
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d=${draws[$opp]:-0}
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frac=$(awk -v d="$d" 'BEGIN{printf "%.4f", d/10000}')
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printf " %-14s %5d draws (share %.4f)\n" "$opp" "$d" "$frac"
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done
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echo ""
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local mfb
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mfb=$(awk -v d="${draws[MyFirstBot]:-0}" 'BEGIN{printf "%.4f", d/10000}')
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assert_range() {
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# assert_range <name> <frac> <lo> <hi>
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if awk -v f="$2" -v lo="$3" -v hi="$4" 'BEGIN{exit !(f >= lo && f <= hi)}'; then
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echo " OK $1 share $2 in [$3,$4]"
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else
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echo " FAIL $1 share $2 not in [$3,$4]"; rc=1
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fi
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}
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assert_range "MyFirstBot (weak focus)" "$mfb" 0.35 0.50
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for opp in Fire MyFirstDroid Target MyFirstLeader Crazy Corners; do
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frac=$(awk -v d="${draws[$opp]:-0}" 'BEGIN{printf "%.4f", d/10000}')
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assert_range "$opp maintenance" "$frac" 0.015 0.05
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done
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echo ""
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[ "$rc" -eq 0 ] && echo "SELF-TEST PASS" || echo "SELF-TEST FAIL"
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exit "$rc"
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}
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# ── main training loop ────────────────────────────────────────────────────────
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main() {
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echo "=== PPO_Bot generalist mixed training — $(date) ==="
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echo "Config: TOTAL_ROUNDS=$TOTAL_ROUNDS CHUNK_SIZE=$CHUNK_SIZE EVAL_INTERVAL=$EVAL_INTERVAL EVAL_ROUNDS=$EVAL_ROUNDS PASS_RATE=$PASS_RATE FLOOR=$FLOOR ALPHA=$ALPHA"
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echo "Opponents: ${OPPONENTS[*]}"
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echo ">>> Compiling PPO_Bot..."
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(cd "$PPO_BOT_SRC" && nimble build -d:release) || { echo "ERROR: PPO_Bot build failed" >&2; exit 1; }
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echo ">>> Compiling RunTraining.java..."
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(cd "$SCRIPT_DIR" && javac -cp "$JAR" RunTraining.java) || { echo "ERROR: RunTraining compile failed" >&2; exit 1; }
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echo ">>> Compilation done."
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# ── tmux-friendly session header ────────────────────────────────────────────
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echo ""
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echo "┌─────────────────────────────────────────────────────────────────┐"
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printf "│ Start time : %-48s│\n" "$(date '+%Y-%m-%d %H:%M:%S %Z')"
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printf "│ Total rounds : %-48s│\n" "$TOTAL_ROUNDS"
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printf "│ Chunk size : %-48s│\n" "$CHUNK_SIZE ($(( TOTAL_ROUNDS / CHUNK_SIZE )) chunks total)"
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printf "│ Eval interval: %-48s│\n" "every $EVAL_INTERVAL rounds ($(( TOTAL_ROUNDS / EVAL_INTERVAL )) evals planned)"
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printf "│ Eval rounds : %-48s│\n" "$EVAL_ROUNDS per opponent ($(( ${#OPPONENTS[@]} * EVAL_ROUNDS )) max wins)"
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printf "│ Opponents : %-48s│\n" "${#OPPONENTS[@]} bots"
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echo "└─────────────────────────────────────────────────────────────────┘"
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echo ""
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load_best
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load_wr
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persist_wr # materialize state now so an early crash still leaves a readable file
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# fresh per-run train JSONLs; cross-chunk state lives in the wr/best files
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local opp
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for opp in "${OPPONENTS[@]}"; do
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: > "/tmp/generalist_train_${opp}.jsonl"
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done
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local trained_rounds=0 chunk_rounds=0
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while [ "$trained_rounds" -lt "$TOTAL_ROUNDS" ]; do
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chunk_rounds=$CHUNK_SIZE
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if [ $(( trained_rounds + CHUNK_SIZE )) -gt "$TOTAL_ROUNDS" ]; then
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chunk_rounds=$(( TOTAL_ROUNDS - trained_rounds ))
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fi
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opp=$(sample_opponent)
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echo ""
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echo "Chunk $trained_rounds: $opp ($chunk_rounds rounds expected)"
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run_chunk "$opp" "$chunk_rounds" train || :
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trained_rounds=$(( trained_rounds + chunk_rounds ))
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if [ $(( trained_rounds % EVAL_INTERVAL )) -eq 0 ]; then
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do_eval "$trained_rounds"
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fi
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done
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# final eval at the very end (skip when the loop already evaluated at TOTAL_ROUNDS)
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if [ $(( TOTAL_ROUNDS % EVAL_INTERVAL )) -ne 0 ]; then
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echo ""
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echo "=== FINAL eval — $(date) ==="
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do_eval "$trained_rounds"
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fi
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echo ""
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echo "=== generalist training complete — $(date) ==="
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echo "Final winrates in $WR_STATE_FILE"
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echo "Best generalist checkpoint: $SNAPSHOTS_DIR/generalist_best_r${BEST_ROUNDS} (mean=$BEST_MEAN at $BEST_ROUNDS rounds)"
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}
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if [ "${1:-}" = "--selftest" ]; then
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selftest 2>&1 | tee "$SELFTEST_LOG"
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exit "${PIPESTATUS[0]}"
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fi
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main "$@" 2>&1 | tee -a "$LOG"
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exit "${PIPESTATUS[0]}" |