| #!/bin/bash |
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| set -u |
| CODE=$(cd "$(dirname "$0")" && pwd); ROOT=$(cd "$CODE/.." && pwd) |
| export BENCH_BASE=${BENCH_BASE:-$ROOT/data} |
| export P1_SAMPLES_DIR=${P1_SAMPLES_DIR:-$ROOT/items/samples} |
| export P1_RESULTS_ROOT=${P1_RESULTS_ROOT:-$ROOT/results} |
| export P1_MANIFEST=${P1_MANIFEST:-$ROOT/manifest/manifest_subset.jsonl} |
| mkdir -p "$BENCH_BASE/logs" "$P1_RESULTS_ROOT" "$ROOT/logs" |
| [ -d "$BENCH_BASE/store/normalized" ] || { echo "unpack the video shards into $BENCH_BASE/store/normalized first"; exit 2; } |
| PY=${PY:-python3}; VLLM=${VLLM:-vllm}; PORT0=${PORT0:-8011}; GPU_UTIL=${GPU_UTIL:-0.85}; MAX_SEQS=${MAX_SEQS:-32} |
| TOKEN_BUDGET=${TOKEN_BUDGET:-58000}; MAX_IMAGES=${MAX_IMAGES:-1024} |
| MODEL="Qwen/Qwen3-VL-8B-Instruct"; REV=0c351dd01ed87e9c1b53cbc748cba10e6187ff3b |
| CONDS=${CONDS:-v_blind,v_1,v_32,v_32_s448,v_32_s224,v_32_s168,v_32_s336,v_8_s224,v_128_s224,v_fps0.25_s224,v_fps0.5_s224,v_fps1_s224,v_fps2_s224} |
| RUNNER="$CODE/exp/pipeline/stage_p1_runner.py" |
| if [ "${PILOT:-0}" = "1" ]; then BENCH=${BENCH:-MVBench,LVBench,TimeScope}; fi |
| BENCH_ARG=(); [ -n "${BENCH:-}" ] && BENCH_ARG=(--bench "$BENCH") |
| if [ "${1:-}" = "--dry-run" ]; then |
| "$PY" "$RUNNER" --conditions "$CONDS" --endpoints http://127.0.0.1:1/v1 --token-budget "$TOKEN_BUDGET" --max-images "$MAX_IMAGES" "${BENCH_ARG[@]}" --dry-run; exit $? |
| fi |
| NGPU=${NGPU:-$(nvidia-smi -L 2>/dev/null | wc -l)}; [ "$NGPU" -ge 1 ] || { echo "no GPU found"; exit 2; } |
| WORKERS=${WORKERS:-$((6 * NGPU))} |
| export VLLM_USE_FLASHINFER_SAMPLER=0 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True TOKENIZERS_PARALLELISM=false |
| PIDS=(); EPS="" |
| for i in $(seq 0 $((NGPU - 1))); do |
| PORT=$((PORT0 + i)); EPS="${EPS:+$EPS,}http://127.0.0.1:$PORT/v1" |
| CUDA_VISIBLE_DEVICES=$i "$VLLM" serve "$MODEL" --revision "$REV" --served-model-name "$MODEL" --host 127.0.0.1 --port "$PORT" \ |
| --max-model-len 65536 --gpu-memory-utilization "$GPU_UTIL" --max-num-seqs "$MAX_SEQS" \ |
| --limit-mm-per-prompt "{\"image\": $MAX_IMAGES}" --mm-processor-cache-gb 0 \ |
| > "$ROOT/logs/vllm_gpu${i}.log" 2>&1 & |
| PIDS+=($!) |
| done |
| trap 'for p in "${PIDS[@]}"; do kill "$p" 2>/dev/null; done' EXIT |
| for i in $(seq 0 $((NGPU - 1))); do |
| PORT=$((PORT0 + i)) |
| for t in $(seq 1 180); do curl -sf "http://127.0.0.1:$PORT/v1/models" >/dev/null 2>&1 && break; kill -0 "${PIDS[$i]}" 2>/dev/null || { echo "vLLM on GPU $i died, see logs/vllm_gpu${i}.log"; exit 1; }; sleep 10; done |
| echo "[frames_pixels] vLLM ready on GPU $i (:$PORT)" |
| done |
| echo "[frames_pixels] launch: --max-model-len 65536 --limit-mm-per-prompt images=$MAX_IMAGES --max-num-seqs $MAX_SEQS --gpu-memory-utilization $GPU_UTIL; runner --token-budget $TOKEN_BUDGET --max-images $MAX_IMAGES --workers $WORKERS" | tee -a "$ROOT/logs/launch_params.txt" |
| "$PY" "$RUNNER" --conditions "$CONDS" --endpoints "$EPS" --workers "$WORKERS" --token-budget "$TOKEN_BUDGET" --max-images "$MAX_IMAGES" "${BENCH_ARG[@]}" 2>&1 | tee -a "$ROOT/logs/runner.log" |
| rc=${PIPESTATUS[0]} |
| echo "[frames_pixels] runner finished rc=$rc"; exit $rc |
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