add steps456_20260910/code/

fc5276f verified about 1 month ago

3.97 kB

#!/bin/bash
# run_remote.sh — run one pool screening step on a multi-GPU machine (no Slurm).
#   STEP=1 bash code/run_remote.sh            # run step 1 on every GPU (one vLLM server + one client shard per GPU)
#   STEP=2 bash code/run_remote.sh --plan-only   # show the remaining work of a step, no GPU used
# Env (optional): NGPU (default: nvidia-smi count), WORKERS (client threads per GPU; defaults per step),
#                 VLLM (default: vllm on PATH), PY (default: python3), PORT0 (default 8001), GPU_UTIL (default 0.85)
# Layout: this script lives in <package>/code/; items are read from <package>/results/pool/ (copy items/* there
# once), frames from <package>/frames/pool_frames/<video_id>/, outputs go to <package>/results/pool/step<N>/.
set -u
CODE=$(cd "$(dirname "$0")" && pwd); ROOT=$(cd "$CODE/.." && pwd)
export POOL_BASE=${POOL_BASE:-$ROOT/work_base}
export POOL_FRAMES_DIR=${POOL_FRAMES_DIR:-$ROOT/frames/pool_frames}
export POOL_RESULTS_ROOT=${POOL_RESULTS_ROOT:-$ROOT/results/pool}
mkdir -p "$POOL_BASE" "$POOL_RESULTS_ROOT" "$ROOT/logs"
PY=${PY:-python3}; VLLM=${VLLM:-vllm}; PORT0=${PORT0:-8001}; GPU_UTIL=${GPU_UTIL:-0.85}
STEPS_PY="$CODE/exp/analysis/pool/pool_steps.py"
STEP=${STEP:?set STEP=1..6}
case "$STEP" in
  1) MODEL="Qwen/Qwen3-VL-8B-Instruct"; REV=0c351dd01ed87e9c1b53cbc748cba10e6187ff3b; MAX_LEN=8192;  MAX_SEQS=64; MM_IMAGES=1;  WORKERS=${WORKERS:-32};;
  2) MODEL="Qwen/Qwen3-VL-8B-Instruct"; REV=0c351dd01ed87e9c1b53cbc748cba10e6187ff3b; MAX_LEN=8192;  MAX_SEQS=32; MM_IMAGES=1;  WORKERS=${WORKERS:-16};;
  3) MODEL="Qwen/Qwen3-VL-2B-Instruct"; REV=89644892e4d85e24eaac8bacfd4f463576704203; MAX_LEN=16384; MAX_SEQS=16; MM_IMAGES=32; WORKERS=${WORKERS:-8};;
  4) MODEL="Qwen/Qwen3-VL-8B-Instruct"; REV=0c351dd01ed87e9c1b53cbc748cba10e6187ff3b; MAX_LEN=8192;  MAX_SEQS=64; MM_IMAGES=1;  WORKERS=${WORKERS:-32};;
  5) MODEL="Qwen/Qwen3-VL-2B-Instruct"; REV=89644892e4d85e24eaac8bacfd4f463576704203; MAX_LEN=16384; MAX_SEQS=16; MM_IMAGES=32; WORKERS=${WORKERS:-8};;
  6) MODEL="Qwen/Qwen3-VL-8B-Instruct"; REV=0c351dd01ed87e9c1b53cbc748cba10e6187ff3b; MAX_LEN=16384; MAX_SEQS=16; MM_IMAGES=32; WORKERS=${WORKERS:-8};;
  *) echo "STEP must be 1..6"; exit 2;;
esac
[ ! -e "$POOL_RESULTS_ROOT/pool_items_base.parquet" ] && { echo "copy items/* into $POOL_RESULTS_ROOT first"; exit 2; }
if [ "${1:-}" = "--plan-only" ]; then "$PY" "$STEPS_PY" --step "$STEP" --plan-only --shard 0/1; exit $?; fi
NGPU=${NGPU:-$(nvidia-smi -L 2>/dev/null | wc -l)}
[ "$NGPU" -ge 1 ] || { echo "no GPU found"; exit 2; }
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+=("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 "$PORT" \
      --max-model-len "$MAX_LEN" --gpu-memory-utilization "$GPU_UTIL" --max-num-seqs "$MAX_SEQS" \
      --limit-mm-per-prompt "{\"image\": $MM_IMAGES}" --mm-processor-cache-gb 0 --max-logprobs 20 \
      > "$ROOT/logs/vllm_s${STEP}_gpu${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
  for t in $(seq 1 180); do curl -sf "${EPS[$i]}/models" >/dev/null 2>&1 && break; kill -0 "${PIDS[$i]}" 2>/dev/null || { echo "vLLM on GPU $i died, see logs/vllm_s${STEP}_gpu${i}.log"; exit 1; }; sleep 10; done
  echo "[run_remote] step $STEP: vLLM ready on GPU $i (${EPS[$i]})"
done
CPIDS=()
for i in $(seq 0 $((NGPU - 1))); do
  "$PY" "$STEPS_PY" --step "$STEP" --endpoint "${EPS[$i]}" --shard "$i/$NGPU" --workers "$WORKERS" \
      > "$ROOT/logs/client_s${STEP}_gpu${i}.log" 2>&1 &
  CPIDS+=($!)
done
rc=0; for p in "${CPIDS[@]}"; do wait "$p" || rc=1; done
echo "[run_remote] step $STEP finished rc=$rc; remaining:"; "$PY" "$STEPS_PY" --step "$STEP" --plan-only --shard 0/1 | tail -1
exit $rc

	#!/bin/bash
	# run_remote.sh — run one pool screening step on a multi-GPU machine (no Slurm).
	# STEP=1 bash code/run_remote.sh # run step 1 on every GPU (one vLLM server + one client shard per GPU)
	# STEP=2 bash code/run_remote.sh --plan-only # show the remaining work of a step, no GPU used
	# Env (optional): NGPU (default: nvidia-smi count), WORKERS (client threads per GPU; defaults per step),
	# VLLM (default: vllm on PATH), PY (default: python3), PORT0 (default 8001), GPU_UTIL (default 0.85)
	# Layout: this script lives in <package>/code/; items are read from <package>/results/pool/ (copy items/* there
	# once), frames from <package>/frames/pool_frames/<video_id>/, outputs go to <package>/results/pool/step<N>/.
	set -u
	CODE=$(cd "$(dirname "$0")" && pwd); ROOT=$(cd "$CODE/.." && pwd)
	export POOL_BASE=${POOL_BASE:-$ROOT/work_base}
	export POOL_FRAMES_DIR=${POOL_FRAMES_DIR:-$ROOT/frames/pool_frames}
	export POOL_RESULTS_ROOT=${POOL_RESULTS_ROOT:-$ROOT/results/pool}
	mkdir -p "$POOL_BASE" "$POOL_RESULTS_ROOT" "$ROOT/logs"
	PY=${PY:-python3}; VLLM=${VLLM:-vllm}; PORT0=${PORT0:-8001}; GPU_UTIL=${GPU_UTIL:-0.85}
	STEPS_PY="$CODE/exp/analysis/pool/pool_steps.py"
	STEP=${STEP:?set STEP=1..6}
	case "$STEP" in
	1) MODEL="Qwen/Qwen3-VL-8B-Instruct"; REV=0c351dd01ed87e9c1b53cbc748cba10e6187ff3b; MAX_LEN=8192; MAX_SEQS=64; MM_IMAGES=1; WORKERS=${WORKERS:-32};;
	2) MODEL="Qwen/Qwen3-VL-8B-Instruct"; REV=0c351dd01ed87e9c1b53cbc748cba10e6187ff3b; MAX_LEN=8192; MAX_SEQS=32; MM_IMAGES=1; WORKERS=${WORKERS:-16};;
	3) MODEL="Qwen/Qwen3-VL-2B-Instruct"; REV=89644892e4d85e24eaac8bacfd4f463576704203; MAX_LEN=16384; MAX_SEQS=16; MM_IMAGES=32; WORKERS=${WORKERS:-8};;
	4) MODEL="Qwen/Qwen3-VL-8B-Instruct"; REV=0c351dd01ed87e9c1b53cbc748cba10e6187ff3b; MAX_LEN=8192; MAX_SEQS=64; MM_IMAGES=1; WORKERS=${WORKERS:-32};;
	5) MODEL="Qwen/Qwen3-VL-2B-Instruct"; REV=89644892e4d85e24eaac8bacfd4f463576704203; MAX_LEN=16384; MAX_SEQS=16; MM_IMAGES=32; WORKERS=${WORKERS:-8};;
	6) MODEL="Qwen/Qwen3-VL-8B-Instruct"; REV=0c351dd01ed87e9c1b53cbc748cba10e6187ff3b; MAX_LEN=16384; MAX_SEQS=16; MM_IMAGES=32; WORKERS=${WORKERS:-8};;
	*) echo "STEP must be 1..6"; exit 2;;
	esac
	[ ! -e "$POOL_RESULTS_ROOT/pool_items_base.parquet" ] && { echo "copy items/* into $POOL_RESULTS_ROOT first"; exit 2; }
	if [ "${1:-}" = "--plan-only" ]; then "$PY" "$STEPS_PY" --step "$STEP" --plan-only --shard 0/1; exit $?; fi
	NGPU=${NGPU:-$(nvidia-smi -L 2>/dev/null \| wc -l)}
	[ "$NGPU" -ge 1 ] \|\| { echo "no GPU found"; exit 2; }
	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+=("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 "$PORT" \
	--max-model-len "$MAX_LEN" --gpu-memory-utilization "$GPU_UTIL" --max-num-seqs "$MAX_SEQS" \
	--limit-mm-per-prompt "{\"image\": $MM_IMAGES}" --mm-processor-cache-gb 0 --max-logprobs 20 \
	> "$ROOT/logs/vllm_s${STEP}_gpu${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
	for t in $(seq 1 180); do curl -sf "${EPS[$i]}/models" >/dev/null 2>&1 && break; kill -0 "${PIDS[$i]}" 2>/dev/null \|\| { echo "vLLM on GPU $i died, see logs/vllm_s${STEP}_gpu${i}.log"; exit 1; }; sleep 10; done
	echo "[run_remote] step $STEP: vLLM ready on GPU $i (${EPS[$i]})"
	done
	CPIDS=()
	for i in $(seq 0 $((NGPU - 1))); do
	"$PY" "$STEPS_PY" --step "$STEP" --endpoint "${EPS[$i]}" --shard "$i/$NGPU" --workers "$WORKERS" \
	> "$ROOT/logs/client_s${STEP}_gpu${i}.log" 2>&1 &
	CPIDS+=($!)
	done
	rc=0; for p in "${CPIDS[@]}"; do wait "$p" \|\| rc=1; done
	echo "[run_remote] step $STEP finished rc=$rc; remaining:"; "$PY" "$STEPS_PY" --step "$STEP" --plan-only --shard 0/1 \| tail -1
	exit $rc