| #!/usr/bin/env bash |
| |
| set -eo pipefail |
|
|
| GPU_ID="${CUDA_VISIBLE_DEVICES:-1}" |
| SWEEP_FRAMES="${SWEEP_FRAMES:-120}" |
| PROMPT="${PROMPT:-a woman dancing.}" |
| BASELINE="/home/dyvm6xra/dyvm6xrauser11/workspace/cz/FlowCache/FlowCache4MAGI-1/outputs/a_woman_dancing_2026-05-19_09-49-14/output_2026-05-19_09-49-14.mp4" |
| DEV3="/home/dyvm6xra/dyvm6xrauser11/workspace/cz/FlowCache/FlowCache4MAGI-1-dev3-motion" |
| DEV4="/home/dyvm6xra/dyvm6xrauser11/workspace/cz/FlowCache/FlowCache4MAGI-1-dev4-detail" |
| DEV6="/home/dyvm6xra/dyvm6xrauser11/workspace/cz/FlowCache/FlowCache4MAGI-1-dev6-adaptive" |
| SWEEP_ROOT="${SWEEP_ROOT:-$DEV6/outputs/hparam_sweep_$(date +%Y%m%d_%H%M%S)}" |
| REPORT_DIR="$SWEEP_ROOT/report" |
| mkdir -p "$REPORT_DIR" |
|
|
| export MASTER_ADDR=localhost |
| export CUDA_VISIBLE_DEVICES="$GPU_ID" |
| export PAD_HQ=1 PAD_DURATION=1 |
| export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True |
| export OFFLOAD_T5_CACHE=true OFFLOAD_VAE_CACHE=true |
|
|
| set +u |
| source "${HOME}/miniforge3/etc/profile.d/conda.sh" 2>/dev/null || source "${HOME}/anaconda3/etc/profile.d/conda.sh" |
| conda activate magi |
| python3 -c "import numpy as np; exit(0 if int(np.__version__.split('.')[0])<2 else 1)" || pip install -q "numpy>=1.24,<2.0" |
| set -u |
|
|
| make_runtime() { |
| python3 - "$1" "$2" <<'PY' |
| import json, sys |
| with open("/home/dyvm6xra/dyvm6xrauser11/workspace/cz/FlowCache/FlowCache4MAGI-1-dev6-adaptive/config/single_run/flowcache_t2v.json") as f: |
| cfg = json.load(f) |
| cfg["runtime_config"]["num_frames"] = int(sys.argv[2]) |
| with open(sys.argv[1], "w") as f: |
| json.dump(cfg, f, indent=4) |
| PY |
| } |
|
|
| write_yaml() { |
| python3 - "$1" "${@:2}" <<'PY' |
| import sys, yaml |
| path = sys.argv[1] |
| params = {} |
| for kv in sys.argv[2:]: |
| k, v = kv.split("=", 1) |
| if v.lower() in ("true", "false"): |
| params[k] = v.lower() == "true" |
| elif v.replace(".", "", 1).isdigit(): |
| params[k] = float(v) if "." in v else int(v) |
| else: |
| params[k] = v |
| base = { |
| "rel_l1_thresh": 0.012, |
| "warmup_steps": 5, |
| "phase1_steps": 9, |
| "alpha": 0.5, |
| "detail_alpha": 0.5, |
| "detail_window_size": 3, |
| "detail_lambda": 0.3, |
| "weight_combine_mode": "blend", |
| "use_adaptive_tau": True, |
| "discard_nearly_clean_chunk": True, |
| "compress_kv_cache": True, |
| "total_cache_chunk_nums": 5, |
| "log": False, |
| "print_peak_memory": True, |
| } |
| base.update(params) |
| with open(path, "w") as f: |
| yaml.dump(base, f, default_flow_style=False) |
| PY |
| } |
|
|
| RESULTS="$REPORT_DIR/results.csv" |
| echo "variant,version,frames,beta,tau_min,tau_max,psnr_db,ssim,black_ratio,reuse_rate_pct,wall_sec,peak_gb,video_path,log_path,config" > "$RESULTS" |
|
|
| run_one() { |
| local version="$1" root="$2" yaml="$3" tag="$4" frames="$5" |
| local beta="${6:-}" tmin="${7:-}" tmax="${8:-}" |
| local runtime="$SWEEP_ROOT/runtime_${frames}f.json" |
| make_runtime "$runtime" "$frames" |
| local edir="$SWEEP_ROOT/${version}_${tag}_${frames}f" |
| mkdir -p "$edir" |
| local out="$edir/output.mp4" log="$edir/infer.log" metric="$edir/metrics.json" |
| export MASTER_PORT=$((6400 + RANDOM % 300)) |
| if [ "$root" = "$DEV6" ]; then |
| export PYTHONPATH="${DEV6}:${DEV4}:${DEV3}" |
| elif [ "$root" = "$DEV4" ]; then |
| export PYTHONPATH="${DEV4}:${DEV3}" |
| else |
| export PYTHONPATH="${DEV3}:${DEV4}" |
| fi |
| echo "========== $version / $tag @ ${frames}f (GPU=$GPU_ID) ==========" |
| local t0=$(date +%s) |
| set +e |
| ( cd "$root" && python3 inference/pipeline/motioncache.py \ |
| --config_file "$runtime" --mode t2v --prompt "$PROMPT" \ |
| --output_path "$out" --additional_config "$yaml" \ |
| --motioncache_metric_stats_path "$metric" 2>&1 | tee "$log" ) |
| local rc=${PIPESTATUS[0]}; set -e |
| local t1=$(date +%s) |
| [ -f "$out" ] && [ "$rc" -eq 0 ] || { echo "FAILED $tag rc=$rc"; return 1; } |
| eval_out=$(python3 "$DEV3/tools/eval_run.py" --baseline "$BASELINE" --generated "$out" --log "$log" --metric "$metric") |
| PSNR=NA; SSIM=NA; BLACK=NA; REUSE=NA; PEAK=NA |
| while IFS='=' read -r k v; do |
| case "$k" in PSNR) PSNR="$v" ;; SSIM) SSIM="$v" ;; BLACK) BLACK="$v" ;; REUSE) REUSE="$v" ;; PEAK) PEAK="$v" ;; esac |
| done <<< "$eval_out" |
| echo "$tag,$version,$frames,$beta,$tmin,$tmax,$PSNR,$SSIM,$BLACK,$REUSE,$((t1-t0)),$PEAK,$out,$log,$yaml" >> "$RESULTS" |
| echo " PSNR=${PSNR}dB reuse=${REUSE}% time=$((t1-t0))s" |
| } |
|
|
| echo "dev6 adaptive sweep @${SWEEP_FRAMES}f -> $SWEEP_ROOT (host=$(hostname), GPU=$GPU_ID)" |
|
|
| |
| run_one dev4 "$DEV4" "$DEV4/yaml_config/single_run/motiondetail_config_best.yaml" best "$SWEEP_FRAMES" "" "" "" || true |
|
|
| |
| for beta in 0.5 0.8 1.2; do |
| for pair in "0.008:0.020" "0.010:0.018" "0.006:0.024" "0.009:0.015"; do |
| IFS=':' read -r tmin tmax <<< "$pair" |
| tag="b${beta}_min${tmin}_max${tmax}" |
| y="$SWEEP_ROOT/dev6_${tag}.yaml" |
| write_yaml "$y" \ |
| "adaptive_tau_beta=$beta" \ |
| "adaptive_tau_min=$tmin" \ |
| "adaptive_tau_max=$tmax" |
| run_one dev6 "$DEV6" "$y" "$tag" "$SWEEP_FRAMES" "$beta" "$tmin" "$tmax" || true |
| done |
| done |
|
|
| BEST_YAML=$(python3 - "$RESULTS" "$DEV6/yaml_config/single_run/adaptive_config_best.yaml" <<'PY' |
| import csv, sys, yaml, os |
| csv_path, default_yaml = sys.argv[1:3] |
| rows = [r for r in csv.DictReader(open(csv_path)) |
| if r["version"] == "dev6" and r["frames"] == "120" and r["psnr_db"] not in ("NA", "")] |
| if not rows: |
| print(default_yaml) |
| raise SystemExit(0) |
|
|
| def score(r): |
| p = float(r["psnr_db"]) if r["psnr_db"] != "inf" else 100.0 |
| return p + 0.02 * float(r["reuse_rate_pct"] or 0) - 0.0001 * float(r["wall_sec"] or 0) |
|
|
| best = max(rows, key=score) |
| src = best["config"] |
| with open(src) as f: |
| cfg = yaml.safe_load(f) |
| with open(default_yaml, "w") as f: |
| yaml.dump(cfg, f, default_flow_style=False) |
| print(src) |
| print(f"BEST_TAG={best['variant']}", file=sys.stderr) |
| print(f"BEST_PSNR={best['psnr_db']}", file=sys.stderr) |
| PY |
| ) |
|
|
| BEST_TAG=$(python3 - "$RESULTS" <<'PY' |
| import csv, sys |
| rows = [r for r in csv.DictReader(open(sys.argv[1])) |
| if r["version"] == "dev6" and r["frames"] == "120" and r["psnr_db"] not in ("NA", "")] |
| def score(r): |
| p = float(r["psnr_db"]) if r["psnr_db"] != "inf" else 100.0 |
| return p + 0.02 * float(r["reuse_rate_pct"] or 0) - 0.0001 * float(r["wall_sec"] or 0) |
| print(max(rows, key=score)["variant"] if rows else "default") |
| PY |
| ) |
|
|
| echo "Best dev6 @120f: $BEST_TAG -> $BEST_YAML" |
|
|
| |
| run_one dev4 "$DEV4" "$DEV4/yaml_config/single_run/motiondetail_config_best.yaml" best 240 "" "" "" || true |
| run_one dev6 "$DEV6" "$BEST_YAML" "${BEST_TAG}_best" 240 \ |
| "$(python3 -c "import yaml; print(yaml.safe_load(open('$BEST_YAML'))['adaptive_tau_beta'])")" \ |
| "$(python3 -c "import yaml; print(yaml.safe_load(open('$BEST_YAML'))['adaptive_tau_min'])")" \ |
| "$(python3 -c "import yaml; print(yaml.safe_load(open('$BEST_YAML'))['adaptive_tau_max'])")" || true |
|
|
| python3 - "$RESULTS" "$REPORT_DIR/comparison_dev4_dev6.md" "$BEST_TAG" "$BEST_YAML" <<'PY' |
| import csv, sys |
| from datetime import datetime |
|
|
| csv_path, md_path, best_tag, best_yaml = sys.argv[1:5] |
| rows = [r for r in csv.DictReader(open(csv_path)) if r["psnr_db"] not in ("NA", "")] |
|
|
| def score(r): |
| p = float(r["psnr_db"]) if r["psnr_db"] != "inf" else 100.0 |
| return p + 0.02 * float(r["reuse_rate_pct"] or 0) - 0.0001 * float(r["wall_sec"] or 0) |
|
|
| dev6_120 = sorted([r for r in rows if r["version"] == "dev6" and r["frames"] == "120"], key=score, reverse=True) |
| dev4_120 = [r for r in rows if r["version"] == "dev4" and r["frames"] == "120"] |
| dev4_240 = [r for r in rows if r["version"] == "dev4" and r["frames"] == "240"] |
| dev6_240 = [r for r in rows if r["version"] == "dev6" and r["frames"] == "240"] |
|
|
| lines = [ |
| "# dev4 fixed vs dev6 adaptive 超参对比报告", |
| "", |
| f"生成时间: {datetime.now():%Y-%m-%d %H:%M:%S}", |
| "", |
| f"Sweep 目录: `{csv_path.replace('/report/results.csv', '')}`", |
| "", |
| "## 评分方法", |
| "", |
| "score = PSNR + 0.02 × reuse_rate(%) − 0.0001 × wall_time(s)", |
| "", |
| f"## dev6 最优 @120f: `{best_tag}`", |
| "", |
| f"配置: `{best_yaml}`", |
| "", |
| "## dev6 120f sweep 全部结果", |
| "", |
| "| variant | β | τ_min | τ_max | PSNR | reuse% | time(s) | score |", |
| "|---------|---|-------|-------|------|--------|---------|-------|", |
| ] |
| for r in dev6_120: |
| lines.append( |
| f"| {r['variant']} | {r['beta']} | {r['tau_min']} | {r['tau_max']} | " |
| f"{r['psnr_db']} dB | {r['reuse_rate_pct']} | {r['wall_sec']} | {score(r):.3f} |" |
| ) |
|
|
| if dev4_120: |
| r = dev4_120[0] |
| lines += [ |
| "", |
| "## dev4 fixed baseline @120f", |
| "", |
| f"- PSNR: **{r['psnr_db']} dB**, reuse: {r['reuse_rate_pct']}%, time: {r['wall_sec']}s", |
| ] |
|
|
| lines += [ |
| "", |
| "## 240f 全分辨率验证", |
| "", |
| "| version | variant | PSNR | reuse% | time(s) |", |
| "|---------|---------|------|--------|---------|", |
| ] |
| for r in dev4_240 + dev6_240: |
| lines.append(f"| {r['version']} | {r['variant']} | {r['psnr_db']} dB | {r['reuse_rate_pct']} | {r['wall_sec']} |") |
|
|
| if dev4_240 and dev6_240: |
| p4 = float(dev4_240[0]["psnr_db"]) |
| p6 = float(dev6_240[0]["psnr_db"]) |
| lines += [ |
| "", |
| "## 结论", |
| "", |
| f"- dev4 @240f: {p4:.4f} dB", |
| f"- dev6 @240f: {p6:.4f} dB", |
| f"- dev6 vs dev4: **{p6 - p4:+.4f} dB**", |
| ] |
|
|
| with open(md_path, "w") as f: |
| f.write("\n".join(lines) + "\n") |
| print(f"Report: {md_path}") |
| PY |
|
|
| echo "Done. Report: $REPORT_DIR/comparison_dev4_dev6.md" |
| cat "$REPORT_DIR/comparison_dev4_dev6.md" |
|
|
