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wehub-resource-sync 94057c3d3e
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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

120 lines
4.2 KiB
Python

"""Generate benchmark summary for GitHub Actions."""
from __future__ import annotations
import os
import sys
from pathlib import Path
from results import BenchmarkResult, GPUUtilization
def discover_benchmarks(base_dir: Path) -> list[tuple[Path, str]]:
"""Auto-discover benchmark folders and their result JSON files.
Returns list of (json_path, label) tuples sorted by folder name.
"""
results = []
for folder in base_dir.rglob("benchmark_*"):
if not folder.is_dir():
continue
# Find result JSON (exclude metadata and gpu files)
for json_file in folder.glob("*.json"):
if (
"experiment_metadata" not in json_file.name
and "gpu_utilization" not in json_file.name
):
# Generate label from folder name: benchmark_cache_aware_pd_grpc -> cache_aware pd grpc
label = folder.name.replace("benchmark_", "").replace("_", " ")
results.append((json_file, label))
break # One JSON per folder
return sorted(results, key=lambda x: x[0].parent.name)
def find_gpu_utilization(result_path: Path) -> Path | None:
"""Find GPU utilization JSON in same folder as result."""
gpu_json = result_path.parent / "gpu_utilization.json"
return gpu_json if gpu_json.exists() else None
def generate_summary(base_dir: Path) -> str:
"""Generate markdown summary."""
benchmarks = discover_benchmarks(base_dir)
if not benchmarks:
return (
"## Gateway E2E Genai-Bench Results Summary\n\nNo benchmark results found."
)
lines = [
"## Gateway E2E Genai-Bench Results Summary",
"",
"| Scenario | Status | TTFT (s) | E2E Latency (s) | Input Throughput (tok/s) | Output Throughput (tok/s) |",
"|----------|--------|----------|-----------------|--------------------------|---------------------------|",
]
gpu_sections = []
for result_path, label in benchmarks:
try:
result = BenchmarkResult.from_json(result_path)
except Exception as e:
print(f"Warning: Failed to parse {result_path}: {e}", file=sys.stderr)
lines.append(f"| {label} | ❌ Failed | - | - | - | - |")
continue
lines.append(
f"| {label} | ✅ Success | "
f"{result.ttft_mean:.2f} | "
f"{result.e2e_latency_mean:.2f} | "
f"{result.input_throughput_mean:.0f} | "
f"{result.output_throughput_mean:.0f} |"
)
# GPU utilization
gpu_path = find_gpu_utilization(result_path)
if gpu_path:
gpu = GPUUtilization.from_json(gpu_path)
if gpu and gpu.per_gpu:
gpu_lines = [
f"### GPU Utilization — {label}",
"",
f"Overall mean: {gpu.overall_mean:.2f}%",
"",
"| GPU | Mean (%) | p5 | p10 | p25 | p50 | p75 | p90 | p95 |",
"|-----|----------|----|-----|-----|-----|-----|-----|-----|",
]
for gpu_id, stats in sorted(
gpu.per_gpu.items(), key=lambda x: int(x[0])
):
gpu_lines.append(
f"| {gpu_id} | {stats.get('mean', 0):.2f} | "
f"{stats.get('p5', 0):.2f} | {stats.get('p10', 0):.2f} | "
f"{stats.get('p25', 0):.2f} | {stats.get('p50', 0):.2f} | "
f"{stats.get('p75', 0):.2f} | {stats.get('p90', 0):.2f} | "
f"{stats.get('p95', 0):.2f} |"
)
gpu_sections.append("\n".join(gpu_lines))
return "\n".join(lines) + "\n" + "\n\n".join(gpu_sections)
def main() -> None:
"""Main entry point."""
base_dir = Path(sys.argv[1]) if len(sys.argv) > 1 else Path.cwd()
summary = generate_summary(base_dir)
# Write to GITHUB_STEP_SUMMARY if available
summary_file = os.environ.get("GITHUB_STEP_SUMMARY")
if summary_file:
with open(summary_file, "a") as f:
f.write(summary)
f.write("\n")
print(f"Summary written to {summary_file}")
else:
print(summary)
if __name__ == "__main__":
main()