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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

166 lines
5.9 KiB
Python

import json
import os
import pytest
print("[CONFTEST] Loading conftest.py at import time")
def pytest_configure(config):
"""
Create the perf results StashKey once and store it in config.
This hook runs once per test session, before module double-import issues.
"""
if not hasattr(config, "_diffusion_perf_key"):
config._diffusion_perf_key = pytest.StashKey[list]()
print(f"[CONFTEST] Created perf_results_key: {config._diffusion_perf_key}")
def add_perf_results(config, results: list):
"""Add performance results to the shared stash."""
# Get the shared key from config (created once in pytest_configure)
key = config._diffusion_perf_key
existing = config.stash.get(key, [])
existing.extend(results)
config.stash[key] = existing
print(f"[CONFTEST] Added {len(results)} results, total now: {len(existing)}")
@pytest.fixture(scope="session")
def perf_config(request):
"""Provide access to pytest config for storing perf results."""
return request.config
def _write_github_step_summary(content: str):
"""Write content 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(content)
def _write_results_json(results: list, output_path: str = "diffusion-results.json"):
"""Write performance results to JSON file for CI artifact collection."""
try:
with open(output_path, "w") as f:
json.dump(results, f, indent=2)
print(f"[CONFTEST] Wrote results to {output_path}")
except Exception as e:
print(f"[CONFTEST] Failed to write results JSON: {e}")
def _generate_diffusion_markdown_report(results: list) -> str:
"""Generate a markdown report for diffusion performance results."""
if not results:
return ""
gpu_config = os.environ.get("GPU_CONFIG", "")
header = "## Diffusion Performance Summary"
if gpu_config:
header += f" [{gpu_config}]"
header += "\n\n"
# Main performance table
markdown = header
markdown += "| Test Suite | Test Name | Modality | E2E (ms) | Avg Denoise (ms) | Median Denoise (ms) |\n"
markdown += "| ---------- | --------- | -------- | -------- | ---------------- | ------------------- |\n"
for entry in sorted(results, key=lambda x: (x["class_name"], x["test_name"])):
modality = entry.get("modality", "image")
markdown += (
f"| {entry['class_name']} | {entry['test_name']} | {modality} | "
f"{entry['e2e_ms']:.2f} | {entry['avg_denoise_ms']:.2f} | "
f"{entry['median_denoise_ms']:.2f} |\n"
)
# Video-specific metrics table (if any video tests)
video_results = [r for r in results if r.get("modality") == "video"]
if video_results:
markdown += "\n### Video Generation Metrics\n\n"
markdown += "| Test Name | FPS | Total Frames | Avg Frame Time (ms) |\n"
markdown += "| --------- | --- | ------------ | ------------------- |\n"
for entry in video_results:
fps = entry.get("frames_per_second", "N/A")
frames = entry.get("total_frames", "N/A")
avg_frame = entry.get("avg_frame_time_ms", "N/A")
if isinstance(fps, float):
fps = f"{fps:.2f}"
if isinstance(avg_frame, float):
avg_frame = f"{avg_frame:.2f}"
markdown += f"| {entry['test_name']} | {fps} | {frames} | {avg_frame} |\n"
return markdown
def pytest_sessionfinish(session):
"""
This hook is called by pytest at the end of the entire test session.
It prints a consolidated summary of all performance results.
"""
# Get results from stash using the shared key from config
key = session.config._diffusion_perf_key
results = session.config.stash.get(key, [])
print(f"\n[DEBUG] pytest_sessionfinish called, has {len(results)} entries")
if not results:
print("[DEBUG] No results collected, skipping summary output")
return
sorted_results = sorted(results, key=lambda x: (x["class_name"], x["test_name"]))
# Print to stdout (existing behavior)
print("\n\n" + "=" * 35 + " Performance Summary " + "=" * 35)
print(
f"{'Test Suite':<30} | {'Test Name':<20} | {'E2E (ms)':>12} | {'Avg Denoise (ms)':>18} | {'Median Denoise (ms)':>20}"
)
print(
"-" * 30
+ "-+-"
+ "-" * 20
+ "-+-"
+ "-" * 12
+ "-+-"
+ "-" * 18
+ "-+-"
+ "-" * 20
)
for entry in sorted_results:
print(
f"{entry['class_name']:<30} | {entry['test_name']:<20} | {entry['e2e_ms']:>12.2f} | "
f"{entry['avg_denoise_ms']:>18.2f} | {entry['median_denoise_ms']:>20.2f}"
)
print("=" * 91)
print("\n\n" + "=" * 36 + " Detailed Reports " + "=" * 37)
for entry in sorted_results:
print(f"\n--- Details for {entry['class_name']} / {entry['test_name']} ---")
stage_report = ", ".join(
f"{name}:{duration:.2f}ms"
for name, duration in entry.get("stage_metrics", {}).items()
)
if stage_report:
print(f" Stages: {stage_report}")
sampled_steps = entry.get("sampled_steps") or {}
if sampled_steps:
step_report = ", ".join(
f"{idx}:{duration:.2f}ms"
for idx, duration in sorted(sampled_steps.items())
)
print(f" Sampled Steps: {step_report}")
print("=" * 91)
print("\n\n" + "=" * 34 + " Performance Data JSON " + "=" * 34)
print(json.dumps(sorted_results, indent=2, sort_keys=True))
print("=" * 91)
# Write to GitHub Step Summary (new behavior for CI monitoring)
markdown_report = _generate_diffusion_markdown_report(sorted_results)
if markdown_report:
_write_github_step_summary(markdown_report)
# Write results to JSON file for CI artifact collection
_write_results_json(sorted_results)