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42443420be
Arc B580 lost the kill test: batch-14 mask p50 103 ms vs Torch CPU 70 ms enhance / OpenVINO CPU 5 ms. Production stays on known-good CPU workers (tag known-good-cpu-2026-08-28). Hop stays 200 ms.
79 lines
2.3 KiB
Python
79 lines
2.3 KiB
Python
#!/usr/bin/env python3
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"""OpenVINO GPU/CPU bench of MetricGAN mask ONNX (.venv-ov)."""
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from __future__ import annotations
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import argparse
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import statistics
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import time
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from pathlib import Path
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import numpy as np
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import openvino as ov
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def pct(xs, p):
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xs = sorted(xs)
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i = int(round((p / 100.0) * (len(xs) - 1)))
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return xs[max(0, min(i, len(xs) - 1))]
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def bench(compiled, feats, warmup, iters):
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infer = compiled.create_infer_request()
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inp = compiled.inputs[0]
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for _ in range(warmup):
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infer.infer({inp: feats})
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xs = []
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for _ in range(iters):
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t0 = time.perf_counter()
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infer.infer({inp: feats})
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xs.append((time.perf_counter() - t0) * 1000.0)
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return xs
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def main() -> None:
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ap = argparse.ArgumentParser()
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ap.add_argument("--onnx", default="scripts/metricgan_enhance.onnx")
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ap.add_argument("--batch", type=int, default=14)
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ap.add_argument("--time", type=int, default=63)
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ap.add_argument("--feat", type=int, default=257)
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ap.add_argument("--iters", type=int, default=40)
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ap.add_argument("--warmup", type=int, default=10)
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args = ap.parse_args()
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core = ov.Core()
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print("openvino", ov.__version__)
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print("devices", core.available_devices)
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for d in core.available_devices:
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try:
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print(" ", d, core.get_property(d, "FULL_DEVICE_NAME"))
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except Exception as e:
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print(" ", d, e)
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onnx = Path(args.onnx)
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model = ov.convert_model(str(onnx))
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feats = np.random.randn(args.batch, args.time, args.feat).astype(np.float32)
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for device in core.available_devices:
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try:
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compiled = core.compile_model(model, device)
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except Exception as e:
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print(f"compile {device} FAILED: {type(e).__name__}: {e}")
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continue
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try:
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xs = bench(compiled, feats, args.warmup, args.iters)
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except Exception as e:
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print(f"infer {device} FAILED: {type(e).__name__}: {e}")
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continue
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per = [x / args.batch for x in xs]
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print(
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f"ov_{device} batch={args.batch} "
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f"p50={statistics.median(xs):.2f}ms p95={pct(xs,95):.2f}ms "
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f"p99={pct(xs,99):.2f}ms "
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f"per_cam_p50={statistics.median(per):.2f}ms "
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f"per_cam_p95={pct(per,95):.2f}ms"
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)
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if __name__ == "__main__":
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main()
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