File size: 3,301 Bytes
3f4bb1d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 | #!/usr/bin/env python3
"""Measure batched SONIC inference throughput, CPU vs CUDA.
An RL rollout evaluates SONIC once per environment per control tick, so the
number that matters is env-steps/s = batch / seconds-per-tick. Isaac Lab at 50 Hz
with N envs needs 50*N env-steps/s just to keep up with physics.
python scripts/bench_sonic_batch.py # CPU and CUDA if available
python scripts/bench_sonic_batch.py --batch 128 512
"""
from __future__ import annotations
import argparse
import importlib.util
import os
import time
from pathlib import Path
import numpy as np
_ROOT = Path(__file__).resolve().parents[1]
_DEFAULT_CKPT = _ROOT.parent / "checkpoints" / "sonic" / "sonic_v1_1"
def _load_policy_module():
"""Import ``sonic/policy.py`` alone; ``v2d_sim`` itself needs Isaac Lab."""
path = _ROOT / "source" / "v2d_sim" / "sonic" / "policy.py"
spec = importlib.util.spec_from_file_location("sonic_policy", path)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module
def bench(ckpt: Path, batches: list[int], repeats: int, use_cuda: bool) -> None:
os.environ["SONIC_ORT_CUDA"] = "1" if use_cuda else "0"
SonicOnnxAgent = _load_policy_module().SonicOnnxAgent
try:
agent = SonicOnnxAgent(ckpt, batched=True)
except Exception as exc: # noqa: BLE001
print(f" could not load ({exc})")
return
providers = agent.encoder.get_providers()
print(f" providers in use: {providers}")
if use_cuda and not any("CUDA" in p or "Tensorrt" in p for p in providers):
print(" CUDA provider did not attach; skipping")
return
rng = np.random.default_rng(0)
for n in batches:
enc = rng.normal(size=(n, 1751)).astype(np.float32)
enc[:, 0] = 1.0 # teleop
dec = rng.normal(size=(n, 994)).astype(np.float32)
for _ in range(3):
dec[:, :64] = agent.encode(enc)
agent.decode(dec)
t0 = time.perf_counter()
for _ in range(repeats):
dec[:, :64] = agent.encode(enc)
agent.decode(dec)
dt = (time.perf_counter() - t0) / repeats
envs_at_50hz = int(1.0 / dt / 50 * n) if dt > 0 else 0
print(
f" N={n:5d} {dt * 1000:8.2f} ms/tick {n / dt:10.0f} env-steps/s"
f" -> sustains {envs_at_50hz:6d} envs at 50 Hz"
)
def main() -> int:
ap = argparse.ArgumentParser()
ap.add_argument("--checkpoint", type=Path, default=_DEFAULT_CKPT)
ap.add_argument("--batch", type=int, nargs="+", default=[64, 256, 1024, 4096])
ap.add_argument("--repeats", type=int, default=10)
args = ap.parse_args()
if not (args.checkpoint / "model_encoder_batch.onnx").is_file():
raise SystemExit(
f"no dynamic-batch graphs in {args.checkpoint}; "
"run scripts/export_sonic_dynamic_batch.py first"
)
import onnxruntime as ort
print(f"onnxruntime {ort.__version__} built-in providers: {ort.get_available_providers()}\n")
print("CPU:")
bench(args.checkpoint, args.batch, args.repeats, use_cuda=False)
print("\nCUDA:")
bench(args.checkpoint, args.batch, args.repeats, use_cuda=True)
return 0
if __name__ == "__main__":
raise SystemExit(main())
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