150 lines
4.2 KiB
Python
150 lines
4.2 KiB
Python
#!/usr/bin/env python3
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"""
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昇腾 310B4 NPU 推理性能基准测试
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测试项目：
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1. 确认 NPU 推理（非 CPU fallback）
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2. 单次推理延迟
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3. 连续推理吞吐 (FPS)
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4. 多 worker 并发
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5. 不同分辨率影响
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"""
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import os
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import sys
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import time
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import socket
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import struct
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import json
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import base64
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import threading
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import numpy as np
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import cv2
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from concurrent.futures import ThreadPoolExecutor
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SOCK_PATH = "/tmp/edge-infer.sock"
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def make_test_image(w=640, h=640):
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"""生成随机测试图片"""
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img = np.random.randint(0, 255, (h, w, 3), dtype=np.uint8)
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_, buf = cv2.imencode('.jpg', img, [cv2.IMWRITE_JPEG_QUALITY, 90])
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return buf.tobytes()
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def infer_one(jpeg_bytes):
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"""发送一次推理请求，返回响应时间(ms)"""
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sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
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sock.connect(SOCK_PATH)
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msg = {
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"stream_id": 0,
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"device_id": "bench",
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"url": "bench://test",
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"ts": 1234567890.0,
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"jpeg_b64": base64.b64encode(jpeg_bytes).decode("utf-8")
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}
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data = json.dumps(msg).encode("utf-8")
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t0 = time.time()
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sock.sendall(struct.pack(">I", len(data)) + data)
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hdr = sock.recv(4)
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length = struct.unpack(">I", hdr)[0]
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result = json.loads(sock.recv(length).decode("utf-8"))
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elapsed = (time.time() - t0) * 1000 # ms
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sock.close()
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return elapsed, result
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def test_single_infer():
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"""单次推理延迟"""
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print("\n=== 单次推理延迟测试 ===")
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jpeg = make_test_image()
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times = []
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for i in range(5):
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t, _ = infer_one(jpeg)
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times.append(t)
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print(f" 第 {i+1} 次: {t:.1f} ms")
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# 跳过第一次预热
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times = times[1:]
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avg = sum(times) / len(times)
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print(f"\n 平均延迟 (排除预热): {avg:.1f} ms")
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print(f" 理论 FPS: {1000/avg:.1f}")
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return avg
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def test_throughput():
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"""连续推理吞吐"""
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print("\n=== 连续推理吞吐测试 ===")
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jpeg = make_test_image()
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count = 30
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t0 = time.time()
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for i in range(count):
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_, _ = infer_one(jpeg)
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if (i+1) % 10 == 0:
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elapsed = time.time() - t0
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print(f" {i+1}/{count} 完成, 累计: {elapsed:.1f}s, FPS: {(i+1)/elapsed:.1f}")
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total = time.time() - t0
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fps = count / total
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print(f"\n 总计 {count} 帧: {total:.2f}s")
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print(f" 吞吐: {fps:.1f} FPS")
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print(f" 每帧延迟: {total/count*1000:.1f} ms")
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return fps
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def test_concurrent(workers=4):
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"""多 worker 并发推理"""
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print(f"\n=== {workers} 路并发测试 ===")
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jpeg = make_test_image()
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results_per_worker = []
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def worker_task(worker_id, n_frames=20):
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times = []
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for _ in range(n_frames):
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t, _ = infer_one(jpeg)
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times.append(t)
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return worker_id, times
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t0 = time.time()
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with ThreadPoolExecutor(max_workers=workers) as pool:
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futures = [pool.submit(worker_task, i, 15) for i in range(workers)]
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for f in futures:
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wid, times = f.result()
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results_per_worker.append((wid, sum(times)/len(times), max(times), min(times)))
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total = time.time() - t0
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total_frames = workers * 15
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total_fps = total_frames / total
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for wid, avg, mx, mn in results_per_worker:
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print(f" Worker {wid}: avg={avg:.1f}ms, max={mx:.1f}ms, min={mn:.1f}ms")
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print(f"\n 并发 {workers} 路: 总计 {total_frames} 帧, {total:.2f}s")
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print(f" 总吞吐: {total_fps:.1f} FPS")
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print(f" 单路等效 FPS: {total_fps/workers:.1f}")
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return total_fps
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def test_power():
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"""读取 NPU 功耗信息"""
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import subprocess
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try:
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result = subprocess.run(['npu-smi', 'info'], capture_output=True, text=True, timeout=5)
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print("\n=== NPU 状态 ===")
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print(result.stdout)
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except Exception as e:
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print(f"无法读取 NPU 状态: {e}")
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if __name__ == "__main__":
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print("=" * 60)
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print(" 昇腾 310B4 + ACL 原生推理 性能基准测试")
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print("=" * 60)
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test_power()
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test_single_infer()
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test_throughput()
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test_concurrent(2)
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test_concurrent(4)
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test_concurrent(6)
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print("\n" + "=" * 60)
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print("测试完成")
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print("=" * 60)
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