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migraphx/test.py

+import time
+import numpy as np
+import migraphx
+
+def pct(a, p):
+    return float(np.percentile(np.asarray(a, dtype=np.float64), p))
+
+def build_mlp(batch, hidden, layers, seed=0):
+    rng = np.random.default_rng(seed)
+
+    p = migraphx.program()
+    mm = p.get_main_module()
+
+    x = mm.add_parameter("x", migraphx.shape(type="float", lens=[batch, hidden]))
+    y = x
+
+    for i in range(layers):
+        w = mm.add_literal(rng.random((hidden, hidden), dtype=np.float32))
+        y = mm.add_instruction(migraphx.op("dot"), [y, w])
+        y = mm.add_instruction(migraphx.op("relu"), [y])
+
+    mm.add_return([y])
+    return p
+
+def run_case(target, batch, hidden, layers, warmup=20, iters=200):
+    p = build_mlp(batch, hidden, layers)
+    p.compile(migraphx.get_target(target))
+
+    x = np.random.rand(batch, hidden).astype(np.float32)
+
+    for _ in range(warmup):
+        p.run({"x": x})
+
+    times = []
+    t0 = time.perf_counter()
+    for _ in range(iters):
+        s = time.perf_counter()
+        p.run({"x": x})
+        times.append((time.perf_counter() - s) * 1000)
+    t1 = time.perf_counter()
+
+    avg = (t1 - t0) * 1000 / iters
+    thr = (batch * iters) / (t1 - t0)
+    return avg, pct(times, 50), pct(times, 95), thr
+
+def main():
+    target = "gpu"   # ✅ 你的镜像就是这个
+    cases = [
+        (128, 8192*4,8),  # 更猛：内存/显存不够就删掉这行
+    ]
+
+    print(f"target={target}\n")
+    for b, h, l in cases:
+        avg, p50, p95, thr = run_case(target, b, h, l, warmup=20, iters=200)
+        print(f"[batch={b} hidden={h} layers={l}] "
+              f"avg={avg:.3f} ms  p50={p50:.3f} ms  p95={p95:.3f} ms  "
+              f"throughput={thr:.1f} samples/s")
+
+if __name__ == "__main__":
+    main()
+