performance test in python

pytorch/cuda/moe_test.py

+from moe import MOELayer
+import torch
+import time
+
+
+def perf():
+    batch_size = 128
+    in_feat = 1024
+    out_feat = 4096
+    num_expert = 4
+
+    inp = torch.rand(batch_size, in_feat).cuda()
+    gate = torch.randint(low=0, high=num_expert, size=(batch_size, ), requires_grad=False).int().cuda()
+
+    moe = MOELayer(num_expert, in_feat, out_feat).cuda()
+
+    o = moe(inp, gate)
+
+    n_runs = 16
+    tott = 0.
+    for i in range(n_runs):
+        gate = torch.randint(low=0, high=num_expert, size=(batch_size, ), requires_grad=False).int().cuda()
+        ts = time.time()
+        o = moe(inp, gate)
+        te = time.time()
+        tott += te - ts
+
+    gflops = 2e-9 * n_runs * in_feat * out_feat * batch_size
+    print('Mean time {:.3f} ms, {:.3f} GFLOPs'.format(tott * 1e3 / n_runs, gflops))
+
+
+if __name__ == '__main__':
+    perf()