diff --git a/tests/test_pwg.py b/tests/test_pwg.py
index 7f2205d..41027b5 100644
--- a/tests/test_pwg.py
+++ b/tests/test_pwg.py
@@ -66,9 +66,14 @@ def test_convin_upsample_net():
         out2.sum().backward()
         print(f"torch conv_in_upsample_net backward takes {t.elapse}s.")
 
+    print("forward check")
     print(out.numpy()[0])
     print(out2.data.cpu().numpy()[0])
 
+    print("backward check")
+    print(net.conv_in.weight.numpy()[0])
+    print(net2.conv_in.weight.data.cpu().numpy()[0])
+
 
 def test_residual_block():
     net = ResidualBlock(dilation=9)
@@ -137,14 +142,19 @@ def test_pwg_generator():
         torch.cuda.synchronize()
         print(f"torch generator backward takes {t.elapse}s.")
 
+    print("test forward:")
     print(out.numpy()[0])
     print(out2.data.cpu().numpy()[0])
+
+    print("test backward:")
+    print(net.first_conv.weight.numpy()[0])
+    print(net2.first_conv.weight.data.cpu().numpy()[0])
     # print(out.shape)
 
 
 def test_pwg_discriminator():
     net = PWGDiscriminator()
-    net2 = pwgan.ParallelWaveGANDiscriminator()
+    net2 = pwgan.ParallelWaveGANDiscriminator().to(device)
     summary(net)
     summary(net2)
     for k, v in net2.named_parameters():
@@ -154,11 +164,39 @@ def test_pwg_discriminator():
         else:
             p.set_value(v.data.cpu().numpy())
     x = paddle.randn([4, 1, 180 * 256])
-    y = net(x)
-    y2 = net2(torch.as_tensor(x.numpy()))
+
+    synchronize()
+    with timer() as t:
+        y = net(x)
+        synchronize()
+        print(f"forward takes {t.elapse}s.")
+
+    synchronize()
+    with timer() as t:
+        y.sum().backward()
+        synchronize()
+        print(f"backward takes {t.elapse}s.")
+
+    x_torch = torch.as_tensor(x.numpy()).to(device)
+    torch.cuda.synchronize()
+    with timer() as t:
+        y2 = net2(x_torch)
+        torch.cuda.synchronize()
+        print(f"forward takes {t.elapse}s.")
+
+    torch.cuda.synchronize()
+    with timer() as t:
+        y2.sum().backward()
+        torch.cuda.synchronize()
+        print(f"backward takes {t.elapse}s.")
+
+    print("test forward:")
     print(y.numpy()[0])
     print(y2.data.cpu().numpy()[0])
-    print(y.shape)
+
+    print("test backward:")
+    print(net.conv_layers[0].weight.numpy()[0])
+    print(net2.conv_layers[0].weight.data.cpu().numpy()[0])
 
 
 def test_residual_pwg_discriminator():