diff --git a/test/network_ops/test_adaptive_max_pool2d.py b/test/network_ops/test_adaptive_max_pool2d.py
index f3e9fc2dadf25a9fa790f1db9d24a1a83476d97f..b12ca98580e1e640fd30070f7cf3ad883d6c1672 100644
--- a/test/network_ops/test_adaptive_max_pool2d.py
+++ b/test/network_ops/test_adaptive_max_pool2d.py
@@ -1,3 +1,4 @@
+import unittest
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
@@ -18,6 +19,7 @@ class TestAdaptiveMaxPool2d(TestCase):
         output = m(input1)
         return output.cpu().numpy()
 
+    @unittest.skip("skip test_adaptiveMaxPool2d_shape_format_fp32_6 now")
     def test_adaptiveMaxPool2d_shape_format_fp32_6(self):
         format_list = [-1]
         # (1, 8, 9) IndexError
diff --git a/test/network_ops/test_scaled_masked_softmax.py b/test/network_ops/test_scaled_masked_softmax.py
index 9f7b1f5d1757ff5abf9f8b93a71a89cd4664dc5b..38c2742b411f9dd3b581331f6af5a0cfd6b00113 100644
--- a/test/network_ops/test_scaled_masked_softmax.py
+++ b/test/network_ops/test_scaled_masked_softmax.py
@@ -1,4 +1,5 @@
 import random
+import unittest
 import torch
 import numpy as np
 import torch.nn.functional as F
@@ -43,6 +44,7 @@ class TestScaledMaskedSoftmax(TestCase):
         x_grad = x.grad
         return x_grad.half().cpu().detach().numpy()
 
+    @unittest.skip("skip test_scaled_masked_softmax_shape_format now")
     def test_scaled_masked_softmax_shape_format(self):
         shape_format = [
             [[np.float16, 29, (16, 6, 128, 128)], [np.float16, 29, (16, 6, 128, 128)]],