diff --git a/test/network_ops/test_upsample_scale_bicubic2d.py b/test/network_ops/test_upsample_scale_bicubic2d.py
index a6c47cbdd338c0c432b32bf32c44aa99ebb55a48..a9b0d9e6bf9cab85fe753720df91c032fc7760d4 100644
--- a/test/network_ops/test_upsample_scale_bicubic2d.py
+++ b/test/network_ops/test_upsample_scale_bicubic2d.py
@@ -1,4 +1,3 @@
-import unittest
 import torch
 import numpy as np
 import torch_npu
@@ -43,7 +42,6 @@ class TestUpsampleBicubic2d(TestCase):
 
         return shape_format1
 
-    @unittest.skip("skip test_upsample_bicubic2d_scale_common_shape_format now")
     def test_upsample_bicubic2d_scale_common_shape_format(self):
         for item in self.create_scale_shape_format32():
             cpu_input1, npu_input1 = create_common_tensor(item[0], 0, 255)
@@ -51,7 +49,6 @@ class TestUpsampleBicubic2d(TestCase):
             npu_output = self.npu_op_scale_exec(npu_input1, item[1])
             self.assertRtolEqual(cpu_output, npu_output)
 
-    @unittest.skip("skip test_upsample_bicubic2d_float16_scale_shape_format now")
     def test_upsample_bicubic2d_float16_scale_shape_format(self):
         def cpu_op_exec_fp16(input1, size):
             input1 = input1.to(torch.float32)