diff --git a/test/custom_ops/test_resize_.py b/test/custom_ops/test_resize_.py
new file mode 100644
index 0000000000000000000000000000000000000000..93b3018324930e4011458b277e8630c11aeb290a
--- /dev/null
+++ b/test/custom_ops/test_resize_.py
@@ -0,0 +1,32 @@
+import numpy as np
+import torch
+import torch_npu
+from torch_npu.testing.testcase import TestCase, run_tests
+
+
+class TestResize(TestCase):
+
+    def test_masked_select_out(self):
+
+        input_data = torch.tensor([[[[[[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14, 15], [16, 17, 18, 19, 20], [21, 22, 23, 24, 25]]]]]], dtype=torch.float)
+        mask = torch.tensor([True, False, True, False, True])
+
+        input_data_npu = input_data.npu()
+        mask_npu = mask.npu()
+
+        out_tensor = torch.empty((1, 1, 1, 1, 1), dtype=input_data.dtype)
+        out_tensor_npu = out_tensor.npu()
+
+        out_tensor_npu = out_tensor_npu.view(-1)
+        out_tensor_npu = torch.masked_select(input_data_npu, mask_npu, out=out_tensor_npu)
+        out_tensor = torch.masked_select(input_data, mask, out=out_tensor)
+        self.assertRtolEqual(out_tensor_npu, out_tensor)
+    
+    def test_resize_ncdhw(self):
+        out_tensor = torch.empty((1, 1, 1, 1, 1), dtype=torch.float16).npu()
+        shape = [25]
+        out_tensor.resize_(shape)
+        self.assertEqual(shape, out_tensor.shape)
+
+if __name__ == "__main__":
+    run_tests()
diff --git a/torch_npu/csrc/framework/StorageDescHelper.cpp b/torch_npu/csrc/framework/StorageDescHelper.cpp
index 24f0f83c4d20d830b62dc1c65f0b67c89e78d116..a451a1a54053875d1ebcfd9c43bb7907def92677 100644
--- a/torch_npu/csrc/framework/StorageDescHelper.cpp
+++ b/torch_npu/csrc/framework/StorageDescHelper.cpp
@@ -61,9 +61,13 @@ void StorageDescHelper::UpdateDesc(torch_npu::NPUStorageDesc &npuDesc, const c10
         }
     }
     npuDesc.base_strides_ = new_stride;
-
     // 更新物理内存信息
-    npuDesc.storage_sizes_ = FormatHelper::GetStorageSizes(npuDesc);
+    int NCDHW_OR_NDHWC_DIM = 5;
+    if ((npuDesc.npu_format_ == ACL_FORMAT_NCDHW || npuDesc.npu_format_ == ACL_FORMAT_NDHWC) && new_size.size() < NCDHW_OR_NDHWC_DIM) {
+        npuDesc.storage_sizes_ = new_size;
+    } else {
+        npuDesc.storage_sizes_ = FormatHelper::GetStorageSizes(npuDesc);
+    }
     if (new_data_numel > new_shape_numel) {
         // Refresh format to base format only when flattening storage data
         npuDesc.storage_sizes_ = new_size;