diff --git a/monai/networks/layers/factories.py b/monai/networks/layers/factories.py
index b808c24de0..89fe1912a5 100644
--- a/monai/networks/layers/factories.py
+++ b/monai/networks/layers/factories.py
@@ -63,12 +63,14 @@ def use_factory(fact_args):
 import warnings
 from typing import Any, Callable, Dict, Tuple, Type, Union
 
+import torch
 import torch.nn as nn
 
 from monai.utils import look_up_option, optional_import
 
 InstanceNorm3dNVFuser, has_nvfuser = optional_import("apex.normalization", name="InstanceNorm3dNVFuser")
 
+
 __all__ = ["LayerFactory", "Dropout", "Norm", "Act", "Conv", "Pool", "Pad", "split_args"]
 
 
@@ -263,8 +265,21 @@ def instance_nvfuser_factory(dim):
     if dim != 3:
         warnings.warn(f"`InstanceNorm3dNVFuser` only supports 3d cases, use {types[dim - 1]} instead.")
         return types[dim - 1]
-    if not has_nvfuser:
-        warnings.warn("`apex.normalization.InstanceNorm3dNVFuser` is not found, use nn.InstanceNorm3d instead.")
+    # test InstanceNorm3dNVFuser installation with a basic example
+    has_nvfuser_flag = has_nvfuser
+    if not torch.cuda.is_available():
+        return nn.InstanceNorm3d
+    try:
+        layer = InstanceNorm3dNVFuser(num_features=1, affine=True).to("cuda:0")
+        inp = torch.randn([1, 1, 1, 1, 1]).to("cuda:0")
+        out = layer(inp)
+        del inp, out, layer
+    except Exception:
+        has_nvfuser_flag = False
+    if not has_nvfuser_flag:
+        warnings.warn(
+            "`apex.normalization.InstanceNorm3dNVFuser` is not installed properly, use nn.InstanceNorm3d instead."
+        )
         return nn.InstanceNorm3d
     return InstanceNorm3dNVFuser
 
diff --git a/tests/test_dynunet.py b/tests/test_dynunet.py
index 14006b96e6..ff5d5efbef 100644
--- a/tests/test_dynunet.py
+++ b/tests/test_dynunet.py
@@ -17,11 +17,9 @@
 
 from monai.networks import eval_mode
 from monai.networks.nets import DynUNet
-from monai.utils import optional_import
+from monai.utils.module import pytorch_after
 from tests.utils import skip_if_no_cuda, skip_if_windows, test_script_save
 
-_, has_nvfuser = optional_import("apex.normalization", name="InstanceNorm3dNVFuser")
-
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 strides: Sequence[Union[Sequence[int], int]]
@@ -123,7 +121,6 @@ def test_script(self):
 
 @skip_if_no_cuda
 @skip_if_windows
-@unittest.skipUnless(has_nvfuser, "To use `instance_nvfuser`, `apex.normalization.InstanceNorm3dNVFuser` is needed.")
 class TestDynUNetWithInstanceNorm3dNVFuser(unittest.TestCase):
     @parameterized.expand([TEST_CASE_DYNUNET_3D[0]])
     def test_consistency(self, input_param, input_shape, _):
@@ -145,7 +142,11 @@ def test_consistency(self, input_param, input_shape, _):
                         with eval_mode(net_fuser):
                             result_fuser = net_fuser(input_tensor)
 
-                        torch.testing.assert_close(result, result_fuser)
+                        # torch.testing.assert_allclose() is deprecated since 1.12 and will be removed in 1.14
+                        if pytorch_after(1, 12):
+                            torch.testing.assert_close(result, result_fuser)
+                        else:
+                            torch.testing.assert_allclose(result, result_fuser)
 
 
 class TestDynUNetDeepSupervision(unittest.TestCase):