diff --git a/monai/networks/nets/ahnet.py b/monai/networks/nets/ahnet.py
index 5146930fca..847993bd44 100644
--- a/monai/networks/nets/ahnet.py
+++ b/monai/networks/nets/ahnet.py
@@ -371,6 +371,7 @@ def __init__(
         self.pool_type = pool_type
         self.spatial_dims = spatial_dims
         self.psp_block_num = psp_block_num
+        self.psp = None
 
         if spatial_dims not in [2, 3]:
             raise AssertionError("spatial_dims can only be 2 or 3.")
@@ -510,7 +511,7 @@ def forward(self, x):
 
         sum4 = self.up3(d3) + conv_x
         d4 = self.dense4(sum4)
-        if self.psp_block_num > 0:
+        if self.psp_block_num > 0 and self.psp is not None:
             psp = self.psp(d4)
             x = torch.cat((psp, d4), dim=1)
         else:
diff --git a/tests/test_ahnet.py b/tests/test_ahnet.py
index 3dc8c05cf2..777e2637a7 100644
--- a/tests/test_ahnet.py
+++ b/tests/test_ahnet.py
@@ -191,9 +191,14 @@ def test_ahnet_shape_3d(self, input_param, input_shape, expected_shape):
 
     @skip_if_quick
     def test_script(self):
+        # test 2D network
         net = AHNet(spatial_dims=2, out_channels=2)
         test_data = torch.randn(1, 1, 128, 64)
         test_script_save(net, test_data)
+        # test 3D network
+        net = AHNet(spatial_dims=3, out_channels=2, psp_block_num=0, upsample_mode="nearest")
+        test_data = torch.randn(1, 1, 32, 32, 64)
+        test_script_save(net, test_data)
 
 
 class TestAHNETWithPretrain(unittest.TestCase):