diff --git a/sdk/python/v1beta1/kubeflow/katib/api/katib_client_test.py b/sdk/python/v1beta1/kubeflow/katib/api/katib_client_test.py
index 0755d6d533a..f8ded73eeff 100644
--- a/sdk/python/v1beta1/kubeflow/katib/api/katib_client_test.py
+++ b/sdk/python/v1beta1/kubeflow/katib/api/katib_client_test.py
@@ -1,6 +1,6 @@
 import multiprocessing
 from typing import List, Optional
-from unittest.mock import Mock, patch
+from unittest.mock import MagicMock, Mock, patch
 
 import kubeflow.katib.katib_api_pb2 as katib_api_pb2
 import pytest
@@ -341,12 +341,12 @@ def __init__(
         self.secret_key = secret_key
 
 
-class PyTorchJobSpec:
+class KubeflowOrgV1PyTorchJobSpec:
     def __init__(
         self,
         elastic_policy=None,
         nproc_per_node=None,
-        pytorch_replica_specs=None,
+        pytorch_replica_specs={},
         run_policy=None,
     ):
         self.elastic_policy = elastic_policy
@@ -355,13 +355,13 @@ def __init__(
         self.run_policy = run_policy
 
 
-class PyTorchJob:
+class KubeflowOrgV1PyTorchJob:
     def __init__(
         self,
         api_version=None,
         kind=None,
         metadata=None,
-        spec=PyTorchJobSpec,
+        spec=KubeflowOrgV1PyTorchJobSpec,
         status=None,
     ):
         self.api_version = api_version
@@ -571,6 +571,7 @@ def test_tune(katib_client, test_name, kwargs, expected_output):
     """
     print("\n\nExecuting test:", test_name)
 
+    PYTORCHJOB_KIND = "PyTorchJob"
     JOB_PARAMETERS = {
         "PyTorchJob": {
             "model": "KubeflowOrgV1PyTorchJob",
@@ -580,7 +581,20 @@ def test_tune(katib_client, test_name, kwargs, expected_output):
         }
     }
 
-    with patch(
+    with patch.dict(
+        "sys.modules",
+        {   
+            "kubeflow.storage_initializer": Mock(),
+            "kubeflow.storage_initializer.hugging_face": Mock(),
+            "kubeflow.storage_initializer.s3": Mock(),
+            "kubeflow.storage_initializer.constants": Mock(),
+            "kubeflow.training": MagicMock(),
+            "kubeflow.training.models": Mock(),
+            "kubeflow.training.utils": Mock(),
+            "kubeflow.training.constants": Mock(),
+            "kubeflow.training.constants.constants": Mock(),
+        }), \
+        patch(
         "kubeflow.storage_initializer.hugging_face.HuggingFaceModelParams",
         HuggingFaceModelParams,
     ), patch(
@@ -592,21 +606,16 @@ def test_tune(katib_client, test_name, kwargs, expected_output):
     ), patch(
         "kubeflow.storage_initializer.s3.S3DatasetParams", S3DatasetParams
     ), patch(
-        "kubeflow.training.models.KubeflowOrgV1PyTorchJob", PyTorchJob
+        "kubeflow.training.models.KubeflowOrgV1PyTorchJob", KubeflowOrgV1PyTorchJob
     ), patch(
         "kubeflow.training.constants.constants.JOB_PARAMETERS", JOB_PARAMETERS
+    ), patch(
+        "kubeflow.training.constants.constants.PYTORCHJOB_KIND", PYTORCHJOB_KIND
     ), patch(
         "kubeflow.katib.utils.utils.get_trial_substitutions_from_trainer",
         return_value={"param": "value"},
-    ), patch.dict(
-        "sys.modules",
-        {
-            "kubeflow.storage_initializer.constants": Mock(),
-            "kubeflow.training.models": Mock(),
-            "kubeflow.training.utils": Mock(),
-            "kubeflow.training.constants": Mock(),
-        },
-    ), patch.object(
+    ), \
+    patch.object(
         katib_client, "create_experiment", return_value=Mock()
     ) as mock_create_experiment:
         try: