diff --git a/tests/python/contrib/test_msc/test_manager.py b/tests/python/contrib/test_msc/test_manager.py
index 393c8decbc79..c3e1583ef291 100644
--- a/tests/python/contrib/test_msc/test_manager.py
+++ b/tests/python/contrib/test_msc/test_manager.py
@@ -34,6 +34,7 @@
 def _get_config(model_type, compile_type, inputs, outputs, atol=1e-2, rtol=1e-2):
     """Get msc config"""
     return {
+        "workspace": msc_utils.msc_dir(),
         "model_type": model_type,
         "inputs": inputs,
         "outputs": outputs,
diff --git a/tests/python/contrib/test_msc/test_runner.py b/tests/python/contrib/test_msc/test_runner.py
index a6005f5d41c2..cbc33d452846 100644
--- a/tests/python/contrib/test_msc/test_runner.py
+++ b/tests/python/contrib/test_msc/test_runner.py
@@ -82,7 +82,7 @@ def _test_from_torch(runner_cls, device, is_training=False, atol=1e-3, rtol=1e-3
 
     torch_model = _get_torch_model("resnet50", is_training)
     if torch_model:
-        workspace = msc_utils.set_workspace()
+        workspace = msc_utils.set_workspace(msc_utils.msc_dir())
         log_path = workspace.relpath("MSC_LOG", keep_history=False)
         msc_utils.set_global_logger("info", log_path)
         input_info = [([1, 3, 224, 224], "float32")]
@@ -139,7 +139,7 @@ def test_tensorflow_runner():
 
     tf_graph, graph_def = _get_tf_graph()
     if tf_graph and graph_def:
-        workspace = msc_utils.set_workspace()
+        workspace = msc_utils.set_workspace(msc_utils.msc_dir())
         log_path = workspace.relpath("MSC_LOG", keep_history=False)
         msc_utils.set_global_logger("info", log_path)
         data = np.random.uniform(size=(1, 224, 224, 3)).astype("float32")
diff --git a/tests/python/contrib/test_msc/test_tools.py b/tests/python/contrib/test_msc/test_tools.py
index 4578e662acb8..6adf70605bfd 100644
--- a/tests/python/contrib/test_msc/test_tools.py
+++ b/tests/python/contrib/test_msc/test_tools.py
@@ -46,10 +46,10 @@ def _get_config(
 ):
     """Get msc config"""
     return {
+        "workspace": msc_utils.msc_dir(),
         "model_type": model_type,
         "inputs": inputs,
         "outputs": outputs,
-        "debug_level": 0,
         "dataset": {"loader": "from_random", "max_iter": 5},
         "prepare": {"profile": {"benchmark": {"repeat": 10}}},
         "baseline": {