Clean up too verbose logs pt. 2 (#2298)

Summary: Pull Request resolved: #2298

Reviewed By: saitcakmak

Differential Revision: D54885252

fbshipit-source-id: e24b502319493e8cb2abdfa196a16b14501c48e0

ax/modelbridge/tests/test_model_spec.py

@@ -58,7 +58,7 @@ def test_fit(self, wrapped_extract_ssd: Mock) -> None:
         # This should skip the model fit.
         with mock.patch("ax.modelbridge.torch.logger") as mock_logger:
             ms.fit(experiment=self.experiment, data=self.data)
-        mock_logger.info.assert_called_with(
+        mock_logger.debug.assert_called_with(
             "The observations are identical to the last set of observations "
             "used to fit the model. Skipping model fitting."
         )

ax/modelbridge/tests/test_torch_modelbridge.py

@@ -149,7 +149,7 @@ def test_TorchModelBridge(
         self.assertIsNone(model_fit_args["candidate_metadata"])
         self.assertEqual(ma._last_observations, observations)
 
-        with mock.patch(f"{TorchModelBridge.__module__}.logger.info") as mock_logger:
+        with mock.patch(f"{TorchModelBridge.__module__}.logger.debug") as mock_logger:
             ma._fit(
                 model=model,
                 search_space=search_space,

ax/modelbridge/torch.py

@@ -633,7 +633,7 @@ def _fit(
         **kwargs: Any,
     ) -> None:
         if self.model is not None and observations == self._last_observations:
-            logger.info(
+            logger.debug(
                 "The observations are identical to the last set of observations "
                 "used to fit the model. Skipping model fitting."
             )