diff --git a/tests/tests_fabric/loggers/test_tensorboard.py b/tests/tests_fabric/loggers/test_tensorboard.py
index 4dcb86f0e7406..9cd61ef2e131b 100644
--- a/tests/tests_fabric/loggers/test_tensorboard.py
+++ b/tests/tests_fabric/loggers/test_tensorboard.py
@@ -147,29 +147,52 @@ def test_tensorboard_log_hparams_and_metrics(tmp_path):
 
 
 @pytest.mark.parametrize("example_input_array", [None, torch.rand(2, 32)])
-def test_tensorboard_log_graph(tmp_path, example_input_array):
-    """Test that log graph works with both model.example_input_array and if array is passed externally."""
-    # TODO(fabric): Test both nn.Module and LightningModule
-    # TODO(fabric): Assert _apply_batch_transfer_handler is calling the batch transfer hooks
+def test_tensorboard_log_graph_plain_module(tmp_path, example_input_array):
     model = BoringModel()
-    if example_input_array is not None:
-        model.example_input_array = None
-
     logger = TensorBoardLogger(tmp_path)
     logger._experiment = Mock()
+
     logger.log_graph(model, example_input_array)
     if example_input_array is not None:
         logger.experiment.add_graph.assert_called_with(model, example_input_array)
+    else:
+        logger.experiment.add_graph.assert_not_called()
+
     logger._experiment.reset_mock()
 
-    # model wrapped in `FabricModule`
     wrapped = _FabricModule(model, strategy=Mock())
     logger.log_graph(wrapped, example_input_array)
     if example_input_array is not None:
         logger.experiment.add_graph.assert_called_with(model, example_input_array)
 
 
-@pytest.mark.skipif(not _TENSORBOARD_AVAILABLE, reason=str(_TENSORBOARD_AVAILABLE))
+@pytest.mark.parametrize("example_input_array", [None, torch.rand(2, 32)])
+def test_tensorboard_log_graph_with_batch_transfer_hooks(tmp_path, example_input_array):
+    model = pytest.importorskip("lightning.pytorch.demos.boring_classes").BoringModel()
+    logger = TensorBoardLogger(tmp_path)
+    logger._experiment = Mock()
+
+    with (
+        mock.patch.object(model, "_on_before_batch_transfer", return_value=example_input_array) as before_mock,
+        mock.patch.object(model, "_apply_batch_transfer_handler", return_value=example_input_array) as transfer_mock,
+    ):
+        logger.log_graph(model, example_input_array)
+        logger._experiment.reset_mock()
+
+        wrapped = _FabricModule(model, strategy=Mock())
+        logger.log_graph(wrapped, example_input_array)
+
+        if example_input_array is not None:
+            assert before_mock.call_count == 2
+            assert transfer_mock.call_count == 2
+            logger.experiment.add_graph.assert_called_with(model, example_input_array)
+        else:
+            before_mock.assert_not_called()
+            transfer_mock.assert_not_called()
+            logger.experiment.add_graph.assert_not_called()
+
+
+@pytest.mark.skipif(not _TENSORBOARD_AVAILABLE, reason="tensorboard is required")
 def test_tensorboard_log_graph_warning_no_example_input_array(tmp_path):
     """Test that log graph throws warning if model.example_input_array is None."""
     model = BoringModel()