format

docs/source/info_callbacks.rst

@@ -104,7 +104,7 @@ does all of that for you before training begins.
 
 This Callback will warn the user with the following message in case data mixing inside the batch is detected:
 
-.. code-block:: bash
+.. code-block::
 
     Your model is mixing data across the batch dimension.
     This can lead to wrong gradient updates in the optimizer.
@@ -123,4 +123,4 @@ that works with any PyTorch :class:`~torch.nn.Module` is also available:
     verification = BatchGradientVerification(model)
     valid = verification.check(input_array=torch.rand(2, 3, 4), sample_idx=1)
 
-In this example we run the test on a batch size 2 by inspecting gradients on the second sample.
+In this example we run the test on a batch size 2 by inspecting gradients on the second sample.