finally got sphinx format right

monai/transforms/regularization/array.py

@@ -88,16 +88,18 @@ def __call__(self, data: torch.Tensor, labels: torch.Tensor | None = None):
 
 class CutMix(Mixer):
  """CutMix augmentation as described in:
- Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, Youngjoon Yoo.
- CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features,
- ICCV 2019
+  Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, Youngjoon Yoo.
+  CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features,
+  ICCV 2019
 
- Class derived from :py:class:`monai.transforms.Mixer`. See corresponding
- documentation for details on the constructor parameters. Here, alpha not only determines
- the mixing weight but also the size of the random rectangles used during for mixing.
- Please refer to the paper for details.
+  Class derived from :py:class:`monai.transforms.Mixer`. See corresponding
+  documentation for details on the constructor parameters. Here, alpha not only determines
+  the mixing weight but also the size of the random rectangles used during for mixing.
+  Please refer to the paper for details.
 
- The most common use case is something close to:
+ The most common use case is something close to:
+
+ .. code-block:: python
 
  cm = CutMix(batch_size=8, alpha=0.5)
  for batch in loader:
@@ -106,6 +108,7 @@ class CutMix(Mixer):
  output = model(augimg)
  loss = loss_function(output, auglabels)
  ...
+
  """
 
  def apply(self, data: torch.Tensor):