Test myst-markdown in docstrings

torch/nn/parameter.py

@@ -19,13 +19,13 @@ class _ParameterMeta(torch._C._TensorMeta):
 class Parameter(torch.Tensor, metaclass=_ParameterMeta):
     r"""A kind of Tensor that is to be considered a module parameter.
 
-    Parameters are :class:`~torch.Tensor` subclasses, that have a
-    very special property when used with :class:`Module` s - when they're
+    Parameters are {class}`~torch.Tensor` subclasses, that have a
+    very special property when used with {class}`Module` s - when they're
     assigned as Module attributes they are automatically added to the list of
-    its parameters, and will appear e.g. in :meth:`~Module.parameters` iterator.
+    its parameters, and will appear e.g. in {meth}`~Module.parameters` iterator.
     Assigning a Tensor doesn't have such effect. This is because one might
     want to cache some temporary state, like last hidden state of the RNN, in
-    the model. If there was no such class as :class:`Parameter`, these
+    the model. If there was no such class as {class}`Parameter`, these
     temporaries would get registered too.
 
     Args:
@@ -33,7 +33,7 @@ class Parameter(torch.Tensor, metaclass=_ParameterMeta):
         requires_grad (bool, optional): if the parameter requires gradient. Note that
             the torch.no_grad() context does NOT affect the default behavior of
             Parameter creation--the Parameter will still have `requires_grad=True` in
-            :class:`~no_grad` mode. See :ref:`locally-disable-grad-doc` for more
+            {class}`~no_grad` mode. See {ref}`locally-disable-grad-doc` for more
             details. Default: `True`
     """