Add Parameter docs

Author: apaszke

docs/source/nn.rst

@@ -7,6 +7,12 @@ torch.nn
 .. automodule:: torch.nn
 .. currentmodule:: torch.nn
 
+Parameters
+----------
+
+.. autoclass:: Parameter
+    :members:
+
 Containers
 ----------------------------------
 

torch/nn/parameter.py

@@ -2,6 +2,25 @@
 
 
 class Parameter(Variable):
+    """A kind of Variable that is to be considered a module parameter.
+
+    Parameters are :class:`~torch.autograd.Variable` 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.
+    Assigning a Variable 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
+    temporaries would get registered too.
+
+    Another difference is that parameters can't be volatile and that they
+    require gradient by default.
+
+    Arguments:
+        data (Tensor): parameter tensor.
+        requires_grad (bool, optional): if the parameter requires gradient. See
+            :ref:`excluding-subgraphs` for more details.
+    """
 
     def __init__(self, data, requires_grad=True):
         super(Parameter, self).__init__(data, requires_grad=requires_grad)