Added some text on how to extend Theano.

doc/cifarSC2011/extending_theano.txt

@@ -48,6 +48,37 @@ Op contract
 	def R_op(self, inputs, eval_points):
         def infer_shape(node, (i0_shapes, ...))
 
+.. ../extending/op.txt
+
+There is 2 mandatory function. The first is :func:`make_node`. The
+second is the one that do/tell the computation to do at run
+time. Currently you have 4 posibility: implement the :func:`perform`
+and/or :func:`c_code <Op.c_code>` (and other related :ref:`c functions
+<cop>`), or the :func:`make_thunk` function. The ``perform`` allow you
+to easily wrap an existing python function in Theano. The ``c_code``
+and related function allow you to have your op generate c code and
+have Theano compile and link to it. The ``make_thunk`` function will
+be called during compilation and should generate a ``thunk``: a
+function that when called will do the wanted computation. This is
+usefull if you want to generate code and compile it yourself. For
+example, this allow you to use PyCUDA to compile gpu code.
+
+There is 2 mandatory/highly suggested function. They are needed to for a basic
+optimization that merge duplicate computation in a Theano function. So
+if you don't want Theano to do you computation multiple time for no
+good reason, implement them! Those function are :func:`__eq__` and
+:func:`__hash__`.
+
+The :func:`infer_shape` method allow some very interesting
+optimization like don't performing the computation of your op just to
+take the shape your Op's output.
+
+The :func:`grad` method is needed you want want differentiation to
+work with your op.
+
+The :func:`__str__` is usefull to have a better printing of you op.
+
+The :func:`R_op` is needed if you want theano.tensor.Rop to work with your op.
 
 Op example
 ----------