expanded on the advanced tutorial

doc/glossary.txt

@@ -28,8 +28,6 @@ Glossary of terminology
         to know, for any operation which supports broadcasting, which
         dimensions will need to be broadcasted. When applicable, this
         information is given in the :term:`Type` of a :term:`Result`.
-
-        For more information, see the article about broadcasting_.
         
         See also:
 
@@ -64,6 +62,9 @@ Glossary of terminology
     graph
         WRITEME
 
+    inplace
+        WRITEME
+
     op
         WRITEME
 
@@ -86,8 +87,9 @@ Glossary of terminology
     type
         WRITEME
 
+    view
+        WRITEME
 
-.. _broadcasting: concepts/broadcasting.html
 
 
 

doc/tutorials/advanced/ex1/index.txt

+
+
+=========
+Example 1
+=========
+
+.. rubric:: Contents
+
+.. toctree::
+   :maxdepth: 2
+
+   type
+
+

doc/tutorials/advanced/ex1/type.txt

+
+
+==========================
+Making the ``double`` type
+==========================
+
+WRITEME

doc/tutorials/advanced/ex2/index.txt

+
+=========
+Example 2
+=========
+
+.. rubric:: Contents
+
+.. toctree::
+   :maxdepth: 2
+
+   type

doc/tutorials/advanced/ex2/type.txt

+
+
+==========================
+Making the ``cons`` type
+==========================
+
+WRITEME

doc/tutorials/advanced/index.txt

@@ -10,17 +10,69 @@ Before tackling this tutorial, it is highly recommended to read the
 
 
 The advanced tutorial is meant to give the reader a greater
-understanding of the building blocks of Theano by making him or her
-define a framework for basic arithmetic on doubles from scratch, as
-well as custom optimizations for this system. This tutorial should be
-of most use to users who want to extend Theano with custom types and
-operations related to these types. Users who want to extend Theano
-with new operations on tensors should check the
+understanding of the building blocks of Theano. It contains two
+examples which cover most of the conceptual space associated with
+:ref:`type` and :ref:`op` and then expands on other important matters
+such as optimization.
+
+
+This tutorial should be of most use to users who want to extend Theano
+with custom types and operations related to these types. Users who
+want to extend Theano with new operations on tensors should check the
 :ref:`tensoroptutorial`, but it is a good idea to read this tutorial
 as well since it probably provides better grounding for the many
 concepts at work here.
 
 
+---------------------------------------
+
+`Example 1`_
+  Making a basic arithmetic system on doubles
+
+`Example 2`_
+  Making a higher-level type: ``cons`` (pair)
+
+`Views and inplace operations`_
+  A guide to making Ops that return a :term:`view` on their inputs or
+  operate :term:`inplace` on them.
+
+`Graph optimization`_
+  A guide to the different ways of defining new custom optimizations
+  to simplify the computation graph and/or improve its numerical
+  stability or other desirable properties.
+
+`Tips`_
+  Tips and tricks about writing types, ops and optimizations. This
+  page is good reference - check it and come back to it!
+
+`Wrapping up`_
+  A guide to what to look at next
+
+---------------------------------------
+
+.. rubric:: Contents
+
+.. toctree::
+   :maxdepth: 2
+
+   ex1/index
+   ex2/index
+   inplace
+   optimization
+   tips
+   wrapup
+
+
+.. _Example 1: ex1/index.html
+.. _Example 2: ex2/index.html
+.. _Views and inplace operations: inplace.html
+.. _Graph optimization: optimization.html
+.. _Tips: tips.html
+.. _Wrapping up: wrapup.html
+
+
+
+
 
 
 

doc/tutorials/advanced/inplace.txt

+
+
+============================
+Views and inplace operations
+============================
+
+WRITEME
+

doc/tutorials/advanced/optimization.txt

+
+
+==================
+Graph optimization
+==================
+
+WRITEME

doc/tutorials/advanced/tips.txt

+
+
+====
+Tips
+====
+
+
+Don't define new Ops unless you have to
+=======================================
+
+It is usually not very useful to define Ops that can be easily
+implemented using other already existing Ops. For example, instead of
+writing a "sum_square_difference" Op, you should probably just write a
+simple function:
+
+.. code-block:: python
+
+   from theano import tensor as T
+
+   def sum_square_difference(a, b):
+       return T.sum((a - b)**2)
+
+Even without taking Theano's optimizations into account, it is likely
+to work just as well as a custom implementation. It also supports all
+data types, tensors of all dimensions as well as broadcasting, whereas
+a custom implementation would probably only bother to support
+contiguous vectors/matrices of doubles...
+
+
+Use Theano's high order Ops when applicable
+===========================================
+
+Theano provides some generic Op classes which allow you to generate a
+lot of ops at a lesser effort. For instance, Elemwise can be used to
+make :term:`elementwise` operations easily whereas DimShuffle can be
+used to make transpose-like transformations. These higher order Ops
+are mostly Tensor-related, as this is Theano's specialty. An exposé of
+them can therefore be found in :ref:`tensoroptools`.
+
+
+.. _opchecklist:
+
+Op Checklist
+============
+
+Use this list to make sure you haven't forgotten anything when
+defining a new Op. It might not be exhaustive but it covers a lot of
+common mistakes.
+
+WRITEME

doc/tutorials/advanced/wrapup.txt

+
+
+===========
+Wrapping up
+===========
+
+WRITEME

doc/tutorials/basic/module.txt

@@ -262,6 +262,13 @@ initialize a state with a matrix of zeros:
    #  [ 0.  0.  0.  0.  0.]]
 
 
+Nesting Modules
+===============
+
+WRITEME
+
+
+
 **Next:** `Tools`_
 
 .. _Tools: tools.html

doc/tutorials/index.txt

+
+=========
+Tutorials
+=========
+
+.. toctree::
+   :maxdepth: 2
+
+   basic/index
+   advanced/index
+   tensorop
+   tensoroptools
+

doc/tutorials/tensorop.txt

+
+.. _tensoroptutorial:
+
+===============================
+How to make a new Op on tensors
+===============================
+
+This tutorial aims to explain how to create a new operation operating
+on numpy's ndarrays and using Theano's Tensor type. It is optional but
+recommended to go through the :ref:`advtutorial` beforehand, which
+explains more in detail the purpose of each of the methods you will
+define here.
+
+The operation we will implement will be multiplication of two matrices
+of doubles. Of course, this operation already exists in Theano, but so
+do all simple operations and a tutorial works better when all concepts
+are kept as simple as possible. We will proceed by steps: the first
+step is to implement the Op in Python using numpy's multiplication
+operator. In the second step, we will extend our Op to (optionally)
+operate inplace on its inputs. In the third step, which is the most
+difficult, we will give our Op a solid C implementation.
+
+
+Implementing a new Op in Python
+===============================
+
+This is actually very simple to do. You are required to define two
+methods - one to create the :ref:`apply` node every time your Op is
+applied to some inputs, declaring the outputs in the process and
+another to operate on the inputs. There is also one optional method
+you may define which will compute the gradient of your Op.
+
+
+Extending the Op to work inplace
+================================
+
+WRITEME
+
+
+Writing a C implementation
+==========================
+
+WRITEME
+
+
+
+What's next
+===========
+
+Theano provides several special Ops that can make your job
+easier. Check the :ref:`tensoroptools` to see if you can leverage them
+to do what you need.
+
+It is highly recommended that you read the :ref:`opchecklist` before
+making any new Op. This can avoid you a lot of problems.
+
+

doc/tutorials/tensoroptools.txt

+
+.. _tensoroptools:
+
+===============
+Tensor Op Tools
+===============
+
+WRITEME - describe how to use Elemwise here
+