changes to documentation

doc/advanced/index.txt

@@ -18,12 +18,3 @@ Structure
    ccodegen
    function
    module
-
-Concepts
-========
-
-.. toctree::
-   :maxdepth: 2
-
-   gradient
-

doc/advanced_tutorial/ex1/op.txt

@@ -63,6 +63,11 @@ An Op is any object which defines the following methods:
   - This function must be determined by the inputs.  That is to say, if it is
     evaluated once on inputs A and returned B, then if ever inputs C, equal to
     A, are presented again, then outputs equal to B must be returned again.
+  
+  - You must be careful about aliasing outputs to inputs, and making
+    modifications to any of the inputs.  See `Views and inplace operations`_
+    before writing a ``perform`` implementation that does either of these
+    things.
 
 - **__eq__(self, other)**
 

doc/advanced_tutorial/ex1/type.txt

@@ -152,7 +152,7 @@ so if ``x`` is an ``int`` it we will return an equivalent ``float``.
 .. code-block:: python
 
    def values_eq_approx(x, y, tolerance=1e-4):
-       return abs(x - y) / (x + y) < tolerance
+       return abs(x - y) / (abs(x) + abs(y)) < tolerance
 
 The second method we define is ``values_eq_approx``. This method
 allows approximate comparison between two values respecting our Type's
@@ -204,7 +204,7 @@ and define ``filter`` and ``values_eq_approx`` in the subclass:
            return float(x)
    
        def values_eq_approx(self, x, y, tolerance=1e-4):
-           return abs(x - y) / (x + y) < tolerance
+           return abs(x - y) / (abs(x) + abs(y)) < tolerance
    
    double = Double()
 
@@ -291,7 +291,7 @@ Final version
            return float(x)
    
        def values_eq_approx(self, x, y, tolerance=1e-4):
-           return abs(x - y) / (x + y) < tolerance
+           return abs(x - y) / (abs(x) + abs(y)) < tolerance
 
        def __str__(self):
            return "double"

doc/advanced_tutorial/index.txt

@@ -30,12 +30,11 @@ concepts at work here.
    graphstructures
    ex1/type
    ex1/op
+   inplace
    ex1/ctype
    ex1/cop
-   inplace
    optimization
    tips
-   wrapup
 
 
 

doc/advanced_tutorial/inplace.txt

@@ -189,11 +189,3 @@ input(s)'s memory). From there, go to the previous section.
    certainly lead to erroneous computations and be a headache to
    debug.
 
-
-**Next:** `Graph optimization`_
-
-.. _Graph optimization: optimization.html
-
-
-
-

doc/advanced_tutorial/optimization.txt

@@ -276,7 +276,3 @@ Inplace optimizations
 
 
 
-
-**Next:** `Tips`_
-
-.. _Tips: tips.html

doc/advanced_tutorial/tips.txt

@@ -56,8 +56,3 @@ common mistakes.
 WRITEME
 
 
-
-**Next:** `Wrapping up`_
-
-.. _Wrapping up: wrapup.html
-

doc/advanced_tutorial/wrapup.txt

-
-
-===========
-Wrapping up
-===========
-
-WRITEME

doc/basic_tutorial/examples.txt

@@ -136,7 +136,7 @@ with respect to the second. In this way, Theano can be used for
 
 .. note::
 
-   In general, the result of ``T.grad`` has the same dimensions as the
+   The result of ``T.grad`` has the same dimensions as the
    second argument. This is exactly like the first derivative if the
    first argument is a scalar or a tensor of size 1 but not if it is
    larger. For more information on the semantics when the first
@@ -212,7 +212,7 @@ of the internal ``state`` will be replaced by the value computed as
 ``new_state``. In this case, the state will be replaced by the result
 of incrementing it by ``inc``.
 
-We recommend (insist?) that internl state arguments occur after any
+We recommend (insist?) that internal state arguments occur after any
 plain arguments and arguments with default values.
 
 There is no limit to how many states you can have. You can add an

doc/basic_tutorial/index.txt

@@ -34,4 +34,3 @@ Now we're ready for the tour:
    module_vs_op
    randomstreams
    tools
-   wrapup

doc/basic_tutorial/module.txt

@@ -269,11 +269,4 @@ WRITEME
 
 
 
-**Next:** `Tools`_
-
-.. _Tools: tools.html
-
-
-
-
 

doc/basic_tutorial/wrapup.txt

-
-
-===========
-Wrapping up
-===========
-
-WRITEME
-

doc/internal/dev_start_guide.txt

@@ -6,8 +6,6 @@ Developer Start Guide
 =====================
 
 
-- Learn about the basics of using mercurial.
-
 - Learn some `non-basic python`_ to understand what's going on in some of the
   tricker files (like tensor.py).
 
@@ -44,7 +42,7 @@ As a developer, you should clone this repository like this:
 Nightly test
 ============
 
-Their is nightly build done. The output is at: http://lgcm/nightly_build/do_nightly_build.txt
+WRITEME 
 
 Setting up your environment
 ===========================

theano/gof/graph.py

@@ -345,6 +345,8 @@ class Value(Result):
             raise ValueError("Value instances cannot have an owner.")
     owner = property(lambda self: None, __set_owner)
 
+    # index is not defined, because the `owner` attribute must necessarily be None
+
 class Constant(Value):
     """
     A :term:`Constant` is a `Value` that cannot be changed at runtime.