fix and better explaination in the doc by code review.

doc/tutorial/extending_theano.txt

@@ -158,17 +158,17 @@ Try it!
 How to test it
 --------------
 
-Theano has some functions to simplify testing. Those help test the
-infer_shape, grad and R_op method. Put the following code in a file
-and execute with the `nosetests` program to run it.
+Theano has some functions to simplify testing. These help test the
+``infer_shape``, ``grad`` and ``R_op`` methods. Put the following code
+in a file and execute it with the ``nosetests`` program.
 
 Basic tests
 ===========
 
-Basic tests are done by you just by using the Op and checking it
+Basic tests are done by you just by using the Op and checking that it
 return the right answer. If you detect an error, you must raise an
-exception. You can use the `assert` keyword to raise automatically an
-AssertionError.
+exception. You can use the `assert` keyword to automatically raise an
+``AssertionError``.
 
 .. code-block:: python
 
@@ -185,25 +185,29 @@ AssertionError.
             f = theano.function([x], self.op(x))
             inp = numpy.asarray(numpy.random.rand(5, 4), dtype=config.floatX)
             out = f(inp)
-	    # Compare to result computed to the expected value.
+            # Compare the result computed to the expected value.
             assert numpy.allclose(inp * 2, out)
 
 Testing the infer_shape
 =======================
 
-When a class inherits from the InferShapeTester class, it gets the
-`self._compile_and_check` method that tests the Op infer_shape
-method. It checks if the optimized graph obtained gives the correct
-values. It also tests that the Op gets removed from the
-graph. `self._compile_and_check` compiles a Theano function. So it
-takes as parameter the list of inputs and outputs Theano variable
-that is passed to `theano.function`. Then
-with a list of real values to pass the the compiled function (don't
-use symmetric shape!). It also takes the class op to verify that
-it get removed from the graph.
+When a class inherits from the ``InferShapeTester`` class, it gets the
+`self._compile_and_check` method that tests the Op ``infer_shape``
+method. It tests that the Op gets optimized out of the graph if only
+the shape of the output is needed and not the output
+itself. Additionally, it checks that such an optimized graph computes
+the correct shape, by comparing it to the actual shape of the computed
+output.
+
+`self._compile_and_check` compiles a Theano function. It takes as
+parameters the lists of input and output Theano variables, as would be
+provided to theano.function, and a list of real values to pass to the
+compiled function (don't use shapes that are symmetric, e.g. (3, 3),
+as they can easily to hide errors). It also takes the Op class to
+verify that no Ops of that type appear in the shape-optimized graph.
 
 If there is an error, the function raises an exception. If you want to
-see it fail, you can implement a wrong infer_shape.
+see it fail, you can implement an incorrect ``infer_shape``.
 
 .. code-block:: python
 
@@ -227,7 +231,7 @@ analytic (symbolically computed) gradient and the numeric
 gradient (computed through the Finite Difference Method).
 
 If there is an error, the function raises an exception. If you want to
-see it fail, you can implement a wrong gradient (for instance removing
+see it fail, you can implement an incorrect gradient (for instance, by removing
 the multiplication by 2).
 
 .. code-block:: python