Merge pull request #187 from nouiz/doc_str

doc/cifarSC2011/extending_theano.txt

@@ -127,17 +127,43 @@ Op example
             z = output_storage[0]
             z[0] = x * 2
 
+        def infer_shape(self, node, i0_shapes):
+            return i0_shapes
+
+        def grad(self, inputs, output_grads):
+            return [output_grads[0] * 2]
+
 Test it!
 
->>> x = theano.tensor.matrix()
->>> f = theano.function([x],DoubleOp()(x))
->>> import numpy
->>> inp = numpy.random.rand(5,5)
->>> out = f(inp)
->>> assert numpy.allclose(inp*2, out)
->>> print inp
->>> print out
+.. code-block:: python
+
+    x = theano.tensor.matrix()
+    f = theano.function([x], DoubleOp()(x))
+    import numpy
+    inp = numpy.random.rand(5, 5)
+    out = f(inp)
+    assert numpy.allclose(inp * 2, out)
+    print inp
+    print out
+
+Testing the gradient
+--------------------
+
+The function :ref:`verify_grad <validating_grad>`
+verifies the gradient of an Op or Theano graph. It compares the
+analytic (symbolically computed) gradient and the numeric
+gradient (computed through the Finite Difference Method).
+
+To verify the grad method of the DoubleOp, you can use this:
+
+.. code-block:: python
+
+   import numpy
+   import theano.tests
+   theano.tests.unittest_tools.verify_grad(DoubleOp(), [numpy.random.rand(5,7,2)])
 
+If nothing happens, then it works! If you want to see it fail, you can
+implement a wrong gradient (for instance removing the multiplication by 2).
 
 Exercises 8
 -----------

doc/extending/unittest.txt

@@ -374,6 +374,8 @@ A few tools have been developed to help automate the development of
 unitests for Theano Ops.
 
 
+.. _validating_grad:
+
 Validating the Gradient
 -----------------------
 

doc/internal/dev_start_guide.txt

@@ -43,6 +43,14 @@ Mailing list
 See the Theano main page for the theano-dev, theano-buildbot and
 theano-github mailing list. They are useful to Theano contributors.
 
+Git config
+----------
+
+.. code-block:: bash
+
+   git config --global user.email you@yourdomain.example.com
+   git config --global user.name "Your Name Comes Here"
+
 Typical development workflow
 ----------------------------
 

doc/tutorial/faq.txt

+
+.. _faq:
+
+==========================
+Frequently Asked Questions
+==========================
+
+TypeError: object of type 'TensorVariable' has no len()
+-------------------------------------------------------
+
+If you receive this error:
+
+.. code-block:: python
+
+   TypeError: object of type 'TensorVariable' has no len()
+
+We can't implement the __len__ function on Theano Variables. This is
+because Python requires that this function returns an integer, but we
+can't do this as we are working with symbolic variables. You can use
+`var.shape[0]` as a workaround.
+
+Also we can't change the above error message into a more explicit one
+because of some other Python internal behavior that can't be modified.

doc/tutorial/index.txt

@@ -39,4 +39,4 @@ you out.
     shape_info
     remarks
     debug_faq
-
+    faq

theano/tensor/basic.py

@@ -3857,6 +3857,9 @@ class Split(Op):
         return (type(self) == type(other) and
                 self.len_splits == other.len_splits)
 
+    def __str__(self):
+        return self.__class__.__name__ + "{%s}" % self.len_splits
+
     def __hash__(self):
         return hash(Split) ^ self.len_splits