added PrintEverythinMode example to faq for lack of better spot

benchmark/regression/regression.py

@@ -77,9 +77,20 @@ class SpecifiedRegressionLayer(RegressionLayer):
         return self.l2_coef * T.sum(self.w * self.w)
 
 
+class PrintEverythingMode(theano.Mode):
+    def __init__(self, linker, optimizer=None):                                                       
+        def print_eval(i, node, fn): 
+            print i, node, [input[0] for input in fn.inputs],                                         
+            fn()
+            print [output[0] for output in fn.outputs]
+        wrap_linker = theano.gof.WrapLinkerMany([linker], [print_eval])
+        super(PrintEverythingMode, self).__init__(wrap_linker, optimizer)                             
+
+
 def test_module_advanced_example():
 
     profmode = theano.ProfileMode(optimizer='fast_run', linker=theano.gof.OpWiseCLinker())
+    profmode = PrintEverythingMode(theano.gof.OpWiseCLinker(), 'fast_run')
 
     data_x = N.random.randn(4, 10)
     data_y = [ [int(x)] for x in (N.random.randn(4) > 0)]

doc/advanced/debug_faq.txt

@@ -43,13 +43,6 @@ precise inspection of what's being computed where, when, and how, see the
 
 
 
-.. _faq_wraplinker:
-
-How do I step through a compiled function with the WrapLinker?
---------------------------------------------------------------
-
-WRITEME
-
 
 I wrote a new Op/Type, and weird stuff is happening...
 ------------------------------------------------------
@@ -85,3 +78,38 @@ Second, try the theano :ref:`profilemode`.  This will tell you which Apply nodes
 and which Ops are eating up your CPU cycles.
 
 
+.. _faq_wraplinker:
+
+How do I step through a compiled function with the WrapLinker?
+--------------------------------------------------------------
+
+This is not exactly an FAQ, but the doc is here for now...
+It's pretty easy to roll-your-own evaluation mode.
+Check out this one:
+
+.. code-block:: python
+
+    class PrintEverythingMode(Mode):
+        def __init__(self):
+            def print_eval(i, node, fn):
+                print i, node, [input[0] for input in fn.inputs],
+                fn()
+                print [output[0] for output in fn.outputs]
+            wrap_linker = theano.gof.WrapLinkerMany([theano.gof.OpWiseCLinker()], [print_eval])
+            super(PrintEverythingMode, self).__init__(wrap_linker, optimizer='fast_run')
+
+When you use ``mode=PrintEverythingMode`` as the mode for Function or Method,
+then you should see a lot of output.  Every Apply node will be printed out,
+along with its position in the graph, the arguments to the ``perform`` or
+``c_code`` and the output it computed.  Admittedly, this is a huge amount of
+output to read through if you are using big tensors... but you can choose to
+put logic inside of the print_eval function  that would, for example, only
+print something out if a certain kind of Op was used, at a certain program
+position, or if a particular value shows up in one of the inputs or outputs.
+
+This can be a really powerful debugging tool.  Read about more things you can
+do with :api:`WrapLinkerMany`.
+
+Note well the call to ``fn`` inside the call to ``print_eval``; without it,
+the graph wouldn't get computed at all!
+