added unimplented_grad method to theano.gradient

theano/gradient.py

-"""Driver for general gradient calculations."""
+"""Driver for gradient calculations."""
+
+__authors__   = "James Bergstra"
+__copyright__ = "(c) 2011, Universite de Montreal"
+__license__   = "3-clause BSD License"
+__contact__   = "theano-dev <theano-dev@googlegroups.com>"
 
 __docformat__ = "restructuredtext en"
 
+import logging
+_logger = logging.getLogger('theano.gradient')
 import sys
-import gof #, gof.variable
+
 import numpy #for numeric_grad
 
+import gof #, gof.variable
 from gof.python25 import all
 import gof.utils
 
-import logging
-_logger = logging.getLogger('theano.gradient')
+from raise_op import Raise
+
 def warning(*msg):
     _logger.warning('WARNING theano.gradient: '+' '.join(msg))
 def info(*msg):
@@ -106,4 +114,14 @@ def grad_sources_inputs(sources, graph_inputs, warn_type=True):
                     gmap[r] = g_r
     return gmap
 
+def unimplemented_grad(op, x_pos, x):
+    """
+    Return an un-computable symbolic variable of type `x.type`.
+
+    If any function tries to compute this un-computable variable, an exception
+    (NotImplementedError) will be raised indicating that the gradient on the
+    `x_pos`'th input of `op` has not been implemented.
 
+    """
+    msg = '%s.grad not implemented for input %i'%(op, x_pos)
+    return Raise(msg=msg)(x)

theano/raise_op.py

+"""Symbolic Op for raising an exception."""
+
+__authors__   = "James Bergstra"
+__copyright__ = "(c) 2011, Universite de Montreal"
+__license__   = "3-clause BSD License"
+__contact__   = "theano-dev <theano-dev@googlegroups.com>"
+
+__docformat__ = "restructuredtext en"
+import gof
+
+class Raise(gof.Op):
+    """Op whose perform() raises an exception.
+    """
+    def __init__(self, msg="", exc=NotImplementedError):
+        """
+        msg - the argument to the exception
+        exc - an exception class to raise in self.perform
+        """
+        self.msg = msg
+        self.exc = exc
+    def __eq__(self, other):
+        # Note: the msg does not technically have to be in the hash and eq
+        # because it doesn't affect the return value.
+        return (type(self) == type(other)
+                and self.msg == other.msg
+                and self.exc == other.exc)
+    def __hash__(self):
+        return hash((type(self), self.msg, self.exc))
+    def __str__(self):
+        return "Raise{%s(%s)}"%(self.exc, self.msg)
+    def make_node(self, x):
+        return gof.Apply(self, [x], [x.type()])
+    def perform(self, node, inputs, out_storage):
+        raise self.exc(self.msg)
+
+

theano/tests/test_gradient.py

@@ -4,6 +4,7 @@
 #
 import unittest
 import numpy
+import theano
 from theano import gof
 
 from theano.gradient import *
@@ -250,6 +251,15 @@ class test_grad_sources_inputs(unittest.TestCase):
         self.assertTrue(g[a1.inputs[0]] == 6)
         self.assertTrue(g[a1.inputs[1]] == 11)
 
+def test_unimplemented_grad():
+    a = theano.tensor.vector()
+    b = theano.gradient.unimplemented_grad(theano.tensor.add, 1, a)
+    f = theano.function([a], b)
+    try:
+        f([1,2,3])
+        assert 0
+    except NotImplementedError:
+        pass
 
 if __name__ == '__main__':
     unittest.main()