added optional argument (warn_type) to gradient.grad_sources_inputs to disable…

theano/gradient.py

@@ -2,16 +2,21 @@
 
 __docformat__ = "restructuredtext en"
 
+import sys
 import gof #, gof.variable
 import numpy #for numeric_grad
 
 from gof.python25 import all
 import gof.utils
 
+def warning(msg):
+    # replace this with logger.warning when adding logging support
+    print >> sys.stderr, 'WARNING', msg
+
 _msg_retType = 'op.grad(...) returned a non-list'
 _msg_badlen = 'op.grad(...) returned wrong number of gradients'
 
-def grad_sources_inputs(sources, graph_inputs):
+def grad_sources_inputs(sources, graph_inputs, warn_type=True):
     """
     A gradient source is a pair (``r``, ``g_r``), in which ``r`` is a `Variable`, and ``g_r`` is a
     `Variable` that is a gradient wrt ``r``.
@@ -96,8 +101,9 @@ def grad_sources_inputs(sources, graph_inputs):
                     len(g_inputs),
                     len(node.inputs))
         for ii, (r, g_r) in enumerate(zip(node.inputs, g_inputs)):
-            if g_r and (r.type != g_r.type):
-                print 'WARNING: %s.grad returned a different type for input %i: %s vs. %s'%(node.op, ii, r.type, g_r.type)
+            if warn_type:
+                if g_r and (getattr(r,'type',0) != getattr(g_r,'type', 1)):
+                    warning('%s.grad returned a different type for input %i: %s vs. %s'%(node.op, ii, r, g_r))
             if g_r and len(sources) == 1 and sources[0][0].name and r.name:
                 g_r.name = "(d%s/d%s)" % (sources[0][0].name, r.name)
             if g_r is not None: 

theano/tests/test_gradient.py

@@ -9,6 +9,11 @@ from theano import gof
 from theano.gradient import *
 from theano import gradient
 
+
+def _grad_sources_inputs(*args):
+    # warn_type was introduced after this code, it complains throughout for nothing.
+    return grad_sources_inputs(warn_type=False, *args)
+
 class test_grad_sources_inputs(unittest.TestCase):
     def test_retNone1(self): 
         """Test that it is not ok to return None from op.grad()"""
@@ -21,7 +26,7 @@ class test_grad_sources_inputs(unittest.TestCase):
                 pass
         a = retNone().make_node()
         try:
-            grad_sources_inputs([(a.out, 1)], None)
+            _grad_sources_inputs([(a.out, 1)], None)
         except ValueError, e:
             self.failUnless(e[0] is gradient._msg_retType)
             return
@@ -36,7 +41,7 @@ class test_grad_sources_inputs(unittest.TestCase):
                 return [None]
         i = gof.generic()
         a = retNone().make_node(i)
-        g = grad_sources_inputs([(a.out, 1)], None)
+        g = _grad_sources_inputs([(a.out, 1)], None)
         self.failUnless(not i in g)
 
     def test_wrong_rval_len1(self): 
@@ -51,10 +56,10 @@ class test_grad_sources_inputs(unittest.TestCase):
         i = gof.generic()
         j = gof.generic()
         a1 = retNone().make_node(i)
-        g = grad_sources_inputs([(a1.out, 1)], None)
+        g = _grad_sources_inputs([(a1.out, 1)], None)
         a2 = retNone().make_node(i,j)
         try:
-            g = grad_sources_inputs([(a2.out, 1)], None)
+            g = _grad_sources_inputs([(a2.out, 1)], None)
         except ValueError, e:
             self.failUnless(e[0] is gradient._msg_badlen)
             return
@@ -74,7 +79,7 @@ class test_grad_sources_inputs(unittest.TestCase):
 
         i = gof.generic()
         a1 = retNone(self).make_node(i)
-        g = grad_sources_inputs([(a1.out, None)], None)
+        g = _grad_sources_inputs([(a1.out, None)], None)
 
     def test_1in_1out(self):
         """Test grad is called correctly for a 1-to-1 op"""
@@ -87,7 +92,7 @@ class test_grad_sources_inputs(unittest.TestCase):
             def grad(self, (x, ), (gz, )):
                 return gval,
         a1 = O().make_node()
-        g = grad_sources_inputs([(a1.outputs[0], 1)], None)
+        g = _grad_sources_inputs([(a1.outputs[0], 1)], None)
         self.failUnless(g[a1.inputs[0]] is gval)
 
     def test_1in_Nout(self):
@@ -101,7 +106,7 @@ class test_grad_sources_inputs(unittest.TestCase):
             def grad(self, (x, ), (gz1, gz2)):
                 return gval,
         a1 = O().make_node()
-        g = grad_sources_inputs([(a1.outputs[0], 1)], None)
+        g = _grad_sources_inputs([(a1.outputs[0], 1)], None)
         self.failUnless(g[a1.inputs[0]] is gval)
     def test_Nin_1out(self):
         """Test grad is called correctly for a many-to-1 op"""
@@ -115,7 +120,7 @@ class test_grad_sources_inputs(unittest.TestCase):
             def grad(self, (x0,x1), (gz, )):
                 return (gval0, gval1)
         a1 = O().make_node()
-        g = grad_sources_inputs([(a1.outputs[0], 1)], None)
+        g = _grad_sources_inputs([(a1.outputs[0], 1)], None)
         self.failUnless(g[a1.inputs[0]] is gval0)
         self.failUnless(g[a1.inputs[1]] is gval1)
     def test_Nin_Nout(self):
@@ -130,7 +135,7 @@ class test_grad_sources_inputs(unittest.TestCase):
             def grad(self, (x0,x1), (gz0,gz1)):
                 return gval0, gval1
         a1 = O().make_node()
-        g = grad_sources_inputs([(a1.outputs[0], 1)], None)
+        g = _grad_sources_inputs([(a1.outputs[0], 1)], None)
         self.failUnless(g[a1.inputs[0]] is gval0)
         self.failUnless(g[a1.inputs[1]] is gval1)
     def test_some_None_ograds(self):
@@ -145,7 +150,7 @@ class test_grad_sources_inputs(unittest.TestCase):
                 return [1]
         i = gof.generic()
         a1 = O(self).make_node(i)
-        g = grad_sources_inputs([(a1.outputs[0], 1)], None)
+        g = grad_sources_inputs([(a1.outputs[0], 1)], None, warn_type=False)
         self.failUnless(g[i] is 1)
 
     def test_some_None_igrads(self):
@@ -167,12 +172,12 @@ class test_grad_sources_inputs(unittest.TestCase):
         k = gof.generic()
         a1 = O(self, True).make_node(i,j)
         a2 = O(self, True).make_node(a1.outputs[1], k)
-        g = grad_sources_inputs([(a2.outputs[0], 1)], None)
+        g = grad_sources_inputs([(a2.outputs[0], 1)], None, warn_type=False)
         self.failUnless(g[i] is 1 and j not in g and k not in g)
 
         a1 = O(self, True).make_node(i,j)
         a2 = O(self, True).make_node(k, a1.outputs[1])
-        g = grad_sources_inputs([(a2.outputs[0], 1)], None)
+        g = _grad_sources_inputs([(a2.outputs[0], 1)], None)
         self.failUnless(g[k] is 1 and i not in g and j not in g)
 
     def test_inputs(self):
@@ -197,7 +202,7 @@ class test_grad_sources_inputs(unittest.TestCase):
         k = gof.generic()
         a1 = O(self, True).make_node(i,j)
         a2 = O(self, True).make_node(k,a1.outputs[1])
-        g = grad_sources_inputs([(a2.outputs[0], 1), (a1.outputs[1],4),
+        g = _grad_sources_inputs([(a2.outputs[0], 1), (a1.outputs[1],4),
             (a1.outputs[0], 3), (a1.outputs[0], 3)], a1.outputs)
         self.failUnless(g[a2.inputs[0]] == 1)
         self.failUnless(g[a2.inputs[1]] == 5)
@@ -228,7 +233,7 @@ class test_grad_sources_inputs(unittest.TestCase):
         k = gof.generic()
         a1 = O(self,True).make_node(i,j)
         a2 = O(self,True).make_node(k,a1.outputs[1])
-        g = grad_sources_inputs([(a2.outputs[0], 1), (a1.outputs[1],4),
+        g = _grad_sources_inputs([(a2.outputs[0], 1), (a1.outputs[1],4),
             (a1.outputs[0], 3), (a1.outputs[0], 3)], None)
         self.failUnless(g[a2.inputs[0]] == 1)
         self.failUnless(g[a2.inputs[1]] == 5)