removed type mismatch warning from gradient propagation algorithm. It was not a…

theano/gradient.py

@@ -9,14 +9,27 @@ 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
+import logging
+_logger=logging.getLogger("theano.gradient")
+_logger.setLevel(logging.WARN)
+
+def error(*args):
+    #sys.stderr.write('ERROR:'+ ' '.join(str(a) for a in args)+'\n')
+    _logger.error("ERROR: "+' '.join(str(a) for a in args))
+def warning(*args):
+    #sys.stderr.write('WARNING:'+ ' '.join(str(a) for a in args)+'\n')
+    _logger.warning("WARNING: "+' '.join(str(a) for a in args))
+def info(*args):
+    #sys.stderr.write('INFO:'+ ' '.join(str(a) for a in args)+'\n')
+    _logger.info("INFO: "+' '.join(str(a) for a in args))
+def debug(*args):
+    #sys.stderr.write('DEBUG:'+ ' '.join(str(a) for a in args)+'\n')
+    _logger.debug("DEBUG: "+' '.join(str(a) for a in args))
 
 _msg_retType = 'op.grad(...) returned a non-list'
 _msg_badlen = 'op.grad(...) returned wrong number of gradients'
 
-def grad_sources_inputs(sources, graph_inputs, warn_type=True):
+def grad_sources_inputs(sources, graph_inputs):
     """
     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``.
@@ -101,9 +114,6 @@ def grad_sources_inputs(sources, graph_inputs, warn_type=True):
                     len(g_inputs),
                     len(node.inputs))
         for ii, (r, g_r) in enumerate(zip(node.inputs, g_inputs)):
-            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

@@ -10,9 +10,7 @@ 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)
+_grad_sources_inputs = grad_sources_inputs
 
 class test_grad_sources_inputs(unittest.TestCase):
     def test_retNone1(self): 
@@ -150,7 +148,7 @@ 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, warn_type=False)
+        g = grad_sources_inputs([(a1.outputs[0], 1)], None)
         self.failUnless(g[i] is 1)
 
     def test_some_None_igrads(self):
@@ -172,7 +170,7 @@ class test_grad_sources_inputs(unittest.TestCase):
         k = gof.generic()
         a1 = O(self, True).make_node(i,j)
         a2 = O(self, True).make_node(a1.outputs[1], k)
-        g = grad_sources_inputs([(a2.outputs[0], 1)], None, warn_type=False)
+        g = grad_sources_inputs([(a2.outputs[0], 1)], None)
         self.failUnless(g[i] is 1 and j not in g and k not in g)
 
         a1 = O(self, True).make_node(i,j)