removed uses of the warn_type flag

theano/tests/test_gradient.py

@@ -16,11 +16,8 @@ from theano.gof.null_type import NullType
 
 one = theano.tensor.as_tensor_variable(1.)
 
-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):
+class testgrad_sources_inputs(unittest.TestCase):
 
     def test_retNone1(self):
         """Test that it is not ok to return None from op.grad()"""
@@ -35,7 +32,7 @@ class test_grad_sources_inputs(unittest.TestCase):
                 pass
         a = retNone().make_node()
         try:
-            _grad_sources_inputs([(a.out, one)], None)
+            grad_sources_inputs([(a.out, one)], None)
         except TypeError, e:
             return
         self.fail()
@@ -52,10 +49,10 @@ class test_grad_sources_inputs(unittest.TestCase):
         i = theano.tensor.vector()
         j = theano.tensor.vector()
         a1 = retOne().make_node(i)
-        g = _grad_sources_inputs([(a1.out, one)], None)
+        g = grad_sources_inputs([(a1.out, one)], None)
         a2 = retOne().make_node(i,j)
         try:
-            g = _grad_sources_inputs([(a2.out, one)], None)
+            g = grad_sources_inputs([(a2.out, one)], None)
         except ValueError, e:
             return
         self.fail()
@@ -71,7 +68,7 @@ class test_grad_sources_inputs(unittest.TestCase):
             def grad(self, inp, grads):
                 return gval,
         a1 = O().make_node()
-        g = _grad_sources_inputs([(a1.outputs[0], one)], None)
+        g = grad_sources_inputs([(a1.outputs[0], one)], None)
         self.assertTrue(g[a1.inputs[0]] is gval)
 
     def test_1in_Nout(self):
@@ -87,7 +84,7 @@ class test_grad_sources_inputs(unittest.TestCase):
                 gz1, gz2 = grads
                 return gval,
         a1 = O().make_node()
-        g = _grad_sources_inputs([(a1.outputs[0], one)], None)
+        g = grad_sources_inputs([(a1.outputs[0], one)], None)
         self.assertTrue(g[a1.inputs[0]] is gval)
 
     def test_Nin_1out(self):
@@ -104,7 +101,7 @@ class test_grad_sources_inputs(unittest.TestCase):
                 gz, = grads
                 return (gval0, gval1)
         a1 = O().make_node()
-        g = _grad_sources_inputs([(a1.outputs[0], one)], None)
+        g = grad_sources_inputs([(a1.outputs[0], one)], None)
         self.assertTrue(g[a1.inputs[0]] is gval0)
         self.assertTrue(g[a1.inputs[1]] is gval1)
 
@@ -120,7 +117,7 @@ class test_grad_sources_inputs(unittest.TestCase):
             def grad(self, inp, grads):
                 return gval0, gval1
         a1 = O().make_node()
-        g = _grad_sources_inputs([(a1.outputs[0], one)], None)
+        g = grad_sources_inputs([(a1.outputs[0], one)], None)
         self.assertTrue(g[a1.inputs[0]] is gval0)
         self.assertTrue(g[a1.inputs[1]] is gval1)
 
@@ -136,7 +133,7 @@ class test_grad_sources_inputs(unittest.TestCase):
                 return [one]
         i = theano.tensor.matrix()
         a1 = O(self).make_node(i)
-        g = grad_sources_inputs([(a1.outputs[0], one)], None, warn_type=False)
+        g = grad_sources_inputs([(a1.outputs[0], one)], None)
         self.assertTrue(g[i] is one)
 
 def test_unimplemented_grad_func():