Fix flake8 and clarify comment.

theano/tensor/nnet/abstract_conv.py

@@ -235,7 +235,7 @@ class AbstractConv2d(BaseAbstractConv2d):
                                              filter_flip)
 
     def make_node(self, img, kern):
-        # Normalize the inputs types
+        # Make sure both inputs have the same Type
         ktype = img.type.clone(dtype=kern.dtype,
                                broadcastable=kern.broadcastable)
         kern = ktype.filter_variable(kern)
@@ -333,7 +333,7 @@ class AbstractConv2d_gradWeights(BaseAbstractConv2d):
 
     # Update shape/height_width
     def make_node(self, img, topgrad, shape):
-        # Normalize the inputs types
+        # Make sure both inputs have the same Type
         gtype = img.type.clone(dtype=topgrad.dtype,
                                broadcastable=topgrad.broadcastable)
         topgrad = gtype.filter_variable(topgrad)
@@ -425,9 +425,9 @@ class AbstractConv2d_gradInputs(BaseAbstractConv2d):
 
     # Update shape/height_width
     def make_node(self, kern, topgrad, shape):
-        # Normalize the inputs types
+        # Make sure both inputs have the same Type
         gtype = kern.type.clone(dtype=topgrad.dtype,
-                               broadcastable=topgrad.broadcastable)
+                                broadcastable=topgrad.broadcastable)
         topgrad = gtype.filter_variable(topgrad)
 
         if kern.type.ndim != 4: