More minor improvements.

theano/tensor/opt.py

@@ -1598,8 +1598,8 @@ def local_useless_elemwise(node):
             return [node.inputs[0]]
             
         if (
-                isinstance(node.op.scalar_op, theano.scalar.basic.AND) and
-                len(node.inputs) == 2
+            isinstance(node.op.scalar_op, scalar.AND)
+            and len(node.inputs) == 2
         ):
             
             if (
@@ -1628,8 +1628,8 @@ def local_useless_elemwise(node):
                 return zeros_like(node, 0)
                 
         if (
-                isinstance(node.op.scalar_op, theano.scalar.basic.OR) and
-                len(node.inputs) == 2
+            isinstance(node.op.scalar_op, scalar.OR)
+            and len(node.inputs) == 2
         ):
             
             if (
@@ -1657,21 +1657,11 @@ def local_useless_elemwise(node):
                 return ones_like(node, 0)
                 
         if (
-                isinstance(node.op.scalar_op, theano.scalar.basic.XOR) and
-                len(node.inputs) == 2
-        ):
-            if node.inputs[0] == node.inputs[1]:
-                return zeros_like(node, 0)
-                
-        if (
-            isinstance(
-                node.op.scalar_op,
-                (theano.scalar.basic.LE, theano.scalar.basic.GE)
-            )
+            isinstance(node.op.scalar_op, scalar.XOR)
             and len(node.inputs) == 2
         ):
             if node.inputs[0] == node.inputs[1]:
-                return ones_like(node, 0)
+                return zeros_like(node, 0)
 
 
 @register_specialize
@@ -4306,7 +4296,7 @@ def local_useless_elemwise_comparison(node):
     # Elemwise[{LE,GE}](X, X) -> Elemwise[ones](X)
     if (isinstance(node.op.scalar_op, (scalar.LE, scalar.GE)) and
         node.inputs[0] is node.inputs[1]):
-        return [T.ones_like(node.inputs[0])]
+        return [T.ones_like(node.inputs[0], dtype=node.outputs[0].type.dtype)]
     # Elemwise[{minimum,maximum}](X, X) -> X
     if (isinstance(node.op.scalar_op, (scalar.Minimum, scalar.Maximum)) and
         node.inputs[0] is node.inputs[1]):