optimization for removing div by one

theano/tensor/opt.py

@@ -2429,7 +2429,6 @@ def local_subtensor_merge(node):
                 lambda x: isinstance(x, T.Variable))
             # Do not call make_node for test_value
             out = subtens(x, *sl_ins)
-
             return [out]
 
 
@@ -4398,6 +4397,17 @@ def local_mul_to_sqr(node):
             if node.inputs[0] is node.inputs[1]:
                 return [T.sqr(node.inputs[0])]
 
+@register_specialize
+@gof.local_optimizer([T.int_div, T.floor_div])
+def local_div_by_one(node):
+    """x // 1 -> x
+    """
+    if node.op in [T.int_div]:
+        if len(node.inputs) == 2:
+            if isinstance(node.inputs[1], T.TensorConstant) and \
+               node.inputs[1].value == 1:
+                return [node.inputs[0]]
+
 
 @gof.local_optimizer([T.pow])
 def local_pow_specialize(node):

theano/tensor/tests/test_opt.py

@@ -5393,6 +5393,32 @@ def test_assert_op_gradient():
     assert func(x_val) == 1
 
 
+class TestDivByOne(unittest.TestCase):
+    def test1(self):
+        y = T.tensor4('y')
+
+        mode = theano.compile.mode.get_default_mode()
+        mode_wo_fusion = mode.excluding('fusion')
+
+        f = theano.function([y], y[::-1][::-1], mode=mode_wo_fusion)
+
+        graph = f.maker.fgraph.toposort()
+        divs = [node for node in graph
+                if isinstance(node.op, T.elemwise.Elemwise) and
+                isinstance(node.op.scalar_op, theano.scalar.IntDiv)]
+        assert len(divs) == 0
+
+    def test2(self):
+        y = T.tensor4('y')
+        z = y // 1
+        f = theano.function([y], z)
+        graph = f.maker.fgraph.toposort()
+        divs = [node for node in graph
+                if isinstance(node.op, T.elemwise.Elemwise) and
+                isinstance(node.op.scalar_op, theano.scalar.IntDiv)]
+        assert len(divs) == 0
+
+
 if __name__ == '__main__':
     t = TestMakeVector('setUp')
     t.setUp()