fix test following raname of Env.

theano/tensor/tests/test_opt.py

@@ -3293,29 +3293,29 @@ class T_local_sum(unittest.TestCase):
         optimizer = optdb.query(self.mode._optimizer)
 
         x = T.TensorType('int64', (True, True, True))()
-        env = Env([x], [x.sum()])
-        optimizer.optimize(env)
+        g = FunctionGraph([x], [x.sum()])
+        optimizer.optimize(g)
         assert not any([
             isinstance(node.op, T.CAReduce)
-            for node in env.toposort()])
+            for node in g.toposort()])
 
     def test_local_sum_broadcast_all_1(self):
         optimizer = optdb.query(self.mode._optimizer)
 
         x = T.TensorType('int64', (True, True))()
-        env = Env([x], [x.sum(axis=[0, 1])])
-        optimizer.optimize(env)
+        g = FunctionGraph([x], [x.sum(axis=[0, 1])])
+        optimizer.optimize(g)
         assert not any([
             isinstance(node.op, T.CAReduce)
-            for node in env.toposort()])
+            for node in g.toposort()])
 
     def test_local_sum_broadcast_some_0(self):
         optimizer = optdb.query(self.mode._optimizer)
 
         x = T.TensorType('int64', (True, False, True))()
-        env = Env([x], [x.sum(axis=[0, 1])])
-        optimizer.optimize(env)
-        order = env.toposort()
+        g = FunctionGraph([x], [x.sum(axis=[0, 1])])
+        optimizer.optimize(g)
+        order = g.toposort()
         assert 1 == sum([isinstance(node.op, T.CAReduce) for node in order])
         op = order[-2].op
         assert isinstance(op, T.CAReduce)
@@ -3329,9 +3329,9 @@ class T_local_sum(unittest.TestCase):
         optimizer = optdb.query(self.mode._optimizer)
 
         x = T.TensorType('int64', (True, False, True))()
-        env = Env([x], [x.sum(axis=[0, 2])])
-        optimizer.optimize(env)
-        order = env.toposort()
+        g = FunctionGraph([x], [x.sum(axis=[0, 2])])
+        optimizer.optimize(g)
+        order = g.toposort()
         assert 0 == sum([isinstance(node.op, T.CAReduce) for node in order])