diff --git a/fluid/PaddleCV/image_classification/eval.py b/fluid/PaddleCV/image_classification/eval.py
index 1db290aec2978557cdb53cdd748495e9c31e89bf..ddce243fe1fcae81ee6064c7ff185fb8a045a402 100644
--- a/fluid/PaddleCV/image_classification/eval.py
+++ b/fluid/PaddleCV/image_classification/eval.py
@@ -49,7 +49,7 @@ def eval(args):
     # model definition
     model = models.__dict__[model_name]()
 
-    if model_name is "GoogleNet":
+    if model_name == "GoogleNet":
         out0, out1, out2 = model.net(input=image, class_dim=class_dim)
         cost0 = fluid.layers.cross_entropy(input=out0, label=label)
         cost1 = fluid.layers.cross_entropy(input=out1, label=label)
@@ -71,8 +71,10 @@ def eval(args):
 
     test_program = fluid.default_main_program().clone(for_test=True)
 
+    fetch_list = [avg_cost.name, acc_top1.name, acc_top5.name]
     if with_memory_optimization:
-        fluid.memory_optimize(fluid.default_main_program())
+        fluid.memory_optimize(
+            fluid.default_main_program(), skip_opt_set=set(fetch_list))
 
     place = fluid.CUDAPlace(0) if args.use_gpu else fluid.CPUPlace()
     exe = fluid.Executor(place)
@@ -88,8 +90,6 @@ def eval(args):
     val_reader = paddle.batch(reader.val(), batch_size=args.batch_size)
     feeder = fluid.DataFeeder(place=place, feed_list=[image, label])
 
-    fetch_list = [avg_cost.name, acc_top1.name, acc_top5.name]
-
     test_info = [[], [], []]
     cnt = 0
     for batch_id, data in enumerate(val_reader()):