disable default memory optimize since it affect the efficiency a lot, test=develop

fluid/PaddleCV/gan/cycle_gan/train.py

@@ -147,19 +147,22 @@ def train(args):
         init_model()
     losses = [[], []]
     t_time = 0
+    build_strategy = fluid.BuildStrategy()
+    build_strategy.enable_inplace = False
+    build_strategy.memory_optimize = False
 
     g_A_trainer_program = fluid.CompiledProgram(
         g_A_trainer.program).with_data_parallel(
-            loss_name=g_A_trainer.g_loss_A.name)
+            loss_name=g_A_trainer.g_loss_A.name, build_strategy=build_strategy)
     g_B_trainer_program = fluid.CompiledProgram(
         g_B_trainer.program).with_data_parallel(
-            loss_name=g_B_trainer.g_loss_B.name)
+            loss_name=g_B_trainer.g_loss_B.name, build_strategy=build_strategy)
     d_B_trainer_program = fluid.CompiledProgram(
         d_B_trainer.program).with_data_parallel(
-            loss_name=d_B_trainer.d_loss_B.name)
+            loss_name=d_B_trainer.d_loss_B.name, build_strategy=build_strategy)
     d_A_trainer_program = fluid.CompiledProgram(
         d_A_trainer.program).with_data_parallel(
-            loss_name=d_A_trainer.d_loss_A.name)
+            loss_name=d_A_trainer.d_loss_A.name, build_strategy=build_strategy)
     for epoch in range(args.epoch):
         batch_id = 0
         for i in range(max_images_num):

fluid/PaddleCV/gan/cycle_gan/trainer.py

@@ -13,8 +13,6 @@ class GATrainer():
         self.program = fluid.default_main_program().clone()
         with fluid.program_guard(self.program):
             self.fake_B = build_generator_resnet_9blocks(input_A, name="g_A")
-            #FIXME set persistable explicitly to pass CE
-            self.fake_B.persistable = True
             self.fake_A = build_generator_resnet_9blocks(input_B, name="g_B")
             self.cyc_A = build_generator_resnet_9blocks(self.fake_B, "g_B")
             self.cyc_B = build_generator_resnet_9blocks(self.fake_A, "g_A")
@@ -60,8 +58,6 @@ class GBTrainer():
         with fluid.program_guard(self.program):
             self.fake_B = build_generator_resnet_9blocks(input_A, name="g_A")
             self.fake_A = build_generator_resnet_9blocks(input_B, name="g_B")
-            #FIXME set persistable explicitly to pass CE
-            self.fake_A.persistable = True
             self.cyc_A = build_generator_resnet_9blocks(self.fake_B, "g_B")
             self.cyc_B = build_generator_resnet_9blocks(self.fake_A, "g_A")
             self.infer_program = self.program.clone()