add inference model

paddle/fluid/train/custom_trainer/feed/accessor/epoch_accessor.cc

@@ -32,7 +32,7 @@ namespace feed {
         _inference_model_base_done_path = fs->path_join(_inference_model_path, 
             config["inference_base_done_name"].as<std::string>("xbox_base_done.txt"));
         _inference_model_delta_done_path = fs->path_join(_inference_model_path, 
-            config["inference_delta_done_name"].as<std::string>("xbox_delta_done.txt"));
+            config["inference_delta_done_name"].as<std::string>("xbox_patch_done.txt"));
         return 0;
     }
     
@@ -149,7 +149,7 @@ namespace feed {
                 if (is_last_epoch(epoch_id)) {
                     return true;
                 }
-                return delta_id(epoch_id) % 24 == 0;
+                return delta_id(epoch_id) % 78 == 0;
         }
         return false;
     }

paddle/fluid/train/custom_trainer/feed/executor/multi_thread_executor.cc

@@ -79,7 +79,7 @@ int MultiThreadExecutor::initialize(YAML::Node exe_config,
         CHECK(accessor_ptr->collect_persistables_name(_persistables) == 0)
             << "collect_persistables Failed, class:" << accessor_class;
     }
-    // std::sort(_persistables.begin(), _persistables.end()); // 持久化变量名一定要排序
+    std::sort(_persistables.begin(), _persistables.end()); // 持久化变量名一定要排序
 
     // Monitor组件
     for (const auto& monitor_config : _model_config["monitor"]) {

paddle/fluid/train/custom_trainer/feed/scripts/create_programs.py

@@ -131,6 +131,11 @@ class ModelBuilder:
                 main_program=test_program,
                 model_filename='inference_program',
                 program_only=True)
+        with open(os.path.join(self._save_path, 'inference_program'), "rb") as f:
+            program_desc_str = f.read()
+        infer_program = fluid.Program.parse_from_string(program_desc_str)
+        with open(os.path.join(self._save_path, 'inference_program.pbtxt'), 'w') as fout:
+            fout.write(str(infer_program))
 
         params = filter(fluid.io.is_parameter, main_program.list_vars())
         vars = []