Fix the problem that new models such as openpose cannot use command line prediction

demo/image_classification/predict.py

@@ -2,5 +2,8 @@ import paddle
 import paddlehub as hub
 
 if __name__ == '__main__':
-    model = hub.Module(name='resnet50_vd_imagenet_ssld', label_list=["roses", "tulips", "daisy", "sunflowers", "dandelion"], load_checkpoint=None)
-    result, feature = model.predict('flower.jpg')
+    model = hub.Module(
+        name='resnet50_vd_imagenet_ssld',
\ No newline at end of file
+        label_list=["roses", "tulips", "daisy", "sunflowers", "dandelion"],
+        load_checkpoint=None)
+    result = model.predict('flower.jpg')

paddlehub/module/module.py

@@ -66,17 +66,6 @@ def serving(func: Callable) -> Callable:
 class RunModule(object):
     '''The base class of PaddleHub Module, users can inherit this class to implement to realize custom class.'''
 
-    def __init__(self, *args, **kwargs):
-        # Avoid module being initialized multiple times
-        if '_is_initialize' in self.__dict__ and self._is_initialize:
-            return
-
-        super(RunModule, self).__init__()
-        _run_func_name = self._get_func_name(self.__class__, _module_runnable_func)
-        self._run_func = getattr(self, _run_func_name) if _run_func_name else None
-        self._serving_func_name = self._get_func_name(self.__class__, _module_serving_func)
-        self._is_initialize = True
-
     def _get_func_name(self, current_cls: Generic, module_func_dict: dict) -> Optional[str]:
         mod = current_cls.__module__ + '.' + current_cls.__name__
         if mod in module_func_dict:
@@ -116,17 +105,25 @@ class RunModule(object):
         with open(req_file, 'r') as file:
             return file.read().split('\n')
 
+    @property
+    def _run_func_name(self):
+        return self._get_func_name(self.__class__, _module_runnable_func)
+
+    @property
+    def _run_func(self):
+        return getattr(self, self._run_func_name) if self._run_func_name else None
+
     @property
     def is_runnable(self) -> bool:
         '''
         Whether the Module is runnable, in other words, whether can we execute the Module through the
         `hub run` command.
         '''
-        return self._run_func != None
-      
+        return True if self._run_func else False
+
     @property
     def serving_func_name(self):
-        return self._serving_func_name
+        return self._get_func_name(self.__class__, _module_serving_func)
 
 
 class Module(object):