Merge branch 'develop' of github.com:PaddlePaddle/PaddleHub into develop

paddlehub/finetune/task.py

@@ -417,8 +417,17 @@ class BasicTask(object):
     def _build_env_end_event(self):
         pass
 
-    def _calculate_metrics(self, run_states):
-        raise NotImplementedError
+    def _finetune_start_event(self):
+        logger.info("PaddleHub finetune start")
+
+    def _finetune_end_event(self, run_states):
+        logger.info("PaddleHub finetune finished.")
+
+    def _predict_start_event(self):
+        logger.info("PaddleHub predict start")
+
+    def _predict_end_event(self, run_states):
+        logger.info("PaddleHub predict finished.")
 
     def _eval_start_event(self):
         logger.info("Evaluation on {} dataset start".format(self.phase))
@@ -434,7 +443,7 @@ class BasicTask(object):
             "step %d: [step/sec: %.2f]" % (self.current_step, run_speed))
 
     def _save_ckpt_interval_event(self):
-        self.save_checkpoint(self.current_epoch, self.current_step)
+        self.save_checkpoint()
 
     def _eval_interval_event(self):
         self.eval(phase="dev")
@@ -443,12 +452,6 @@ class BasicTask(object):
         if self.is_predict_phase:
             yield run_state.run_results
 
-    def _finetune_start_event(self):
-        logger.info("PaddleHub finetune start")
-
-    def _finetune_end_event(self, run_state):
-        logger.info("PaddleHub finetune finished.")
-
     def _build_net(self):
         raise NotImplementedError
 
@@ -461,9 +464,12 @@ class BasicTask(object):
     def _add_metrics(self):
         raise NotImplementedError
 
+    def _calculate_metrics(self, run_states):
+        raise NotImplementedError
+
     # NOTE: current saved checkpoint machanism is not completed,
     # it can't restore dataset training status
-    def save_checkpoint(self, epoch, step):
+    def save_checkpoint(self):
         save_checkpoint(
             checkpoint_dir=self.config.checkpoint_dir,
             current_epoch=self.current_epoch,
@@ -506,7 +512,7 @@ class BasicTask(object):
                     self.env.current_epoch += 1
 
                 # Save checkpoint after finetune
-                self.save_checkpoint(self.current_epoch + 1, self.current_step)
+                self.save_checkpoint()
 
                 # Final evaluation
                 self.eval(phase="dev")
@@ -529,7 +535,9 @@ class BasicTask(object):
                                                "best_model")
                 self.load_parameters(best_model_path)
             self._predict_data = data
+            self._predict_start_event()
             run_states = self._run()
+            self._predict_end_event(run_states)
             self._predict_data = None
         return [run_state.run_results for run_state in run_states]
 
@@ -946,10 +954,10 @@ class SequenceLabelTask(BasicTask):
 
 class MultiLabelClassifierTask(ClassifierTask):
     def __init__(self,
-                 data_reader,
                  feature,
                  num_classes,
                  feed_list,
+                 data_reader,
                  startup_program=None,
                  config=None,
                  hidden_units=None):