question: NeptunePossibleLegacyUsageException  when logging accuracy
context: I want to log accuracy to neptune.ai logger. I tried this way
  def test_epoch_end(self, outputs):
          pred=torch.cat([x["pred"] for x in outputs]).detach().cpu().numpy()
          label=torch.cat([x["label"] for x in outputs]).detach().cpu().numpy()
          pred=np.argmax(pred,1)
          acc=accuracy_score(label,pred)
          print('acc',acc)
          self.logger.experiment.log_metric("acc", acc)
  
  and i am getting this error
  ---------------------------------------------------------------------------
  NeptunePossibleLegacyUsageException       Traceback (most recent call last)
  <ipython-input-15-a549be9bb6fe> in <module>
  ----> 1 trainer.test(model)
  
  C:\anaconda3\lib\site-packages\pytorch_lightning\trainer\trainer.py in test(self, model, test_dataloaders, ckpt_path, verbose, datamodule)
      577 
      578         # run test
  --> 579         results = self._run(model)
      580 
      581         assert self.state.stopped
  
  C:\anaconda3\lib\site-packages\pytorch_lightning\trainer\trainer.py in _run(self, model)
      754 
      755         # dispatch `start_training` or `start_evaluating` or `start_predicting`
  --> 756         self.dispatch()
      757 
      758         # plugin will finalized fitting (e.g. ddp_spawn will load trained model)
  
  C:\anaconda3\lib\site-packages\pytorch_lightning\trainer\trainer.py in dispatch(self)
      791     def dispatch(self):
      792         if self.evaluating:
  --> 793             self.accelerator.start_evaluating(self)
      794         elif self.predicting:
      795             self.accelerator.start_predicting(self)
  
  C:\anaconda3\lib\site-packages\pytorch_lightning\accelerators\accelerator.py in start_evaluating(self, trainer)
       97 
       98     def start_evaluating(self, trainer: 'pl.Trainer') -> None:
  ---> 99         self.training_type_plugin.start_evaluating(trainer)
      100 
      101     def start_predicting(self, trainer: 'pl.Trainer') -> None:
  
  C:\anaconda3\lib\site-packages\pytorch_lightning\plugins\training_type\training_type_plugin.py in start_evaluating(self, trainer)
      146     def start_evaluating(self, trainer: 'pl.Trainer') -> None:
      147         # double dispatch to initiate the test loop
  --> 148         self._results = trainer.run_stage()
      149 
      150     def start_predicting(self, trainer: 'pl.Trainer') -> None:
  
  C:\anaconda3\lib\site-packages\pytorch_lightning\trainer\trainer.py in run_stage(self)
      802 
      803         if self.evaluating:
  --> 804             return self.run_evaluate()
      805         if self.predicting:
      806             return self.run_predict()
  
  C:\anaconda3\lib\site-packages\pytorch_lightning\trainer\trainer.py in run_evaluate(self)
     1042 
     1043         with self.profiler.profile(f"run_{self.state.stage}_evaluation"):
  -> 1044             eval_loop_results = self.run_evaluation()
     1045 
     1046         # remove the tensors from the eval results
  
  C:\anaconda3\lib\site-packages\pytorch_lightning\trainer\trainer.py in run_evaluation(self, on_epoch)
      986 
      987         # lightning module method
  --> 988         self.evaluation_loop.evaluation_epoch_end(outputs)
      989 
      990         # hook
  
  C:\anaconda3\lib\site-packages\pytorch_lightning\trainer\evaluation_loop.py in evaluation_epoch_end(self, outputs)
      206             if is_overridden('test_epoch_end', model=model):
      207                 model._current_fx_name = 'test_epoch_end'
  --> 208                 model.test_epoch_end(outputs)
      209 
      210         else:
  
  <ipython-input-9-b08c6aa77d3f> in test_epoch_end(self, outputs)
      104         acc=accuracy_score(label,pred)
      105         print('acc',acc)
  --> 106         self.logger.experiment.log_metric("acc", acc)
  
  C:\anaconda3\lib\site-packages\neptune\new\run.py in __getattr__(self, item)
      161     def __getattr__(self, item):
      162         if item in LEGACY_METHODS:
  --> 163             raise NeptunePossibleLegacyUsageException()
      164         raise AttributeError(f"'{self.__class__.__name__}' object has no attribute '{item}'")
      165
answer: Dear @9157,
  Netpune is currently in the process of switching their client and I believe you are using their latest version while the currently Logger within Lightning users the old client.
  Please, downgrade your netpune version and it should work !
  Note: Netpune is currently in the process of updating the logger within Lightning.
  Best,
  T.C