We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
AttributeError Traceback (most recent call last) in () 1 # Testing the loss & accuracy of the model ----> 2 trainer.test(model)
10 frames /usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py in test(self, model, test_dataloaders, ckpt_path, verbose, datamodule) 912 913 if model is not None: --> 914 results = self.__test_given_model(model, test_dataloaders) 915 else: 916 results = self.__test_using_best_weights(ckpt_path, test_dataloaders)
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py in __test_given_model(self, model, test_dataloaders) 972 # run test 973 # sets up testing so we short circuit to eval --> 974 results = self.fit(model) 975 976 # teardown
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py in fit(self, model, train_dataloader, val_dataloaders, datamodule) 497 498 # dispath start_training or start_testing or start_predicting --> 499 self.dispatch() 500 501 # plugin will finalized fitting (e.g. ddp_spawn will load trained model)
start_training
start_testing
start_predicting
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py in dispatch(self) 538 def dispatch(self): 539 if self.testing: --> 540 self.accelerator.start_testing(self) 541 542 elif self.predicting:
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/accelerators/accelerator.py in start_testing(self, trainer) 74 75 def start_testing(self, trainer): ---> 76 self.training_type_plugin.start_testing(trainer) 77 78 def start_predicting(self, trainer):
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py in start_testing(self, trainer) 116 def start_testing(self, trainer: 'Trainer') -> None: 117 # double dispatch to initiate the test loop --> 118 self._results = trainer.run_test() 119 120 def start_predicting(self, trainer: 'Trainer') -> None:
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py in run_test(self) 785 # self.reset_test_dataloader(ref_model) 786 with self.profiler.profile("run_test_evaluation"): --> 787 eval_loop_results, _ = self.run_evaluation() 788 789 if len(eval_loop_results) == 0:
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py in run_evaluation(self, max_batches, on_epoch) 740 741 # lightning module method --> 742 deprecated_eval_results = self.evaluation_loop.evaluation_epoch_end() 743 744 # hook
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/evaluation_loop.py in evaluation_epoch_end(self) 187 188 # call the model epoch end --> 189 deprecated_results = self.__run_eval_epoch_end(self.num_dataloaders) 190 191 # enable returning anything
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/evaluation_loop.py in __run_eval_epoch_end(self, num_dataloaders) 219 if is_overridden('test_epoch_end', model=model): 220 model._current_fx_name = 'test_epoch_end' --> 221 eval_results = model.test_epoch_end(eval_results) 222 user_reduced = True 223
/content/MTMCT-Person-Re-Identification/mtmct_reid/engine.py in test_epoch_end(self, outputs) 199 fig = plot_distributions(self.trainer.datamodule.st_distribution) 200 --> 201 self.logger.experiment.add_figure('Spatial-Temporal Distribution', 202 fig) 203
The text was updated successfully, but these errors were encountered:
I am getting the above error while testing the model
Sorry, something went wrong.
@mayank5ah Can you please specify the version of Pytorch-lightning being used?
The recommended version is specified in the requirements.txt
No branches or pull requests
AttributeError Traceback (most recent call last)
in ()
1 # Testing the loss & accuracy of the model
----> 2 trainer.test(model)
10 frames
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py in test(self, model, test_dataloaders, ckpt_path, verbose, datamodule)
912
913 if model is not None:
--> 914 results = self.__test_given_model(model, test_dataloaders)
915 else:
916 results = self.__test_using_best_weights(ckpt_path, test_dataloaders)
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py in __test_given_model(self, model, test_dataloaders)
972 # run test
973 # sets up testing so we short circuit to eval
--> 974 results = self.fit(model)
975
976 # teardown
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py in fit(self, model, train_dataloader, val_dataloaders, datamodule)
497
498 # dispath
start_training
orstart_testing
orstart_predicting
--> 499 self.dispatch()
500
501 # plugin will finalized fitting (e.g. ddp_spawn will load trained model)
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py in dispatch(self)
538 def dispatch(self):
539 if self.testing:
--> 540 self.accelerator.start_testing(self)
541
542 elif self.predicting:
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/accelerators/accelerator.py in start_testing(self, trainer)
74
75 def start_testing(self, trainer):
---> 76 self.training_type_plugin.start_testing(trainer)
77
78 def start_predicting(self, trainer):
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py in start_testing(self, trainer)
116 def start_testing(self, trainer: 'Trainer') -> None:
117 # double dispatch to initiate the test loop
--> 118 self._results = trainer.run_test()
119
120 def start_predicting(self, trainer: 'Trainer') -> None:
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py in run_test(self)
785 # self.reset_test_dataloader(ref_model)
786 with self.profiler.profile("run_test_evaluation"):
--> 787 eval_loop_results, _ = self.run_evaluation()
788
789 if len(eval_loop_results) == 0:
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py in run_evaluation(self, max_batches, on_epoch)
740
741 # lightning module method
--> 742 deprecated_eval_results = self.evaluation_loop.evaluation_epoch_end()
743
744 # hook
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/evaluation_loop.py in evaluation_epoch_end(self)
187
188 # call the model epoch end
--> 189 deprecated_results = self.__run_eval_epoch_end(self.num_dataloaders)
190
191 # enable returning anything
/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/evaluation_loop.py in __run_eval_epoch_end(self, num_dataloaders)
219 if is_overridden('test_epoch_end', model=model):
220 model._current_fx_name = 'test_epoch_end'
--> 221 eval_results = model.test_epoch_end(eval_results)
222 user_reduced = True
223
/content/MTMCT-Person-Re-Identification/mtmct_reid/engine.py in test_epoch_end(self, outputs)
199 fig = plot_distributions(self.trainer.datamodule.st_distribution)
200
--> 201 self.logger.experiment.add_figure('Spatial-Temporal Distribution',
202 fig)
203
The text was updated successfully, but these errors were encountered: