Fix for incorrect run on the validation set with overwritten validation_epoch_end and test_end (Lightning-AI#1353)

* reorder if clauses

* fix wrong method overload in test

* fix formatting

* update change_log

* fix line too long

Author: Adrian Wälchli

CHANGELOG.md

@@ -61,6 +61,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed an issue where `val_percent_check=0` would not disable validation ([#1251](https://github.com/PyTorchLightning/pytorch-lightning/pull/1251))
 - Fixed average of incomplete `TensorRunningMean` ([#1309](https://github.com/PyTorchLightning/pytorch-lightning/pull/1309))
 - Fixed an issue with early stopping that would prevent it from monitoring training metrics when validation is disabled / not implemented ([#1235](https://github.com/PyTorchLightning/pytorch-lightning/pull/1235)). 
+- Fixed a bug that would cause `trainer.test()` to run on the validation set when overloading `validation_epoch_end ` and `test_end` ([#1353](https://github.com/PyTorchLightning/pytorch-lightning/pull/1353)).
 
 ## [0.7.1] - 2020-03-07
 

pytorch_lightning/trainer/evaluation_loop.py

@@ -295,20 +295,25 @@ def _evaluate(self, model: LightningModule, dataloaders, max_batches: int, test_
         if isinstance(model, (LightningDistributedDataParallel, LightningDataParallel)):
             model = model.module
 
-        # TODO: remove in v1.0.0
-        if test_mode and self.is_overriden('test_end', model=model):
-            eval_results = model.test_end(outputs)
-            warnings.warn('Method `test_end` was deprecated in 0.7.0 and will be removed 1.0.0.'
-                          ' Use `test_epoch_end` instead.', DeprecationWarning)
-        elif self.is_overriden('validation_end', model=model):
-            eval_results = model.validation_end(outputs)
-            warnings.warn('Method `validation_end` was deprecated in 0.7.0 and will be removed 1.0.0.'
-                          ' Use `validation_epoch_end` instead.', DeprecationWarning)
-
-        if test_mode and self.is_overriden('test_epoch_end', model=model):
-            eval_results = model.test_epoch_end(outputs)
-        elif self.is_overriden('validation_epoch_end', model=model):
-            eval_results = model.validation_epoch_end(outputs)
+        if test_mode:
+            if self.is_overriden('test_end', model=model):
+                # TODO: remove in v1.0.0
+                eval_results = model.test_end(outputs)
+                warnings.warn('Method `test_end` was deprecated in 0.7.0 and will be removed 1.0.0.'
+                              ' Use `test_epoch_end` instead.', DeprecationWarning)
+
+            elif self.is_overriden('test_epoch_end', model=model):
+                eval_results = model.test_epoch_end(outputs)
+
+        else:
+            if self.is_overriden('validation_end', model=model):
+                # TODO: remove in v1.0.0
+                eval_results = model.validation_end(outputs)
+                warnings.warn('Method `validation_end` was deprecated in 0.7.0 and will be removed 1.0.0.'
+                              ' Use `validation_epoch_end` instead.', DeprecationWarning)
+
+            elif self.is_overriden('validation_epoch_end', model=model):
+                eval_results = model.validation_epoch_end(outputs)
 
         # enable train mode again
         model.train()

tests/trainer/test_trainer.py

@@ -528,15 +528,15 @@ def test_disabled_validation():
     class CurrentModel(LightTrainDataloader, LightValidationMixin, TestModelBase):
 
         validation_step_invoked = False
-        validation_end_invoked = False
+        validation_epoch_end_invoked = False
 
         def validation_step(self, *args, **kwargs):
             self.validation_step_invoked = True
             return super().validation_step(*args, **kwargs)
 
-        def validation_end(self, *args, **kwargs):
-            self.validation_end_invoked = True
-            return super().validation_end(*args, **kwargs)
+        def validation_epoch_end(self, *args, **kwargs):
+            self.validation_epoch_end_invoked = True
+            return super().validation_epoch_end(*args, **kwargs)
 
     hparams = tutils.get_default_hparams()
     model = CurrentModel(hparams)
@@ -555,8 +555,10 @@ def validation_end(self, *args, **kwargs):
     # check that val_percent_check=0 turns off validation
     assert result == 1, 'training failed to complete'
     assert trainer.current_epoch == 1
-    assert not model.validation_step_invoked, '`validation_step` should not run when `val_percent_check=0`'
-    assert not model.validation_end_invoked, '`validation_end` should not run when `val_percent_check=0`'
+    assert not model.validation_step_invoked, \
+        '`validation_step` should not run when `val_percent_check=0`'
+    assert not model.validation_epoch_end_invoked, \
+        '`validation_epoch_end` should not run when `val_percent_check=0`'
 
     # check that val_percent_check has no influence when fast_dev_run is turned on
     model = CurrentModel(hparams)
@@ -566,8 +568,10 @@ def validation_end(self, *args, **kwargs):
 
     assert result == 1, 'training failed to complete'
     assert trainer.current_epoch == 0
-    assert model.validation_step_invoked, 'did not run `validation_step` with `fast_dev_run=True`'
-    assert model.validation_end_invoked, 'did not run `validation_end` with `fast_dev_run=True`'
+    assert model.validation_step_invoked, \
+        'did not run `validation_step` with `fast_dev_run=True`'
+    assert model.validation_epoch_end_invoked, \
+        'did not run `validation_epoch_end` with `fast_dev_run=True`'
 
 
 def test_nan_loss_detection(tmpdir):