[tiny] Fix training_dataloader usage to be train_dataloader instead. (#…

…2521)

Co-authored-by: Vijay Rajaram <vrajaram3@gatech.edu>

pytorch_lightning/trainer/trainer.py

@@ -1274,17 +1274,17 @@ def check_model_configuration(self, model: LightningModule):
             if not self.is_overridden('training_step', model):
                 raise MisconfigurationException(
                     'No `training_step()` method defined. Lightning `Trainer` expects as minimum a'
-                    ' `training_step()`, `training_dataloader()` and `configure_optimizers()` to be defined.')
+                    ' `training_step()`, `train_dataloader()` and `configure_optimizers()` to be defined.')
 
             if not self.is_overridden('train_dataloader', model):
                 raise MisconfigurationException(
                     'No `train_dataloader()` method defined. Lightning `Trainer` expects as minimum a'
-                    ' `training_step()`, `training_dataloader()` and `configure_optimizers()` to be defined.')
+                    ' `training_step()`, `train_dataloader()` and `configure_optimizers()` to be defined.')
 
             if not self.is_overridden('configure_optimizers', model):
                 raise MisconfigurationException(
                     'No `configure_optimizers()` method defined. Lightning `Trainer` expects as minimum a'
-                    ' `training_step()`, `training_dataloader()` and `configure_optimizers()` to be defined.')
+                    ' `training_step()`, `train_dataloader()` and `configure_optimizers()` to be defined.')
 
             # Check val_dataloader, validation_step and validation_epoch_end
             if self.is_overridden('val_dataloader', model):

tests/trainer/test_checks.py

@@ -11,7 +11,7 @@
 
 def test_wrong_train_setting(tmpdir):
     """
-    * Test that an error is thrown when no `training_dataloader()` is defined
+    * Test that an error is thrown when no `train_dataloader()` is defined
     * Test that an error is thrown when no `training_step()` is defined
     """
     tutils.reset_seed()