group fit data links

pytorch_lightning/trainer/trainer.py

@@ -981,16 +981,8 @@ class Trainer(
         if hasattr(model, 'hparams'):
             parsing.clean_namespace(model.hparams)
 
-        # if a datamodule comes in as the second arg, then fix it for the user
-        if isinstance(train_dataloader, LightningDataModule):
-            datamodule = train_dataloader
-            train_dataloader = None
-
-        self.config_validator.enforce_datamodule_dataloader_override(train_dataloader, val_dataloaders, datamodule)
-
-        # set up the passed in dataloaders (if needed)
-        self.__attach_dataloaders(model, train_dataloader, val_dataloaders)
-        self.__attach_datamodule(model, datamodule, 'fit')
+        # links data to the trainer
+        self.attach_data(model, train_dataloader, val_dataloaders)
 
         # check that model is configured correctly
         self.config_validator.verify_loop_configurations(model)
@@ -1045,6 +1037,18 @@ class Trainer(
         # used for testing or when we need to know that training succeeded
         return results or 1
 
+    def attach_data(self, model, train_dataloader, val_dataloaders):
+        # if a datamodule comes in as the second arg, then fix it for the user
+        if isinstance(train_dataloader, LightningDataModule):
+            datamodule = train_dataloader
+            train_dataloader = None
+
+        self.config_validator.enforce_datamodule_dataloader_override(train_dataloader, val_dataloaders, datamodule)
+
+        # set up the passed in dataloaders (if needed)
+        self.__attach_dataloaders(model, train_dataloader, val_dataloaders)
+        self.__attach_datamodule(model, datamodule, 'fit')
+
     def select_accelerator(self):
         # SLURM ddp
         use_slurm_ddp = self.use_ddp and self.is_slurm_managing_tasks