as discussed, datamodule and dataloaders (from model) are merged. Dat…

…amodule has the precedence
Lightning-AI · Feb 21, 2021 · de60a3b · de60a3b
1 parent f96d871
commit de60a3b
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Showing 2 changed files with 20 additions and 5 deletions.
diff --git a/pytorch_lightning/trainer/configuration_validator.py b/pytorch_lightning/trainer/configuration_validator.py
@@ -38,11 +38,13 @@ def verify_loop_configurations(self, model: LightningModule):
             self.__verify_eval_loop_configuration(model, 'test')
 
     def __verify_train_dataloader(self, model):
+        # We COMBINE dataloaders and datamodule. Datamodule has precedence
+
+        has_train_dataloader = False
         if self.trainer.datamodule:
-            has_train_dataloader = is_overridden(
-                'train_dataloader', self.trainer.datamodule
-            )
-        else:
+            has_train_dataloader = is_overridden('train_dataloader', self.trainer.datamodule)
+
+        if not has_train_dataloader:
             has_train_dataloader = is_overridden('train_dataloader', model)
 
         if not has_train_dataloader:

diff --git a/pytorch_lightning/trainer/data_loading.py b/pytorch_lightning/trainer/data_loading.py
@@ -21,6 +21,7 @@
 from torch.utils.data import BatchSampler, DataLoader, RandomSampler, SequentialSampler
 from torch.utils.data.distributed import DistributedSampler
 
+from pytorch_lightning import _logger as log
 from pytorch_lightning.accelerators import Accelerator
 from pytorch_lightning.core import LightningModule
 from pytorch_lightning.trainer.supporters import CombinedLoader
@@ -196,8 +197,20 @@ def reset_train_dataloader(self, model: LightningModule) -> None:
             model: The current `LightningModule`
         """
 
-        # TODO - what if we pass `train_dataloader` as input, instead of model?
+        # TODO - what if we pass `train_dataloader` as input, in
+        model_has_loader = is_overridden('train_dataloader', model)
+        datamodule_has_loader = False
+
         if self.datamodule:
+            datamodule_has_loader = is_overridden('train_dataloader', model)
+
+        if datamodule_has_loader and model_has_loader:
+            log.info(
+                "You implemented `train_dataloader` both in model and datamodule. Please note that datamodule implementation has precedence"
+            )
+
+        # Configuration_validation has already checked that either datamodule or model has overridden train_dataloader
+        if datamodule_has_loader:
             train_dataloader = self.datamodule.train_dataloader
         else:
             train_dataloader = model.train_dataloader