merge conflict fix

Author: ved1beta

docs/source-pytorch/common/trainer.rst

@@ -774,7 +774,7 @@ Useful for quickly debugging or trying to overfit on purpose.
 
     # overfit on 10 consistent train batches & 10 consistent val batches
     trainer = Trainer(overfit_batches=10)
-    
+
     # debug using a single consistent train batch and a single consistent val batch
 
 
@@ -962,7 +962,7 @@ Additionally, you can pass a strategy object.
 See Also:
     - :ref:`Multi GPU Training <multi_gpu>`.
     - :doc:`Model Parallel GPU training guide <../advanced/model_parallel>`.
-    - :doc:`TPU training guide <../accelerators/tpu>`. 
+    - :doc:`TPU training guide <../accelerators/tpu>`.
 
 
 sync_batchnorm

src/lightning/pytorch/trainer/connectors/data_connector.py

@@ -245,10 +245,10 @@ def _get_distributed_sampler(
 
 def _resolve_overfit_batches(combined_loader: CombinedLoader, mode: RunningStage) -> None:
     """Resolve overfit batches by disabling shuffling.
-    
-    When overfit_batches > 0, this function ensures that sequential sampling is used
-    without shuffling for consistent batches across epochs. Training and validation
-    use different sets of data.
+
+    When overfit_batches > 0, this function ensures that sequential sampling is used without shuffling for consistent
+    batches across epochs. Training and validation use different sets of data.
+
     """
     all_have_sequential_sampler = all(
         isinstance(dl.sampler, SequentialSampler) for dl in combined_loader.flattened if hasattr(dl, "sampler")
@@ -260,7 +260,7 @@ def _resolve_overfit_batches(combined_loader: CombinedLoader, mode: RunningStage
         f"You requested to overfit but enabled {mode.dataloader_prefix} dataloader shuffling."
         f" We are turning off the {mode.dataloader_prefix} dataloader shuffling for you."
     )
-    
+
     updated = [
         _update_dataloader(dl, sampler=SequentialSampler(dl.dataset), mode=mode) if hasattr(dl, "dataset") else dl
         for dl in combined_loader.flattened