fix

CHANGELOG.md

@@ -75,7 +75,6 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added a warning when using `DistributedSampler` during evaluation ([#11479](https://github.com/PyTorchLightning/pytorch-lightning/pull/11479))
 
 
-
 ### Changed
 
 - Raised exception in `init_dist_connection()` when torch distibuted is not available ([#10418](https://github.com/PyTorchLightning/pytorch-lightning/issues/10418))

docs/source/common/test_set.rst

@@ -146,10 +146,10 @@ Apart from this ``.validate`` has same API as ``.test``, but would rely respecti
 
 .. automethod:: pytorch_lightning.trainer.Trainer.validate
     :noindex:
-    
+
 .. warning::
 
-    It is recommended to test on single device since Distributed Training such as DDP internally
+    It is recommended to validate on single device since Distributed Training such as DDP internally
     uses :class:`~torch.utils.data.distributed.DistributedSampler` which replicates some samples to
     make sure all devices have same batch size in case of uneven inputs. This is helpful to make sure
     benchmarking for research papers is done the right way.

pytorch_lightning/trainer/connectors/data_connector.py

@@ -396,10 +396,12 @@ def _resolve_sampler(self, dataloader: DataLoader, shuffle: bool, mode: Optional
             trainer_fn = self.trainer.state.fn
             if isinstance(sampler, DistributedSampler) and trainer_fn in (TrainerFn.VALIDATING, TrainerFn.TESTING):
                 rank_zero_warn(
-                    'Using `DistributedSampler` with the dataloaders. It is recommended to'
-                    ' use single device strategy with evaluation.'
+                    "Using `DistributedSampler` with the dataloaders. It is recommended to"
+                    " use single device strategy with evaluation."
                 )
 
+            return sampler
+
         return dataloader.sampler
 
     @staticmethod

tests/trainer/connectors/test_data_connector.py

@@ -14,12 +14,11 @@
 from unittest.mock import Mock
 
 import pytest
-from pytorch_lightning.accelerators import accelerator
-from pytorch_lightning.trainer.states import TrainerFn
 from torch.utils.data import DataLoader
 
-from pytorch_lightning import Trainer, strategies
+from pytorch_lightning import Trainer
 from pytorch_lightning.trainer.connectors.data_connector import _DataLoaderSource
+from pytorch_lightning.trainer.states import TrainerFn
 from tests.helpers import BoringDataModule, BoringModel
 
 
@@ -74,16 +73,15 @@ def test_eval_distributed_sampler_warning(tmpdir):
     """Test that a warning is raised with `DistributedSampler` is used with evaluation."""
 
     model = BoringModel()
-    trainer = Trainer(strategy='ddp', devices=2, accelerator='cpu')
+    trainer = Trainer(strategy="ddp", devices=2, accelerator="cpu")
     trainer._data_connector.attach_data(model)
 
     # validation
-    with pytest.warns(UserWarning, match = 'It is recommended to use single device strategy'):
+    with pytest.warns(UserWarning, match="It is recommended to use single device strategy"):
         trainer.state.fn = TrainerFn.VALIDATING
         trainer.reset_val_dataloader(model)
 
     # testing
-    with pytest.warns(UserWarning, match = 'It is recommended to use single device strategy'):
+    with pytest.warns(UserWarning, match="It is recommended to use single device strategy"):
         trainer.state.fn = TrainerFn.TESTING
         trainer.reset_test_dataloader(model)
-