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

@@ -14,7 +14,7 @@
 import logging
 import os
 import re
-from typing import Any, Dict, Optional, List
+from typing import Any, Dict, List, Optional
 
 import torch
 from fsspec.core import url_to_fs
@@ -521,7 +521,8 @@ def _get_loops_state_dict(self) -> Dict[str, Any]:
 
     def _get_dataloader_state_dicts(self) -> List[Dict[str, Any]]:
         return [
-            train_dataloader.state_dict() for train_dataloader in (self.trainer.train_dataloader or [])
+            train_dataloader.state_dict()
+            for train_dataloader in (self.trainer.train_dataloader or [])
             if isinstance(train_dataloader, _Stateful)
         ]
 

tests/tests_pytorch/trainer/connectors/test_checkpoint_connector.py

@@ -12,20 +12,17 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import os
-from copy import deepcopy
 from unittest import mock
 from unittest.mock import Mock
 
 import pytest
 import torch
-from torch.utils.data import DataLoader
-
 from lightning.pytorch import Trainer
 from lightning.pytorch.callbacks import ModelCheckpoint
 from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
 from lightning.pytorch.trainer.states import TrainerFn
 from lightning.pytorch.utilities.migration.utils import _set_version
-from lightning.pytorch.trainer.connectors.checkpoint_connector import _CheckpointConnector
+from torch.utils.data import DataLoader
 
 
 def test_preloaded_checkpoint_lifecycle(tmpdir):
@@ -235,12 +232,14 @@ def load_state_dict(self, state_dict):
         self._counter = state_dict["counter"]
 
 
-@pytest.mark.parametrize(("train_dataloaders", "expected_states"), [
-    ([], None),
-    (StatefulDataLoader(RandomDataset(32, 64)), [{"counter": 0}]),
-])
+@pytest.mark.parametrize(
+    ("train_dataloaders", "expected_states"),
+    [
+        ([], None),
+        (StatefulDataLoader(RandomDataset(32, 64)), [{"counter": 0}]),
+    ],
+)
 def test_train_dataloaders_restore(train_dataloaders, expected_states, tmp_path):
-
     class TestModel(BoringModel):
         def train_dataloader(self):
             return train_dataloaders