Updated dataloader str method

Made changes to comply with requested suggestions
Switched from hardcoded \n to more general os.linesep

Author: MrWhatZitToYaa

src/lightning/pytorch/core/datamodule.py

@@ -14,6 +14,7 @@
 """LightningDataModule for loading DataLoaders with ease."""
 
 import inspect
+import os
 from typing import IO, Any, Dict, Iterable, Optional, Union, cast
 
 from lightning_utilities import apply_to_collection
@@ -251,7 +252,7 @@ def __str__(self) -> str:
             A string representation of the datasets that are setup.
 
         """
-        datasets_info = []
+        datasets_info: Optional[str] = []
 
         def len_implemented(obj):
             try:
@@ -273,4 +274,4 @@ def len_implemented(obj):
         if not datasets_info:
             return "No datasets are set up."
 
-        return "\n".join(datasets_info) + "\n"
+        return os.linesep.join(datasets_info)

tests/tests_pytorch/core/test_datamodules.py

@@ -11,6 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+import os
 import pickle
 from argparse import Namespace
 from dataclasses import dataclass
@@ -526,48 +527,53 @@ def test_datamodule_string_no_datasets():
 
 def test_datamodule_string_no_length():
     dm = BoringDataModuleNoLen()
-    expected_output = "name=random_full, size=Unavailable\n"
+    expected_output = "name=random_full, size=Unavailable"
     assert str(dm) == expected_output
 
 
 def test_datamodule_string_length_not_implemented():
     dm = BoringDataModuleLenNotImplemented()
-    expected_output = "name=random_full, size=Unavailable\n"
+    expected_output = "name=random_full, size=Unavailable"
     assert str(dm) == expected_output
 
 
 def test_datamodule_string_fit_setup():
     dm = BoringDataModule()
     dm.setup(stage="fit")
 
-    expected_outputs = ["name=random_full, size=256\n", "name=random_train, size=64\n", "name=random_val, size=64\n"]
+    expected_output = (
+        f"name=random_full, size=256{os.linesep}" f"name=random_train, size=64{os.linesep}" f"name=random_val, size=64"
+    )
     output = str(dm)
-    for expected_output in expected_outputs:
-        assert expected_output in output
+
+    assert expected_output == output
 
 
 def test_datamodule_string_validation_setup():
     dm = BoringDataModule()
     dm.setup(stage="validate")
-    expected_outputs = ["name=random_full, size=256\n", "name=random_val, size=64\n"]
+
+    expected_output = f"name=random_full, size=256{os.linesep}" f"name=random_val, size=64"
     output = str(dm)
-    for expected_output in expected_outputs:
-        assert expected_output in output
+
+    assert expected_output == output
 
 
 def test_datamodule_string_test_setup():
     dm = BoringDataModule()
     dm.setup(stage="test")
-    expected_outputs = ["name=random_full, size=256\n", "name=random_test, size=64\n"]
+
+    expected_output = f"name=random_full, size=256{os.linesep}" f"name=random_test, size=64"
     output = str(dm)
-    for expected_output in expected_outputs:
-        assert expected_output in output
+
+    assert expected_output == output
 
 
 def test_datamodule_string_predict_setup():
     dm = BoringDataModule()
     dm.setup(stage="predict")
-    expected_outputs = ["name=random_full, size=256\n", "name=random_predict, size=64\n"]
+
+    expected_output = f"name=random_full, size=256{os.linesep}" f"name=random_predict, size=64"
     output = str(dm)
-    for expected_output in expected_outputs:
-        assert expected_output in output
+
+    assert expected_output == output