linter

Author: Borda

requirements/collect_env_details.py

@@ -70,7 +70,7 @@ def nice_print(details: dict, level: int = 0) -> list:
             lines += [level * LEVEL_OFFSET + key]
             lines += [(level + 1) * LEVEL_OFFSET + "- " + v for v in details[k]]
         else:
-            template = "{:%is} {}" % KEY_PADDING
+            template = "{:%is} {}" % KEY_PADDING  # noqa: UP031
             key_val = template.format(key, details[k])
             lines += [(level * LEVEL_OFFSET) + key_val]
     return lines

src/lightning/pytorch/loggers/utilities.py

@@ -74,7 +74,7 @@ def _log_hyperparams(trainer: "pl.Trainer") -> None:
                 continue
             lm_val, dm_val = lightning_hparams[key], datamodule_hparams[key]
             if (
-                type(lm_val) != type(dm_val)
+                type(lm_val) != type(dm_val)  # noqa: E721
                 or (isinstance(lm_val, Tensor) and id(lm_val) != id(dm_val))
                 or lm_val != dm_val
             ):

tests/tests_fabric/utilities/test_load.py

@@ -56,7 +56,7 @@ def test_lazy_load_tensor(tmp_path):
     for t0, t1 in zip(expected.values(), loaded.values()):
         assert isinstance(t1, _NotYetLoadedTensor)
         t1_materialized = _materialize_tensors(t1)
-        assert type(t0) == type(t1_materialized)
+        assert type(t0) == type(t1_materialized)  # noqa: E721
         assert torch.equal(t0, t1_materialized)
 
 
@@ -92,7 +92,7 @@ def test_materialize_tensors(tmp_path):
     loaded = _lazy_load(tmp_path / "tensor.pt")
     materialized = _materialize_tensors(loaded)
     assert torch.equal(materialized, tensor)
-    assert type(tensor) == type(materialized)
+    assert type(tensor) == type(materialized)  # noqa: E721
 
     # Collection of tensors
     collection = {