diff --git a/examples/research_projects/intel_opts/textual_inversion/textual_inversion_bf16.py b/examples/research_projects/intel_opts/textual_inversion/textual_inversion_bf16.py
index a1aff1d91c..f20db249ec 100644
--- a/examples/research_projects/intel_opts/textual_inversion/textual_inversion_bf16.py
+++ b/examples/research_projects/intel_opts/textual_inversion/textual_inversion_bf16.py
@@ -336,7 +336,10 @@ class TextualInversionDataset(Dataset):
 
         if self.center_crop:
             crop = min(img.shape[0], img.shape[1])
-            (h, w,) = (
+            (
+                h,
+                w,
+            ) = (
                 img.shape[0],
                 img.shape[1],
             )
diff --git a/examples/textual_inversion/textual_inversion.py b/examples/textual_inversion/textual_inversion.py
index d6c27444e0..1c4bd235e6 100644
--- a/examples/textual_inversion/textual_inversion.py
+++ b/examples/textual_inversion/textual_inversion.py
@@ -432,7 +432,10 @@ class TextualInversionDataset(Dataset):
 
         if self.center_crop:
             crop = min(img.shape[0], img.shape[1])
-            (h, w,) = (
+            (
+                h,
+                w,
+            ) = (
                 img.shape[0],
                 img.shape[1],
             )
diff --git a/examples/textual_inversion/textual_inversion_flax.py b/examples/textual_inversion/textual_inversion_flax.py
index 69637c3645..b37d1e2ac4 100644
--- a/examples/textual_inversion/textual_inversion_flax.py
+++ b/examples/textual_inversion/textual_inversion_flax.py
@@ -306,7 +306,10 @@ class TextualInversionDataset(Dataset):
 
         if self.center_crop:
             crop = min(img.shape[0], img.shape[1])
-            (h, w,) = (
+            (
+                h,
+                w,
+            ) = (
                 img.shape[0],
                 img.shape[1],
             )
diff --git a/src/diffusers/models/attention.py b/src/diffusers/models/attention.py
index ec5d6fdb38..b5acd6f4f9 100644
--- a/src/diffusers/models/attention.py
+++ b/src/diffusers/models/attention.py
@@ -94,8 +94,10 @@ class AttentionBlock(nn.Module):
         if use_memory_efficient_attention_xformers:
             if not is_xformers_available():
                 raise ModuleNotFoundError(
-                    "Refer to https://github.com/facebookresearch/xformers for more information on how to install"
-                    " xformers",
+                    (
+                        "Refer to https://github.com/facebookresearch/xformers for more information on how to install"
+                        " xformers"
+                    ),
                     name="xformers",
                 )
             elif not torch.cuda.is_available():
diff --git a/src/diffusers/models/cross_attention.py b/src/diffusers/models/cross_attention.py
index 5f0777327d..a1d77f66ef 100644
--- a/src/diffusers/models/cross_attention.py
+++ b/src/diffusers/models/cross_attention.py
@@ -111,8 +111,10 @@ class CrossAttention(nn.Module):
                 )
             elif not is_xformers_available():
                 raise ModuleNotFoundError(
-                    "Refer to https://github.com/facebookresearch/xformers for more information on how to install"
-                    " xformers",
+                    (
+                        "Refer to https://github.com/facebookresearch/xformers for more information on how to install"
+                        " xformers"
+                    ),
                     name="xformers",
                 )
             elif not torch.cuda.is_available():
diff --git a/src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py b/src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py
index de5203e793..45f939aafe 100644
--- a/src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py
+++ b/src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py
@@ -189,9 +189,11 @@ class EulerAncestralDiscreteScheduler(SchedulerMixin, ConfigMixin):
             or isinstance(timestep, torch.LongTensor)
         ):
             raise ValueError(
-                "Passing integer indices (e.g. from `enumerate(timesteps)`) as timesteps to"
-                " `EulerDiscreteScheduler.step()` is not supported. Make sure to pass"
-                " one of the `scheduler.timesteps` as a timestep.",
+                (
+                    "Passing integer indices (e.g. from `enumerate(timesteps)`) as timesteps to"
+                    " `EulerDiscreteScheduler.step()` is not supported. Make sure to pass"
+                    " one of the `scheduler.timesteps` as a timestep."
+                ),
             )
 
         if not self.is_scale_input_called:
diff --git a/src/diffusers/schedulers/scheduling_euler_discrete.py b/src/diffusers/schedulers/scheduling_euler_discrete.py
index 32adf5a61c..02e5c2cd99 100644
--- a/src/diffusers/schedulers/scheduling_euler_discrete.py
+++ b/src/diffusers/schedulers/scheduling_euler_discrete.py
@@ -198,9 +198,11 @@ class EulerDiscreteScheduler(SchedulerMixin, ConfigMixin):
             or isinstance(timestep, torch.LongTensor)
         ):
             raise ValueError(
-                "Passing integer indices (e.g. from `enumerate(timesteps)`) as timesteps to"
-                " `EulerDiscreteScheduler.step()` is not supported. Make sure to pass"
-                " one of the `scheduler.timesteps` as a timestep.",
+                (
+                    "Passing integer indices (e.g. from `enumerate(timesteps)`) as timesteps to"
+                    " `EulerDiscreteScheduler.step()` is not supported. Make sure to pass"
+                    " one of the `scheduler.timesteps` as a timestep."
+                ),
             )
 
         if not self.is_scale_input_called:
diff --git a/tests/test_scheduler.py b/tests/test_scheduler.py
index 9d74cac698..d49d599c57 100755
--- a/tests/test_scheduler.py
+++ b/tests/test_scheduler.py
@@ -537,8 +537,10 @@ class SchedulerCommonTest(unittest.TestCase):
                 )
                 self.assertTrue(
                     hasattr(scheduler, "scale_model_input"),
-                    f"{scheduler_class} does not implement a required class method `scale_model_input(sample,"
-                    " timestep)`",
+                    (
+                        f"{scheduler_class} does not implement a required class method `scale_model_input(sample,"
+                        " timestep)`"
+                    ),
                 )
             self.assertTrue(
                 hasattr(scheduler, "step"),