Update train_dreambooth_colossalai.py

examples/research_projects/colossalai/train_dreambooth_colossalai.py

@@ -365,10 +365,10 @@ def gemini_zero_dpp(model: torch.nn.Module, placememt_policy: str = "auto"):
 
 
 def main(args):
-    colossalai.launch_from_torch(config={})
-
-    if args.seed is not None:
-        gpc.set_seed(args.seed)
+    if args.seed is None:
+        colossalai.launch_from_torch(config={})
+    else:
+        colossalai.launch_from_torch(config={}, seed=args.seed)
 
     if args.with_prior_preservation:
         class_images_dir = Path(args.class_data_dir)

examples/research_projects/intel_opts/textual_inversion/textual_inversion_bf16.py

@@ -336,7 +336,10 @@ def __getitem__(self, i):
 
         if self.center_crop:
             crop = min(img.shape[0], img.shape[1])
-            (h, w,) = (
+            (
+                h,
+                w,
+            ) = (
                 img.shape[0],
                 img.shape[1],
             )

examples/textual_inversion/textual_inversion.py

@@ -381,7 +381,10 @@ def __getitem__(self, i):
 
         if self.center_crop:
             crop = min(img.shape[0], img.shape[1])
-            (h, w,) = (
+            (
+                h,
+                w,
+            ) = (
                 img.shape[0],
                 img.shape[1],
             )

examples/textual_inversion/textual_inversion_flax.py

@@ -306,7 +306,10 @@ def __getitem__(self, i):
 
         if self.center_crop:
             crop = min(img.shape[0], img.shape[1])
-            (h, w,) = (
+            (
+                h,
+                w,
+            ) = (
                 img.shape[0],
                 img.shape[1],
             )

src/diffusers/models/attention.py

@@ -90,8 +90,10 @@ def set_use_memory_efficient_attention_xformers(self, use_memory_efficient_atten
         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():

src/diffusers/models/cross_attention.py

@@ -105,8 +105,10 @@ def set_use_memory_efficient_attention_xformers(self, use_memory_efficient_atten
                 )
             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():

src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py

@@ -189,9 +189,11 @@ def step(
             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:

src/diffusers/schedulers/scheduling_euler_discrete.py

@@ -198,9 +198,11 @@ def step(
             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:

tests/test_scheduler.py

@@ -537,8 +537,10 @@ def test_scheduler_public_api(self):
                 )
                 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"),