isort pipeline

pipeline.py

@@ -1,37 +1,27 @@
+from collections import OrderedDict
 from typing import Any, Dict, Optional
-from diffusers.schedulers import KarrasDiffusionSchedulers
 
+import diffusers
 import numpy
+import rembg
 import torch
+import torch.distributed
 import torch.nn as nn
 import torch.utils.checkpoint
-import torch.distributed
 import transformers
-from collections import OrderedDict
+from diffusers import (AutoencoderKL, DDPMScheduler, DiffusionPipeline,
+                       EulerAncestralDiscreteScheduler, UNet2DConditionModel)
+from diffusers.image_processor import VaeImageProcessor
+from diffusers.models.attention_processor import (Attention, AttnProcessor,
+                                                  AttnProcessor2_0,
+                                                  XFormersAttnProcessor)
+from diffusers.schedulers import KarrasDiffusionSchedulers
+from diffusers.utils import BaseOutput
+from diffusers.utils.import_utils import is_xformers_available
 from PIL import Image
 from torchvision import transforms
-from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
-from diffusers.utils import BaseOutput
-
-import rembg
 from torchvision.transforms import v2
-
-import diffusers
-from diffusers import (
-    AutoencoderKL,
-    DDPMScheduler,
-    DiffusionPipeline,
-    EulerAncestralDiscreteScheduler,
-    UNet2DConditionModel,
-)
-from diffusers.image_processor import VaeImageProcessor
-from diffusers.models.attention_processor import (
-    Attention,
-    AttnProcessor,
-    XFormersAttnProcessor,
-    AttnProcessor2_0,
-)
-from diffusers.utils.import_utils import is_xformers_available
+from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
 
 
 def to_rgb_image(maybe_rgba: Image.Image):