fix style

Author: faaany

examples/research_projects/geodiff/geodiff_molecule_conformation.ipynb

@@ -26,8 +26,7 @@
     "%load_ext autoreload\n",
     "%autoreload 2\n",
     "\n",
-    "import torch\n",
-    "from diffusers import StableDiffusionGLIGENTextImagePipeline, StableDiffusionGLIGENPipeline"
+    "from diffusers import StableDiffusionGLIGENPipeline"
    ]
   },
   {
@@ -36,16 +35,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import os\n",
+    "from transformers import CLIPTextModel, CLIPTokenizer\n",
+    "\n",
     "import diffusers\n",
     "from diffusers import (\n",
     "    AutoencoderKL,\n",
     "    DDPMScheduler,\n",
-    "    UNet2DConditionModel,\n",
-    "    UniPCMultistepScheduler,\n",
     "    EulerDiscreteScheduler,\n",
+    "    UNet2DConditionModel,\n",
     ")\n",
-    "from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer\n",
+    "\n",
+    "\n",
     "# pretrained_model_name_or_path = 'masterful/gligen-1-4-generation-text-box'\n",
     "\n",
     "pretrained_model_name_or_path = '/root/data/zhizhonghuang/checkpoints/models--masterful--gligen-1-4-generation-text-box/snapshots/d2820dc1e9ba6ca082051ce79cfd3eb468ae2c83'\n",
@@ -122,6 +122,7 @@
     "\n",
     "import numpy as np\n",
     "\n",
+    "\n",
     "boxes = np.array([x[1] for x in gen_boxes])\n",
     "boxes = boxes / 512\n",
     "boxes[:, 2] = boxes[:, 0] + boxes[:, 2]\n",

examples/research_projects/gligen/demo.ipynb

@@ -57,9 +57,8 @@
     get_python_version,
     is_torch_compile,
     require_torch_2,
-    require_torch_accelerator_with_training,
-    require_torch_gpu,
     require_torch_accelerator,
+    require_torch_accelerator_with_training,
     require_torch_multi_gpu,
     run_test_in_subprocess,
     torch_all_close,

tests/models/test_modeling_common.py

@@ -22,7 +22,6 @@
 from diffusers.utils.testing_utils import (
     numpy_cosine_similarity_distance,
     require_accelerator,
-    require_torch_gpu,
     require_torch_accelerator,
     slow,
     torch_device,

tests/pipelines/animatediff/test_animatediff.py

@@ -26,7 +26,6 @@
 from diffusers.utils.testing_utils import (
     enable_full_determinism,
     numpy_cosine_similarity_distance,
-    require_torch_gpu,
     require_torch_accelerator,
     slow,
     torch_device,

tests/pipelines/cogvideo/test_cogvideox_image2video.py

@@ -40,8 +40,8 @@
     load_image,
     load_numpy,
     require_torch_2,
-    require_torch_gpu,
     require_torch_accelerator,
+    require_torch_gpu,
     run_test_in_subprocess,
     slow,
     torch_device,
@@ -964,7 +964,7 @@ def test_sequential_cpu_offloading(self):
             num_inference_steps=2,
             output_type="np",
         )
-        
+
         if torch_device == "cuda":
             mem_bytes = torch.cuda.max_memory_allocated()
         elif torch_device == "xpu":

tests/pipelines/controlnet/test_controlnet.py

@@ -28,7 +28,12 @@
     UNet2DConditionModel,
 )
 from diffusers.utils.import_utils import is_xformers_available
-from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, require_torch_accelerator, torch_device
+from diffusers.utils.testing_utils import (
+    enable_full_determinism,
+    floats_tensor,
+    require_torch_accelerator,
+    torch_device,
+)
 
 from ..pipeline_params import (
     IMAGE_TO_IMAGE_IMAGE_PARAMS,

tests/pipelines/controlnet/test_controlnet_sdxl_img2img.py

@@ -40,7 +40,6 @@
     load_numpy,
     require_accelerator,
     require_torch_2,
-    require_torch_gpu,
     require_torch_accelerator,
     run_test_in_subprocess,
     slow,

tests/pipelines/controlnet_xs/test_controlnetxs.py

@@ -31,7 +31,13 @@
     UNet2DConditionModel,
 )
 from diffusers.utils.import_utils import is_xformers_available
-from diffusers.utils.testing_utils import enable_full_determinism, load_image, require_torch_accelerator, slow, torch_device
+from diffusers.utils.testing_utils import (
+    enable_full_determinism,
+    load_image,
+    require_torch_accelerator,
+    slow,
+    torch_device,
+)
 from diffusers.utils.torch_utils import randn_tensor
 
 from ...models.autoencoders.vae import (

tests/pipelines/controlnet_xs/test_controlnetxs_sdxl.py

@@ -124,7 +124,7 @@ def test_if_img2img_superresolution(self):
         )
         pipe.unet.set_attn_processor(AttnAddedKVProcessor())
         pipe.enable_model_cpu_offload(device=torch_device)
-        
+
         if torch_device == "cuda":
             torch.cuda.reset_max_memory_allocated()
             torch.cuda.empty_cache()