[misc] update pre-commit and run all files (#4752)

* [misc] update pre-commit

* [misc] run pre-commit

* [misc] remove useless configuration files

* [misc] ignore cuda for clang-format

examples/images/diffusion/scripts/tests/test_checkpoint.py

@@ -1,28 +1,18 @@
-import os
-import sys
-from copy import deepcopy
-
-import yaml
-from datetime import datetime
-
-from diffusers import StableDiffusionPipeline
 import torch
-
-from main import get_parser
+import yaml
+from diffusers import StableDiffusionPipeline
 from ldm.modules.diffusionmodules.openaimodel import UNetModel
 
 if __name__ == "__main__":
     with torch.no_grad():
         yaml_path = "../../train_colossalai.yaml"
-        with open(yaml_path, 'r', encoding='utf-8') as f:
+        with open(yaml_path, "r", encoding="utf-8") as f:
             config = f.read()
         base_config = yaml.load(config, Loader=yaml.FullLoader)
-        unet_config = base_config['model']['params']['unet_config']
+        unet_config = base_config["model"]["params"]["unet_config"]
         diffusion_model = UNetModel(**unet_config).to("cuda:0")
 
-        pipe = StableDiffusionPipeline.from_pretrained(
-            "/data/scratch/diffuser/stable-diffusion-v1-4"
-        ).to("cuda:0")
+        pipe = StableDiffusionPipeline.from_pretrained("/data/scratch/diffuser/stable-diffusion-v1-4").to("cuda:0")
         dif_model_2 = pipe.unet
 
         random_input_ = torch.rand((4, 4, 32, 32)).to("cuda:0")
@@ -35,4 +25,4 @@ if __name__ == "__main__":
         out_1 = diffusion_model(random_input_, time_stamp, context_)
         out_2 = dif_model_2(random_input_2, time_stamp2, context_2)
         print(out_1.shape)
-        print(out_2['sample'].shape)
+        print(out_2["sample"].shape)