fix unknown parameters

app.py

@@ -1,8 +1,9 @@
 PATH = 'harpomaxx/deeplili' #stable diffusion 1.5
+from PIL import Image
 import torch
-#from transformers import CLIPTextModel, CLIPTokenizer
-#from diffusers import AutoencoderKL, UNet2DConditionModel, PNDMScheduler
-#from diffusers import UniPCMultistepScheduler
+from transformers import CLIPTextModel, CLIPTokenizer
+from diffusers import AutoencoderKL, UNet2DConditionModel, PNDMScheduler
+from diffusers import UniPCMultistepScheduler
 from diffusers import StableDiffusionPipeline
 from PIL import Image
 from tqdm.auto import tqdm
@@ -12,7 +13,7 @@ import gradio as gr
 guidance_scale = 8.5  # Scale for classifier-free guidance
 
 
-pipe = StableDiffusionPipeline.from_pretrained(PATH,local_files_only=False ).to("cpu")
+pipe = StableDiffusionPipeline.from_pretrained(PATH,local_files_only=False ).to("cuda")
 guidance_scale = 8.5
 
 def generate_images(prompt, guidance_scale, n_samples, num_inference_steps):
@@ -26,7 +27,7 @@ def generate_images(prompt, guidance_scale, n_samples, num_inference_steps):
 
 def gr_generate_images(prompt: str, num_images: int, num_inference: int):
     prompt = prompt + "sks style"
-    images = generate_images(prompt, tokenizer, text_encoder, unet, vae, scheduler, guidance_scale, num_images, num_inference)
+    images = generate_images(prompt, guidance_scale, num_images, num_inference)
     return images
 
 with gr.Blocks() as demo:
@@ -110,4 +111,5 @@ with gr.Blocks() as demo:
     )
 
 if __name__ == "__main__":
+    #demo.launch(share=True)
     demo.queue().launch(share=True)