update app.py for exhibition

app.py

@@ -1,31 +1,25 @@
 PATH = 'harpomaxx/deeplili' #stable diffusion 1.5
 from PIL import Image
 import torch
-from transformers import CLIPTextModel, CLIPTokenizer
-from PIL import Image
+import torch.distributed as dist
+import torch.multiprocessing as mp
+import argparse
+
+from diffusers import StableDiffusionPipeline, LMSDiscreteScheduler
 from tqdm.auto import tqdm
 import random
 import gradio as gr
-from diffusers import StableDiffusionPipeline, LMSDiscreteScheduler
-
-
-
-guidance_scale = 8.5  # Scale for classifier-free guidance
-
-
-pipe = StableDiffusionPipeline.from_pretrained(PATH,local_files_only=False ).to("cpu")
-guidance_scale = 8.5
 
 def generate_images(prompt, guidance_scale, n_samples, num_inference_steps):
     seeds = [random.randint(1, 10000) for _ in range(n_samples)]
-    images = [] 
+    images = []
     for seed in tqdm(seeds):
         torch.manual_seed(seed)
-        image = pipe(prompt, num_inference_steps=num_inference_steps,guidance_scale=guidance_scale).images[0]   
+        image = pipe(prompt, num_inference_steps=num_inference_steps,guidance_scale=guidance_scale).images[0]
         images.append(image)
     return images
 
-def gr_generate_images(prompt: str, num_images: int, num_inference: int):
+def gr_generate_images(prompt: str, num_images = 1, num_inference = 20, guidance_scale = 8 ):
     prompt = prompt + "sks style"
     images = generate_images(prompt, guidance_scale, num_images, num_inference)
     return images
@@ -35,36 +29,37 @@ with gr.Blocks() as demo:
     [
         'A black and white cute character on top of a hill',
         1,
-	30
+        30
     ],
     [
         'Bubbles and mountains in the sky',
         1,
-	20
+        20
     ],
     [
         'A tree with multiple eyes and a small flower muted colors',
         1,
-	20
+        20
     ],
     [
         "3d character on top of a hill",
         1,
-	20
+        20
     ],
     [
         "a poster of a large forest with black and white characters",
         1,
-	20
+        20
     ],
     ]
     gr.Markdown(
     """
     <img src="https://github.com/harpomaxx/DeepLili/raw/main/images/lilifiallo/660.png" width="150" height="150">
 
-    # #DeepLili v0.45b
+    # #DeepLili v0.5b
 
     ## Enter your prompt and generate a work of art in the style of Lili's Toy Art paintings.
+    ## (English, Spanish)
     """
     )
 
@@ -78,39 +73,75 @@ with gr.Blocks() as demo:
             ).style(
                 container=False,
             )
-          
+
         with gr.Row(variant="compact"):
-            num_images_slider = gr.Slider(
-                minimum=1,
-                maximum=10,
-                step=1,
-                value=1,
-                label="Number of Images",
-            )
-   
-            num_inference_steps_slider = gr.Slider(
-                minimum=1,
-                maximum=25,
-                step=1,
-                value=20,
-                label="Number of Inference Steps",
-            )
+          #  num_images_slider = gr.Slider(
+          #      minimum=1,
+          #      maximum=10,
+          #      step=1,
+          #      value=1,
+          #      label="Number of Images",
+          #  )
+
+          #  num_inference_steps_slider = gr.Slider(
+          #      minimum=1,
+          #      maximum=25,
+          #      step=1,
+          #      value=20,
+          #      label="Inference Steps",
+          #  )
+
+          #  guidance_slider = gr.Slider(
+          #      minimum=1,
+          #      maximum=14,
+          #      step=1,
+          #      value=8,
+          #      label="Guidance Scale",
+          #  )
+
+
 
             btn = gr.Button("Generate image").style(full_width=False)
-      
+
         gallery = gr.Gallery(
             label="Generated images", show_label=False, elem_id="gallery"
-        ).style(columns=[5], rows=[1], object_fit="contain", height="250px", width="250px")
+        ).style(columns=[1], rows=[1], object_fit="contain", height="512px", width="512px")
+
+    num_images_slider = 1
+    num_inference_steps_slider = 20
+    guidance_slider = 8
 
-    btn.click(gr_generate_images, [text, num_images_slider,num_inference_steps_slider], gallery)
+    btn.click(gr_generate_images, [text], gallery)
     gr.Examples(examples, inputs=[text])
     gr.HTML(
     """
     <h6><a href="https://harpomaxx.github.io/"> harpomaxx </a></h6>
-    <h6> This space is running on CPU. So it gonna be very slow!!!! </h6>
     """
     )
 
 if __name__ == "__main__":
-    #demo.launch(share=True)
-    demo.queue().launch()
+
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "--ip",
+        default="0.0.0.0",
+        help="The IP address to of the server"
+    )
+    parser.add_argument(
+        "--port",
+        type=int,
+        default=7860,
+        help="The port used"
+    )
+    parser.add_argument(
+        "--gpuid",
+        default="0",
+        help="The gpu id"
+    )
+
+    args = parser.parse_args()
+    pipe = StableDiffusionPipeline.from_single_file(PATH,torch_dtype=torch.float16).to(f"cuda:{args.gpuid}")
+    demo.queue(concurrency_count=2,
+            ).launch(server_name = args.ip, server_port = args.port)
+~