Update app.py

app.py

@@ -1,4 +1,4 @@
-from diffusers import AutoPipelineForText2Image
+from diffusers import AutoPipelineForText2Image, PNDMScheduler
 import torch
 import gradio as gr
 from PIL import Image
@@ -8,21 +8,25 @@ from transformers import pipeline
 from diffusers.utils import load_image
 from accelerate import Accelerator
 
-accelerator = Accelerator()
+accelerator = Accelerator(cpu=True)
 apol=[]
 pipe = accelerator.prepare(AutoPipelineForText2Image.from_pretrained("openskyml/overall-v1", torch_dtype=torch.float32, variant=None, use_safetensors=False, safety_checker=None))
+pipe.scheduler = accelerator.prepare(PNDMScheduler.from_config(pipe.scheduler.config))
 pipe.unet.to(memory_format=torch.channels_last)
 pipe = accelerator.prepare(pipe.to("cpu"))
-def plex(prompt,neg_prompt):
-    nm = random.randint(1, 4836928)
-    while nm % 32 != 0:
-        nm = random.randint(1, 4836928)
+def plex(prompt,neg_prompt,nut):
+    if nut == 0:
+        nm = random.randint(1, 2147483616)
+        while nm % 32 != 0:
+            nm = random.randint(1, 2147483616)
+    else:
+        nm=nut
     generator = torch.Generator(device="cpu").manual_seed(nm)
     image = pipe(prompt=prompt, negative_prompt=neg_prompt, generator=generator, num_inference_steps=15)
     for a, imze in enumerate(image["images"]):
         apol.append(imze)
     return apol
 
-iface = gr.Interface(fn=plex,inputs=[gr.Textbox(label="Prompt"), gr.Textbox(label="negative_prompt", value="low quality, bad quality")],outputs=gr.Gallery(label="Generated Output Image", columns=1), title="Txt2Img_Overall_v1_SD",description="Running on cpu, very slow!")
+iface = gr.Interface(fn=plex,inputs=[gr.Textbox(label="Prompt"), gr.Textbox(label="negative_prompt", value="low quality, bad quality"),gr.Slider(label="manual seed (leave 0 for random)",minimum=0,step=32,maximum=2147483616,value=0)],outputs=gr.Gallery(label="Generated Output Image", columns=1),description="Running on cpu, very slow! by JoPmt.")
 iface.queue(max_size=1,api_open=False)
 iface.launch(max_threads=1)