Update app.py

app.py

@@ -11,10 +11,10 @@ from accelerate import 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.scheduler = 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,nut):
+pipe.to("cpu")
+def plex(prompt,neg_prompt,stips,nut):
     if nut == 0:
         nm = random.randint(1, 2147483616)
         while nm % 32 != 0:
@@ -22,11 +22,11 @@ def plex(prompt,neg_prompt,nut):
     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)
+    image = pipe(prompt=[prompt]*2, negative_prompt=[neg_prompt]*2, generator=generator, num_inference_steps=stips)
     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"),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 = gr.Interface(fn=plex,inputs=[gr.Textbox(label="Prompt"), gr.Textbox(label="negative_prompt", value="low quality, bad quality"),gr.Slider(label="num steps",minimum=1,step=1,maximum=30,value=20),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)