Update app.py

app.py

@@ -2,7 +2,6 @@ from diffusers import DiffusionPipeline
 import torch
 import PIL.Image
 import gradio as gr
-import random
 import numpy as np
 
 pipeline = DiffusionPipeline.from_pretrained("1aurent/ddpm-mnist")
@@ -12,12 +11,11 @@ def predict(steps, seed):
     for i in range(1,steps):
         yield pipeline(generator=generator, num_inference_steps=i).images[0]
 
-random_seed = random.randint(0, 2147483647)
 gr.Interface(
     predict,
     inputs=[
-        gr.inputs.Slider(1, 100, label='Inference Steps', default=5, step=1),
-        gr.inputs.Slider(0, 2147483647, label='Seed', default=random_seed, step=1),
+        gr.inputs.Slider(1, 100, label='Inference Steps', default=12, step=1),
+        gr.inputs.Slider(0, 2147483647, label='Seed', default=69420, step=1),
     ],
     outputs=gr.Image(shape=[28,28], type="pil", elem_id="output_image"),
     css="#output_image{width: 256px}",