Update app.py

app.py

@@ -1,6 +1,22 @@
-from diffusers import DiffusionPipeline
+from diffusers import DDPMScheduler, UNet2DModel
+from PIL import Image
+import torch
 
-pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.1-T2V-14B")
+scheduler = DDPMScheduler.from_pretrained("google/ddpm-cat-256")
+model = UNet2DModel.from_pretrained("google/ddpm-cat-256").to("cuda")
+scheduler.set_timesteps(50)
 
-prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
-image = pipe(prompt).images[0]
+sample_size = model.config.sample_size
+noise = torch.randn((1, 3, sample_size, sample_size), device="cuda")
+input = noise
+
+for t in scheduler.timesteps:
+    with torch.no_grad():
+        noisy_residual = model(input, t).sample
+        prev_noisy_sample = scheduler.step(noisy_residual, t, input).prev_sample
+        input = prev_noisy_sample
+
+image = (input / 2 + 0.5).clamp(0, 1)
+image = image.cpu().permute(0, 2, 3, 1).numpy()[0]
+image = Image.fromarray((image * 255).round().astype("uint8"))
+image