Update app.py

app.py

@@ -101,12 +101,12 @@ class ModelWrapper:
             #current_timesteps = current_timesteps.to(torch.float16)
             print(f'current_timestpes: {current_timesteps.dtype}')
             eval_images = self.model(noise, current_timesteps, prompt_embed, added_cond_kwargs=unet_added_conditions).sample
-
+            print(eval_images.dtype)
             eval_images = get_x0_from_noise(noise, eval_images, alphas_cumprod, current_timesteps).to(self.DTYPE)
-
+            print(eval_images.dtype)
             next_timestep = current_timesteps - step_interval 
             noise = self.scheduler.add_noise(eval_images, torch.randn_like(eval_images), next_timestep).to(torch.float16) 
-
+            print(noise.dtype)
         if fast_vae_decode:
             eval_images = self.tiny_vae.decode(eval_images.to(self.tiny_vae_dtype) / self.tiny_vae.config.scaling_factor, return_dict=False)[0]
         else: