Update app.py

app.py

@@ -91,14 +91,14 @@ class ModelWrapper:
         
         DTYPE = prompt_embed.dtype
         print(DTYPE)
-        print(typeof(noise))
-        print(typeof(current_timesteps))
-        print(typeof(unet_added_conditions))
+        print(type(noise))
+        print(type(current_timesteps))
+        print(type(unet_added_conditions))
         
         for constant in all_timesteps:
             current_timesteps = torch.ones(len(prompt_embed), device="cuda", dtype=torch.long) * constant
             eval_images = self.model(noise, current_timesteps, prompt_embed, added_cond_kwargs=unet_added_conditions).sample
-            print(typeof(eval_images))
+            print(type(eval_images))
 
             eval_images = get_x0_from_noise(noise, eval_images, alphas_cumprod, current_timesteps).to(self.DTYPE)