Update app.py

app.py

@@ -165,7 +165,7 @@ def inference(net, prompt, negative_prompt, guidance_scale, ddim_steps, seed):
             ).bfloat16()
            
         
-    text_input = self.tokenizer(prompt, padding="max_length", max_length=tokenizer.model_max_length, truncation=True, return_tensors="pt")
+    text_input = tokenizer(prompt, padding="max_length", max_length=tokenizer.model_max_length, truncation=True, return_tensors="pt")
         
     text_embeddings = text_encoder(text_input.input_ids.to(device))[0]
         
@@ -176,7 +176,7 @@ def inference(net, prompt, negative_prompt, guidance_scale, ddim_steps, seed):
     uncond_embeddings = text_encoder(uncond_input.input_ids.to(device))[0]
     text_embeddings = torch.cat([uncond_embeddings, text_embeddings]).bfloat16()
     noise_scheduler.set_timesteps(ddim_steps) 
-    latents = latents * self.noise_scheduler.init_noise_sigma
+    latents = latents * noise_scheduler.init_noise_sigma
             
     for i,t in enumerate(tqdm.tqdm(noise_scheduler.timesteps)):
         latent_model_input = torch.cat([latents] * 2)