Update injection_main.py

injection_main.py

@@ -238,14 +238,13 @@ def sample_disentangled(
     latents = start_latents.clone()
 
     latents = latents.repeat(len(prompt), 1, 1, 1)
-    # randomly initalize the 1st lantent for generation
+    # randomly initialize the 1st latent for generation
 
     latents[1] = generative_latent
     # assume that the first latent is used for reconstruction
-    for i in tqdm(range(start_step, num_inference_steps), desc="Stylizing"):
-
+    for i in range(start_step, num_inference_steps):
         if use_content_anchor:
-            latents[0] = intermediate_latents[(-i + 1)]
+            latents[0] = intermediate_latents[-(i + 1)]
         t = pipe.scheduler.timesteps[i]
 
         # Expand the latents if we are doing classifier free guidance
@@ -287,6 +286,7 @@ def sample_disentangled(
     return images
 
 
+
 ## Inversion
 @torch.no_grad()
 def invert(