Update app_quant_latent.py

app_quant_latent.py

@@ -593,7 +593,7 @@ def generate_image(prompt, height, width, steps, seed, guidance_scale=0.0):
         try:
             latents = safe_get_latents(pipe, height, width, generator, device, LOGS)
 
-            # --- FIX: Convert latent tensor to PIL image ---
+            # --- Latent preview only ---
             try:
                 with torch.no_grad():
                     latent_img_tensor = pipe.vae.decode(latents).sample  # [1, 3, H, W]
@@ -605,10 +605,10 @@ def generate_image(prompt, height, width, steps, seed, guidance_scale=0.0):
 
             latent_gallery.append(latent_img)
 
-            # Yield initial latent preview
+            # Yield latent preview immediately
             yield None, latent_gallery, LOGS
 
-            # --- Final image from latent ---
+            # --- Final image decoding ---
             try:
                 with torch.no_grad():
                     final_img_tensor = pipe.vae.decode(latents).sample
@@ -621,7 +621,7 @@ def generate_image(prompt, height, width, steps, seed, guidance_scale=0.0):
             final_gallery.append(final_img)
             LOGS.append("✅ Advanced latent pipeline succeeded.")
 
-            # Save latents to dict and upload to HF
+            # Save latents to dict and upload to Hugging Face
             latent_dict = {"latents": latents.cpu(), "prompt": prompt, "seed": seed}
             try:
                 hf_url = upload_latents_to_hf(latent_dict, filename=f"latents_{seed}.pt")