Update app_quant_latent.py

app_quant_latent.py

@@ -245,88 +245,6 @@ log_system_stats("AFTER PIPELINE BUILD")
 
 
 
-@spaces.GPU
-def generate_image(prompt, height, width, steps, seed, guidance_scale=0.0, return_latents=False):
-    """
-    Returns 3 outputs for Gradio:
-    - image: PIL.Image
-    - gallery: optional latents or empty list
-    - logs: list of messages
-    """
-
-    LOGS = []
-    image = None
-    latents = None
-    gallery = []
-
-    try:
-        generator = torch.Generator(device).manual_seed(int(seed))
-
-        # -------------------------------
-        # Attempt advanced latent generation
-        # -------------------------------
-        try:
-            batch_size = 1
-            num_channels_latents = getattr(pipe.unet, "in_channels", None)
-            if num_channels_latents is None:
-                raise AttributeError("pipe.unet.in_channels not found, fallback to standard pipeline")
-
-            latents = pipe.prepare_latents(
-                batch_size=batch_size,
-                num_channels=num_channels_latents,
-                height=height,
-                width=width,
-                dtype=torch.float32,
-                device=device,
-                generator=generator
-            )
-            LOGS.append(f"✅ Latents prepared: {latents.shape}")
-
-            output = pipe(
-                prompt=prompt,
-                height=height,
-                width=width,
-                num_inference_steps=steps,
-                guidance_scale=guidance_scale,
-                generator=generator,
-                latents=latents
-            )
-            image = output.images[0]
-            gallery = [image]  # You can also return other latent previews if needed
-            LOGS.append("✅ Advanced latent generation succeeded.")
-
-        # -------------------------------
-        # Fallback to standard pipeline
-        # -------------------------------
-        except Exception as e_latent:
-            LOGS.append(f"⚠️ Advanced latent generation failed: {e_latent}")
-            LOGS.append("🔁 Falling back to standard pipeline...")
-            try:
-                output = pipe(
-                    prompt=prompt,
-                    height=height,
-                    width=width,
-                    num_inference_steps=steps,
-                    guidance_scale=guidance_scale,
-                    generator=generator
-                )
-                image = output.images[0]
-                gallery = [image]  # still return at least the final image
-                LOGS.append("✅ Standard pipeline generation succeeded.")
-            except Exception as e_standard:
-                LOGS.append(f"❌ Standard pipeline generation failed: {e_standard}")
-                # Fallback: return None image and empty gallery
-                image = None
-                gallery = []
-
-        # -------------------------------
-        # Return all 3 outputs
-        # -------------------------------
-        return image, gallery, LOGS
-
-    except Exception as e:
-        LOGS.append(f"❌ Inference failed entirely: {e}")
-        return None, [], LOGS
 
 @spaces.GPU
 def generate_image(prompt, height, width, steps, seed, guidance_scale=0.0, return_latents=False):