tqdm progress on the render step

app.py

@@ -119,8 +119,7 @@ def _duration(embeds_path, images, width, height, seed):
     return int(30 + 4 * megapixels + 0.15 * megapixels**2)
 
 
-@spaces.GPU(duration=_duration, size="xlarge")
-def _generate(embeds_path, images, width, height, seed):
+def _run(embeds_path, images, width, height, seed):
     embeds = load_file(embeds_path)
     kwargs = dict(
         prompt_embeds=embeds["prompt_embeds"].to("cuda", torch.bfloat16),
@@ -139,6 +138,11 @@ def _generate(embeds_path, images, width, height, seed):
     return path
 
 
+@spaces.GPU(duration=_duration, size="xlarge")
+def _generate(embeds_path, images, width, height, seed):
+    return _run(embeds_path, images, width, height, seed)
+
+
 def generate(prompt, images=None, aspect=AUTO, resolution="4 MP", seed=0, randomize=True, enhance=False,
              reasoning_effort="low", progress=gr.Progress(track_tqdm=True)):
     """Text-to-image, or an edit of up to 8 images referred to as `<Picture 1>`, `<Picture 2>`, ... in the prompt.
@@ -194,10 +198,15 @@ def studio(state, seed, randomize, effort):
     yield f"Generating {width}×{height} ...", final, thinking, seed, plan
 
 
-def render(plan):
-    """Part 2: the image, as its own event so the result panel shows the normal loading UI."""
+def _render_duration(plan, progress=None):
+    return _duration(plan["embeds"], plan["images"], plan["width"], plan["height"], plan["seed"])
+
+
+@spaces.GPU(duration=_render_duration, size="xlarge")
+def render(plan, progress=gr.Progress(track_tqdm=True)):
+    """Part 2: the image, as its own event so the result panel shows the loading UI and the denoising steps."""
     t0 = time.time()
-    path = _generate(plan["embeds"], plan["images"], plan["width"], plan["height"], plan["seed"])
+    path = _run(plan["embeds"], plan["images"], plan["width"], plan["height"], plan["seed"])
     return path, f"{plan['width']}×{plan['height']} · seed {plan['seed']} · {time.time() - t0:.0f}s"
 
 IDEAS = [