测试加入进度

app.py

@@ -12,6 +12,8 @@ MAX_SEED = np.iinfo(np.int32).max
 
 pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16).to("cuda")
 
+progress=gr.Progress()
+
 @spaces.GPU
 def infer(input_image, prompt, seed=42, randomize_seed=False, guidance_scale=2.5, steps=28, progress=gr.Progress(track_tqdm=True)):
     """
@@ -53,6 +55,12 @@ def infer(input_image, prompt, seed=42, randomize_seed=False, guidance_scale=2.5
         ...     guidance_scale=2.5
         ... )
     """
+
+    def callback_fn(step: int, timestep: int, latents: torch.FloatTensor):
+        print(f"[Step {step}] Timestep: {timestep}")
+        # progress_value = (step+1.0)/num_inference_steps
+        # progress(progress_value, desc=f"Image generating, {step + 1}/{num_inference_steps} steps")
+
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
     
@@ -72,6 +80,7 @@ def infer(input_image, prompt, seed=42, randomize_seed=False, guidance_scale=2.5
             prompt=prompt,
             guidance_scale=guidance_scale,
             num_inference_steps=steps,
+            callback=callback_fn,
             generator=torch.Generator().manual_seed(seed),
         ).images[0]
     return image, seed, gr.Button(visible=True)