fix: 修复缺少的call参数

app.py

@@ -408,7 +408,9 @@ class Demo:
             num_inference_steps=self.num_inference_steps,
             generator=generator,
             networks=networks,  # 加载多个 LoRA 模型
+            start_noise=int(start_noise),
             scales=scale_list,   # 设置每个 LoRA 的权重
+            unet=unet,
             guidance_scale=self.guidance_scale
         ).images[0]
 
@@ -419,8 +421,10 @@ class Demo:
             num_images_per_prompt=1,
             num_inference_steps=self.num_inference_steps,
             generator=generator,
-            networks=[],  # 不加载任何 LoRA 模型
-            scales=[],    # 不设置任何权重
+            networks=networks,
+            start_noise=int(start_noise),
+            scales=[0] * len(networks), # 不设置任何权重
+            unet=unet,
             guidance_scale=self.guidance_scale
         ).images[0]
         

utils.py

@@ -333,7 +333,7 @@ def call(
                 if networks is not None and scales is not None:
                     for _network, _scale in zip(networks, scales):
                         with _network:
-                            _network.set_lora_slider(scale=0 if t > start_noise else _scale)
+                            _network.set_lora_slider(scale=0 if t > start_noise else float(_scale))
                             
                 # expand the latents if we are doing classifier free guidance
                 latent_model_input = torch.cat([latents] * 2) if do_classifier_free_guidance else latents