Update inference_manager.py

inference_manager.py

@@ -514,7 +514,6 @@ class ModelManager:
             faceid_all_embeds.append(faceid_embed)
 
         average_embedding = torch.mean(torch.stack(faceid_all_embeds, dim=0), dim=0)
-        average_embedding = average_embedding.to("cuda")
         
         print("start inference...")
         style_selection = ""
@@ -523,9 +522,9 @@ class ModelManager:
         seed = seed or int(randomize_seed_fn(seed, randomize_seed))
         p = remove_child_related_content(p)
         prompt_str = cfg.get("prompt", "{prompt}").replace("{prompt}", p)
-        generator = torch.Generator(model.base_model_pipeline.device).manual_seed(seed)
+        #generator = torch.Generator(model.base_model_pipeline.device).manual_seed(seed)
         print(f"generate: p={p}, np={negative_prompt}, steps={steps}, guidance_scale={guidance_scale}, size={width},{height}, seed={seed}")
-        print(f"device: embedding={average_embedding.device}, generator={generator.device}, ip_model={ip_model.device}, pipe={model.base_model_pipeline.device}")
+        #print(f"device: embedding={average_embedding.device}, generator={generator.device}, ip_model={ip_model.device}, pipe={model.base_model_pipeline.device}")
         images = ip_model.generate(
             prompt=prompt_str,
             negative_prompt=negative_prompt,
@@ -535,7 +534,7 @@ class ModelManager:
             height=height,
             guidance_scale=face_strength,
             num_inference_steps=steps,
-            generator=generator,
+            #generator=generator,
             num_images_per_prompt=1,
             #output_type="pil",
             #callback_on_step_end=callback_dynamic_cfg,