Save checkpoints also for the adapter since I do not have it after training

diffusers_repo/examples/research_projects/ip_adapter/tutorial_train_ip-adapter.py

@@ -321,6 +321,7 @@ def main():
     adapter_modules = torch.nn.ModuleList(unet.attn_processors.values())
 
     ip_adapter = IPAdapter(unet, image_proj_model, adapter_modules, args.pretrained_ip_adapter_path)
+    accelerator.register_for_checkpointing(ip_adapter)
 
     weight_dtype = torch.float32
     if accelerator.mixed_precision == "fp16":