[bug fix] fixes #6444 - checkpointing save issue in advanced dreambooth lora sdxl script (#6464)

* unwrap text encoder when saving hook only for full text encoder tuning

* unwrap text encoder when saving hook only for full text encoder tuning

* save embeddings in each checkpoint as well

* save embeddings in each checkpoint as well

* save embeddings in each checkpoint as well

* Update examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py

@@ -1316,10 +1316,12 @@ def main(args):
                 if isinstance(model, type(accelerator.unwrap_model(unet))):
                     unet_lora_layers_to_save = convert_state_dict_to_diffusers(get_peft_model_state_dict(model))
                 elif isinstance(model, type(accelerator.unwrap_model(text_encoder_one))):
+                    if args.train_text_encoder:
                         text_encoder_one_lora_layers_to_save = convert_state_dict_to_diffusers(
                             get_peft_model_state_dict(model)
                         )
                 elif isinstance(model, type(accelerator.unwrap_model(text_encoder_two))):
+                    if args.train_text_encoder:
                         text_encoder_two_lora_layers_to_save = convert_state_dict_to_diffusers(
                             get_peft_model_state_dict(model)
                         )
@@ -1335,6 +1337,8 @@ def main(args):
                 text_encoder_lora_layers=text_encoder_one_lora_layers_to_save,
                 text_encoder_2_lora_layers=text_encoder_two_lora_layers_to_save,
             )
+        if args.train_text_encoder_ti:
+            embedding_handler.save_embeddings(f"{output_dir}/{args.output_dir}_emb.safetensors")
 
     def load_model_hook(models, input_dir):
         unet_ = None