[textual_inversion] unwrap_model text encoder before accessing weights (#1816)

* unwrap_model text encoder before accessing weights

* fix another call

* fix the right call

examples/textual_inversion/textual_inversion.py

@@ -592,7 +592,7 @@ def main():
     progress_bar.set_description("Steps")
 
     # keep original embeddings as reference
-    orig_embeds_params = text_encoder.get_input_embeddings().weight.data.clone()
+    orig_embeds_params = accelerator.unwrap_model(text_encoder).get_input_embeddings().weight.data.clone()
 
     for epoch in range(first_epoch, args.num_train_epochs):
         text_encoder.train()
@@ -644,7 +644,9 @@ def main():
                 # Let's make sure we don't update any embedding weights besides the newly added token
                 index_no_updates = torch.arange(len(tokenizer)) != placeholder_token_id
                 with torch.no_grad():
-                    text_encoder.get_input_embeddings().weight[index_no_updates] = orig_embeds_params[index_no_updates]
+                    accelerator.unwrap_model(text_encoder).get_input_embeddings().weight[
+                        index_no_updates
+                    ] = orig_embeds_params[index_no_updates]
 
             # Checks if the accelerator has performed an optimization step behind the scenes
             if accelerator.sync_gradients: