remove extraneous warnings about overwriting trigger terms

Author: lstein

ldm/generate.py

@@ -976,17 +976,18 @@ def set_model(self, model_name):
         self.generators = {}
 
         seed_everything(random.randrange(0, np.iinfo(np.uint32).max))
-        if self.embedding_path is not None:
+        if self.embedding_path and not model_data.get("ti_embeddings_loaded"):
             print(f'>> Loading embeddings from {self.embedding_path}')
             for root, _, files in os.walk(self.embedding_path):
                 for name in files:
                     ti_path = os.path.join(root, name)
                     self.model.textual_inversion_manager.load_textual_inversion(
                         ti_path, defer_injecting_tokens=True
                     )
-            print(
-                f'>> Textual inversion triggers: {", ".join(sorted(self.model.textual_inversion_manager.get_all_trigger_strings()))}'
-            )
+            model_data["ti_embeddings_loaded"] = True
+        print(
+            f'>> Textual inversion triggers: {", ".join(sorted(self.model.textual_inversion_manager.get_all_trigger_strings()))}'
+        )
 
         self.model_name = model_name
         self._set_sampler()  # requires self.model_name to be set first

ldm/invoke/model_manager.py

@@ -103,11 +103,7 @@ def get_model(self, model_name: str):
             requested_model = self.models[model_name]["model"]
             print(f">> Retrieving model {model_name} from system RAM cache")
             self.models[model_name]["model"] = self._model_from_cpu(requested_model)
-            width = self.models[model_name]["width"]
-            height = self.models[model_name]["height"]
-            hash = self.models[model_name]["hash"]
-
-        else:  # we're about to load a new model, so potentially offload the least recently used one
+        else:
             requested_model, width, height, hash = self._load_model(model_name)
             self.models[model_name] = {
                 "model": requested_model,
@@ -118,13 +114,8 @@ def get_model(self, model_name: str):
 
         self.current_model = model_name
         self._push_newest_model(model_name)
-        return {
-            "model": requested_model,
-            "width": width,
-            "height": height,
-            "hash": hash,
-        }
-
+        return self.models[model_name]
+    
     def default_model(self) -> str | None:
         """
         Returns the name of the default model, or None