Fix behavior when encountering a bad embedding (#2721)

When encountering a bad embedding, InvokeAI was asking about reconfiguring models. This is because the embedding load error was never handled - it now is.

ldm/modules/textual_inversion_manager.py

@@ -79,7 +79,10 @@ def load_textual_inversion(self, ckpt_path: Union[str,Path], defer_injecting_tok
 
         embedding_info = self._parse_embedding(str(ckpt_path))
 
-        if (
+        if embedding_info is None:
+            # We've already put out an error message about the bad embedding in _parse_embedding, so just return.
+            return
+        elif (
             self.text_encoder.get_input_embeddings().weight.data[0].shape[0]
             != embedding_info["embedding"].shape[0]
         ):
@@ -287,6 +290,7 @@ def _parse_embedding(self, embedding_file: str):
             return self._parse_embedding_bin(embedding_file)
         else:
             print(f">> Not a recognized embedding file: {embedding_file}")
+            return None
 
     def _parse_embedding_pt(self, embedding_file):
         embedding_ckpt = torch.load(embedding_file, map_location="cpu")