support for sd-concepts as alternatives for textual inversion #151

.gitignore

@@ -9,4 +9,5 @@ __pycache__
 /outputs
 /config.json
 /log
-webui.settings.bat
+/webui.settings.bat
+/embeddings

modules/sd_hijack.py

@@ -73,11 +73,21 @@ class StableDiffusionModelHijack:
             name = os.path.splitext(filename)[0]
 
             data = torch.load(path)
+
+            # textual inversion embeddings
+            if 'string_to_param' in data:
                 param_dict = data['string_to_param']
                 if hasattr(param_dict, '_parameters'):
                     param_dict = getattr(param_dict, '_parameters')  # fix for torch 1.12.1 loading saved file from torch 1.11
                 assert len(param_dict) == 1, 'embedding file has multiple terms in it'
                 emb = next(iter(param_dict.items()))[1]
+            elif type(data) == dict and type(next(iter(data.values()))) == torch.Tensor:
+                assert len(data.keys()) == 1, 'embedding file has multiple terms in it'
+
+                emb = next(iter(data.values()))
+                if len(emb.shape) == 1:
+                    emb = emb.unsqueeze(0)
+
             self.word_embeddings[name] = emb.detach()
             self.word_embeddings_checksums[name] = f'{const_hash(emb.reshape(-1))&0xffff:04x}'