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-rw-r--r--modules/textual_inversion/textual_inversion.py13
1 files changed, 5 insertions, 8 deletions
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index c0baaace..0c50161d 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -117,24 +117,21 @@ class EmbeddingDatabase:
possible_matches = self.ids_lookup.get(token, None)
if possible_matches is None:
- return None
+ return None, None
for ids, embedding in possible_matches:
if tokens[offset:offset + len(ids)] == ids:
- return embedding
+ return embedding, len(ids)
- return None
+ return None, None
-
-def create_embedding(name, num_vectors_per_token):
- init_text = '*'
-
+def create_embedding(name, num_vectors_per_token, init_text='*'):
cond_model = shared.sd_model.cond_stage_model
embedding_layer = cond_model.wrapped.transformer.text_model.embeddings
ids = cond_model.tokenizer(init_text, max_length=num_vectors_per_token, return_tensors="pt", add_special_tokens=False)["input_ids"]
- embedded = embedding_layer(ids.to(devices.device)).squeeze(0)
+ embedded = embedding_layer.token_embedding.wrapped(ids.to(devices.device)).squeeze(0)
vec = torch.zeros((num_vectors_per_token, embedded.shape[1]), device=devices.device)
for i in range(num_vectors_per_token):