Merge branch 'master' into support_any_resolution

1 files changed, 3 insertions, 4 deletions

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 5e4d8688..a273e663 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -64,7 +64,8 @@ class EmbeddingDatabase:
 

         self.word_embeddings[embedding.name] = embedding

 

-        ids = model.cond_stage_model.tokenizer([embedding.name], add_special_tokens=False)['input_ids'][0]

+        # TODO changing between clip and open clip changes tokenization, which will cause embeddings to stop working

+        ids = model.cond_stage_model.tokenize([embedding.name])[0]

 

         first_id = ids[0]

         if first_id not in self.ids_lookup:

@@ -155,13 +156,11 @@ class EmbeddingDatabase:
 

 def create_embedding(name, num_vectors_per_token, overwrite_old, init_text='*'):

     cond_model = shared.sd_model.cond_stage_model

-    embedding_layer = cond_model.wrapped.transformer.text_model.embeddings

 

     with devices.autocast():

         cond_model([""])  # will send cond model to GPU if lowvram/medvram is active

 

-    ids = cond_model.tokenizer(init_text, max_length=num_vectors_per_token, return_tensors="pt", add_special_tokens=False)["input_ids"]

-    embedded = embedding_layer.token_embedding.wrapped(ids.to(devices.device)).squeeze(0)

+    embedded = cond_model.encode_embedding_init_text(init_text, num_vectors_per_token)

     vec = torch.zeros((num_vectors_per_token, embedded.shape[1]), device=devices.device)

 

     for i in range(num_vectors_per_token):