From ce6911158b5b2f9cf79b405a1f368f875492044d Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 26 Nov 2022 16:10:46 +0300
Subject: Add support Stable Diffusion 2.0

---
 modules/textual_inversion/textual_inversion.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

(limited to 'modules/textual_inversion')

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):
-- 
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