Merge pull request #6667 from Shondoit/zero-vector-ti

Allow creation of zero vectors for TI

1 files changed, 6 insertions, 3 deletions

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index b915b091..853246a6 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -248,11 +248,14 @@ def create_embedding(name, num_vectors_per_token, overwrite_old, init_text='*'):
     with devices.autocast():

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

 

-    embedded = cond_model.encode_embedding_init_text(init_text, num_vectors_per_token)

+    #cond_model expects at least some text, so we provide '*' as backup.

+    embedded = cond_model.encode_embedding_init_text(init_text or '*', 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):

-        vec[i] = embedded[i * int(embedded.shape[0]) // num_vectors_per_token]

+    #Only copy if we provided an init_text, otherwise keep vectors as zeros

+    if init_text:

+        for i in range(num_vectors_per_token):

+            vec[i] = embedded[i * int(embedded.shape[0]) // num_vectors_per_token]

 

     # Remove illegal characters from name.

     name = "".join( x for x in name if (x.isalnum() or x in "._- "))