Merge branch 'AUTOMATIC1111:master' into sub-quad_attn_opt

1 files changed, 6 insertions, 4 deletions

diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py
index b451d1cf..ca92b142 100644
--- a/modules/sd_hijack_clip.py
+++ b/modules/sd_hijack_clip.py
@@ -5,7 +5,6 @@ import torch
 from modules import prompt_parser, devices

 from modules.shared import opts

 

-

 def get_target_prompt_token_count(token_count):

     return math.ceil(max(token_count, 1) / 75) * 75

 

@@ -254,10 +253,13 @@ class FrozenCLIPEmbedderWithCustomWords(FrozenCLIPEmbedderWithCustomWordsBase):
     def __init__(self, wrapped, hijack):

         super().__init__(wrapped, hijack)

         self.tokenizer = wrapped.tokenizer

-        self.comma_token = [v for k, v in self.tokenizer.get_vocab().items() if k == ',</w>'][0]

+

+        vocab = self.tokenizer.get_vocab()

+

+        self.comma_token = vocab.get(',</w>', None)

 

         self.token_mults = {}

-        tokens_with_parens = [(k, v) for k, v in self.tokenizer.get_vocab().items() if '(' in k or ')' in k or '[' in k or ']' in k]

+        tokens_with_parens = [(k, v) for k, v in vocab.items() if '(' in k or ')' in k or '[' in k or ']' in k]

         for text, ident in tokens_with_parens:

             mult = 1.0

             for c in text:

@@ -296,6 +298,6 @@ class FrozenCLIPEmbedderWithCustomWords(FrozenCLIPEmbedderWithCustomWordsBase):
     def encode_embedding_init_text(self, init_text, nvpt):

         embedding_layer = self.wrapped.transformer.text_model.embeddings

         ids = self.wrapped.tokenizer(init_text, max_length=nvpt, return_tensors="pt", add_special_tokens=False)["input_ids"]

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

+        embedded = embedding_layer.token_embedding.wrapped(ids.to(embedding_layer.token_embedding.wrapped.weight.device)).squeeze(0)

 

         return embedded