diff options
Diffstat (limited to 'modules/sd_hijack.py')
| -rw-r--r-- | modules/sd_hijack.py | 13 |
1 files changed, 7 insertions, 6 deletions
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index d68f89cc..340329c0 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -18,7 +18,6 @@ attention_CrossAttention_forward = ldm.modules.attention.CrossAttention.forward diffusionmodules_model_nonlinearity = ldm.modules.diffusionmodules.model.nonlinearity
diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.AttnBlock.forward
-
def apply_optimizations():
undo_optimizations()
@@ -83,7 +82,7 @@ class StableDiffusionModelHijack: layer.padding_mode = 'circular' if enable else 'zeros'
def tokenize(self, text):
- max_length = self.clip.max_length - 2
+ max_length = opts.max_prompt_tokens - 2
_, remade_batch_tokens, _, _, _, token_count = self.clip.process_text([text])
return remade_batch_tokens[0], token_count, max_length
@@ -94,7 +93,6 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): self.wrapped = wrapped
self.hijack: StableDiffusionModelHijack = hijack
self.tokenizer = wrapped.tokenizer
- self.max_length = wrapped.max_length
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]
@@ -116,7 +114,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): def tokenize_line(self, line, used_custom_terms, hijack_comments):
id_start = self.wrapped.tokenizer.bos_token_id
id_end = self.wrapped.tokenizer.eos_token_id
- maxlen = self.wrapped.max_length
+ maxlen = opts.max_prompt_tokens
if opts.enable_emphasis:
parsed = prompt_parser.parse_prompt_attention(line)
@@ -191,7 +189,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): def process_text_old(self, text):
id_start = self.wrapped.tokenizer.bos_token_id
id_end = self.wrapped.tokenizer.eos_token_id
- maxlen = self.wrapped.max_length
+ maxlen = self.wrapped.max_length # you get to stay at 77
used_custom_terms = []
remade_batch_tokens = []
overflowing_words = []
@@ -268,8 +266,11 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module): if len(used_custom_terms) > 0:
self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms]))
+ position_ids_array = [min(x, 75) for x in range(len(remade_batch_tokens[0])-1)] + [76]
+ position_ids = torch.asarray(position_ids_array, device=devices.device).expand((1, -1))
+
tokens = torch.asarray(remade_batch_tokens).to(device)
- outputs = self.wrapped.transformer(input_ids=tokens)
+ outputs = self.wrapped.transformer(input_ids=tokens, position_ids=position_ids)
z = outputs.last_hidden_state
# restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
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