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Comma backtrack padding (#2192)

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Comma backtrack padding
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hentailord85ez 2022-10-11 07:55:28 +01:00 committed by GitHub
parent 8617396c6d
commit 5e2627a1a6
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2 changed files with 19 additions and 1 deletions
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19
modules/sd_hijack.py
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@ -107,6 +107,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
self.tokenizer = wrapped.tokenizer
self.token_mults = {}
self.comma_token = [v for k, v in self.tokenizer.get_vocab().items() if k == ',</w>'][0]
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]
for text, ident in tokens_with_parens:
mult = 1.0
@ -136,6 +138,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
fixes = []
remade_tokens = []
multipliers = []
last_comma = -1
for tokens, (text, weight) in zip(tokenized, parsed):
i = 0
@ -144,6 +147,20 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
if token == self.comma_token:
last_comma = len(remade_tokens)
elif opts.comma_padding_backtrack != 0 and max(len(remade_tokens), 1) % 75 == 0 and last_comma != -1 and len(remade_tokens) - last_comma <= opts.comma_padding_backtrack:
last_comma += 1
reloc_tokens = remade_tokens[last_comma:]
reloc_mults = multipliers[last_comma:]
remade_tokens = remade_tokens[:last_comma]
length = len(remade_tokens)
rem = int(math.ceil(length / 75)) * 75 - length
remade_tokens += [id_end] * rem + reloc_tokens
multipliers = multipliers[:last_comma] + [1.0] * rem + reloc_mults
if embedding is None:
remade_tokens.append(token)
multipliers.append(weight)
@ -284,7 +301,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
while max(map(len, remade_batch_tokens)) != 0:
rem_tokens = [x[75:] for x in remade_batch_tokens]
rem_multipliers = [x[75:] for x in batch_multipliers]
self.hijack.fixes = []
for unfiltered in hijack_fixes:
fixes = []

1
modules/shared.py
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@ -227,6 +227,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
"enable_emphasis": OptionInfo(True, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"),
"use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
"enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
"comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }),
"filter_nsfw": OptionInfo(False, "Filter NSFW content"),
'CLIP_stop_at_last_layers': OptionInfo(1, "Stop At last layers of CLIP model", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
"random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),