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https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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8617396c6d
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5e2627a1a6
@ -107,6 +107,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
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self.tokenizer = wrapped.tokenizer
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self.token_mults = {}
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self.comma_token = [v for k, v in self.tokenizer.get_vocab().items() if k == ',</w>'][0]
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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]
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for text, ident in tokens_with_parens:
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mult = 1.0
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@ -136,6 +138,7 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
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fixes = []
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remade_tokens = []
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multipliers = []
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last_comma = -1
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for tokens, (text, weight) in zip(tokenized, parsed):
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i = 0
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@ -144,6 +147,20 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
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embedding, embedding_length_in_tokens = self.hijack.embedding_db.find_embedding_at_position(tokens, i)
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if token == self.comma_token:
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last_comma = len(remade_tokens)
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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:
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last_comma += 1
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reloc_tokens = remade_tokens[last_comma:]
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reloc_mults = multipliers[last_comma:]
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remade_tokens = remade_tokens[:last_comma]
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length = len(remade_tokens)
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rem = int(math.ceil(length / 75)) * 75 - length
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remade_tokens += [id_end] * rem + reloc_tokens
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multipliers = multipliers[:last_comma] + [1.0] * rem + reloc_mults
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if embedding is None:
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remade_tokens.append(token)
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multipliers.append(weight)
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@ -227,6 +227,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
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"enable_emphasis": OptionInfo(True, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"),
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"use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
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"enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
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"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 }),
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"filter_nsfw": OptionInfo(False, "Filter NSFW content"),
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'CLIP_stop_at_last_layers': OptionInfo(1, "Stop At last layers of CLIP model", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
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"random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
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