add BREAK keyword to end current text chunk and start the next
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205991df78
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@ -274,6 +274,7 @@ re_attention = re.compile(r"""
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""", re.X)
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""", re.X)
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re_break = re.compile(r"\s*\bBREAK\b\s*", re.S)
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def parse_prompt_attention(text):
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def parse_prompt_attention(text):
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"""
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"""
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@ -339,7 +340,11 @@ def parse_prompt_attention(text):
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elif text == ']' and len(square_brackets) > 0:
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elif text == ']' and len(square_brackets) > 0:
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multiply_range(square_brackets.pop(), square_bracket_multiplier)
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multiply_range(square_brackets.pop(), square_bracket_multiplier)
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else:
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else:
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res.append([text, 1.0])
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parts = re.split(re_break, text)
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for i, part in enumerate(parts):
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if i > 0:
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res.append(["BREAK", -1])
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res.append([part, 1.0])
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for pos in round_brackets:
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for pos in round_brackets:
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multiply_range(pos, round_bracket_multiplier)
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multiply_range(pos, round_bracket_multiplier)
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@ -96,13 +96,18 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
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token_count = 0
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token_count = 0
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last_comma = -1
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last_comma = -1
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def next_chunk():
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def next_chunk(is_last=False):
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"""puts current chunk into the list of results and produces the next one - empty"""
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"""puts current chunk into the list of results and produces the next one - empty;
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if is_last is true, tokens <end-of-text> tokens at the end won't add to token_count"""
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nonlocal token_count
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nonlocal token_count
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nonlocal last_comma
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nonlocal last_comma
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nonlocal chunk
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nonlocal chunk
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token_count += len(chunk.tokens)
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if is_last:
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token_count += len(chunk.tokens)
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else:
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token_count += self.chunk_length
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to_add = self.chunk_length - len(chunk.tokens)
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to_add = self.chunk_length - len(chunk.tokens)
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if to_add > 0:
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if to_add > 0:
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chunk.tokens += [self.id_end] * to_add
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chunk.tokens += [self.id_end] * to_add
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@ -116,6 +121,10 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
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chunk = PromptChunk()
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chunk = PromptChunk()
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for tokens, (text, weight) in zip(tokenized, parsed):
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for tokens, (text, weight) in zip(tokenized, parsed):
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if text == 'BREAK' and weight == -1:
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next_chunk()
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continue
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position = 0
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position = 0
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while position < len(tokens):
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while position < len(tokens):
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token = tokens[position]
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token = tokens[position]
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@ -159,7 +168,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
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position += embedding_length_in_tokens
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position += embedding_length_in_tokens
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if len(chunk.tokens) > 0 or len(chunks) == 0:
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if len(chunk.tokens) > 0 or len(chunks) == 0:
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next_chunk()
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next_chunk(is_last=True)
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return chunks, token_count
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return chunks, token_count
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