lllyasviel/stable-diffusion-webui-forge
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Apply emphasis mode changes immediately (#2423)

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Previously emphasis mode changes applied only on model load.
Also added handling for mode 'None' (literal interpretation), which previously gave results identical to mode 'Ignore'.
This commit is contained in:
DenOfEquity
2024-12-08 19:25:39 +00:00
committed by GitHub
parent 2e867aaf3a
commit 2051c4100b
3 changed files with 51 additions and 39 deletions
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8
backend/text_processing/classic_engine.py
View File

@@ -6,6 +6,8 @@ from backend.text_processing import parsing, emphasis
from backend.text_processing.textual_inversion import EmbeddingDatabase
from backend import memory_management
from modules.shared import opts
PromptChunkFix = namedtuple('PromptChunkFix', ['offset', 'embedding'])
last_extra_generation_params = {}
@@ -67,7 +69,7 @@ class ClassicTextProcessingEngine:
self.text_encoder = text_encoder
self.tokenizer = tokenizer
self.emphasis = emphasis.get_current_option(emphasis_name)()
self.emphasis = emphasis.get_current_option(opts.emphasis)()
self.text_projection = text_projection
self.minimal_clip_skip = minimal_clip_skip
self.clip_skip = clip_skip
@@ -146,7 +148,7 @@ class ClassicTextProcessingEngine:
return z
def tokenize_line(self, line):
parsed = parsing.parse_prompt_attention(line)
parsed = parsing.parse_prompt_attention(line, self.emphasis.name)
tokenized = self.tokenize([text for text, _ in parsed])
@@ -248,6 +250,8 @@ class ClassicTextProcessingEngine:
return batch_chunks, token_count
def __call__(self, texts):
self.emphasis = emphasis.get_current_option(opts.emphasis)()
batch_chunks, token_count = self.process_texts(texts)
used_embeddings = {}

74
backend/text_processing/parsing.py
View File

@@ -20,7 +20,7 @@ re_attention = re.compile(r"""
re_break = re.compile(r"\s*\bBREAK\b\s*", re.S)
def parse_prompt_attention(text):
def parse_prompt_attention(text, emphasis):
res = []
round_brackets = []
square_brackets = []
@@ -32,44 +32,48 @@ def parse_prompt_attention(text):
for p in range(start_position, len(res)):
res[p][1] *= multiplier
for m in re_attention.finditer(text):
text = m.group(0)
weight = m.group(1)
if emphasis == "None":
# interpret literally
res = [[text, 1.0]]
else:
for m in re_attention.finditer(text):
text = m.group(0)
weight = m.group(1)
if text.startswith('\\'):
res.append([text[1:], 1.0])
elif text == '(':
round_brackets.append(len(res))
elif text == '[':
square_brackets.append(len(res))
elif weight is not None and round_brackets:
multiply_range(round_brackets.pop(), float(weight))
elif text == ')' and round_brackets:
multiply_range(round_brackets.pop(), round_bracket_multiplier)
elif text == ']' and square_brackets:
multiply_range(square_brackets.pop(), square_bracket_multiplier)
else:
parts = re.split(re_break, text)
for i, part in enumerate(parts):
if i > 0:
res.append(["BREAK", -1])
res.append([part, 1.0])
if text.startswith('\\'):
res.append([text[1:], 1.0])
elif text == '(':
round_brackets.append(len(res))
elif text == '[':
square_brackets.append(len(res))
elif weight is not None and round_brackets:
multiply_range(round_brackets.pop(), float(weight))
elif text == ')' and round_brackets:
multiply_range(round_brackets.pop(), round_bracket_multiplier)
elif text == ']' and square_brackets:
multiply_range(square_brackets.pop(), square_bracket_multiplier)
else:
parts = re.split(re_break, text)
for i, part in enumerate(parts):
if i > 0:
res.append(["BREAK", -1])
res.append([part, 1.0])
for pos in round_brackets:
multiply_range(pos, round_bracket_multiplier)
for pos in round_brackets:
multiply_range(pos, round_bracket_multiplier)
for pos in square_brackets:
multiply_range(pos, square_bracket_multiplier)
for pos in square_brackets:
multiply_range(pos, square_bracket_multiplier)
if len(res) == 0:
res = [["", 1.0]]
if len(res) == 0:
res = [["", 1.0]]
i = 0
while i + 1 < len(res):
if res[i][1] == res[i + 1][1]:
res[i][0] += res[i + 1][0]
res.pop(i + 1)
else:
i += 1
i = 0
while i + 1 < len(res):
if res[i][1] == res[i + 1][1]:
res[i][0] += res[i + 1][0]
res.pop(i + 1)
else:
i += 1
return res

8
backend/text_processing/t5_engine.py
View File

@@ -4,6 +4,8 @@ from collections import namedtuple
from backend.text_processing import parsing, emphasis
from backend import memory_management
from modules.shared import opts
PromptChunkFix = namedtuple('PromptChunkFix', ['offset', 'embedding'])
@@ -21,7 +23,7 @@ class T5TextProcessingEngine:
self.text_encoder = text_encoder.transformer
self.tokenizer = tokenizer
self.emphasis = emphasis.get_current_option(emphasis_name)()
self.emphasis = emphasis.get_current_option(opts.emphasis)()
self.min_length = min_length
self.id_end = 1
self.id_pad = 0
@@ -64,7 +66,7 @@ class T5TextProcessingEngine:
return z
def tokenize_line(self, line):
parsed = parsing.parse_prompt_attention(line)
parsed = parsing.parse_prompt_attention(line, self.emphasis.name)
tokenized = self.tokenize([text for text, _ in parsed])
@@ -111,6 +113,8 @@ class T5TextProcessingEngine:
zs = []
cache = {}
self.emphasis = emphasis.get_current_option(opts.emphasis)()
for line in texts:
if line in cache:
line_z_values = cache[line]