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refactor taesd and add multiple variants in settings

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Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2025-01-12 14:09:55 -05:00
parent e81db4cdfe
commit 49f5c8ab12
13 changed files with 755 additions and 221 deletions
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modules/sd_samplers_diffusers.py
+20 -13
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@@ -7,8 +7,8 @@ from modules import shared, errors
from modules.sd_samplers_common import SamplerData, flow_models
debug = shared.log.trace if os.environ.get('SD_SAMPLER_DEBUG', None) is not None else lambda *args, **kwargs: None
debug('Trace: SAMPLER')
debug = os.environ.get('SD_SAMPLER_DEBUG', None) is not None
debug_log = shared.log.trace if debug else lambda *args, **kwargs: None
try:
from diffusers import (
@@ -178,17 +178,17 @@ class DiffusionSampler:
model.default_scheduler = copy.deepcopy(model.scheduler)
for key, value in config.get('All', {}).items(): # apply global defaults
self.config[key] = value
debug(f'Sampler: all="{self.config}"')
debug_log(f'Sampler: all="{self.config}"')
if hasattr(model.default_scheduler, 'scheduler_config'): # find model defaults
orig_config = model.default_scheduler.scheduler_config
else:
orig_config = model.default_scheduler.config
debug(f'Sampler: diffusers="{self.config}"')
debug(f'Sampler: original="{orig_config}"')
debug_log(f'Sampler: diffusers="{self.config}"')
debug_log(f'Sampler: original="{orig_config}"')
for key, value in orig_config.items(): # apply model defaults
if key in self.config:
self.config[key] = value
debug(f'Sampler: default="{self.config}"')
debug_log(f'Sampler: default="{self.config}"')
for key, value in config.get(name, {}).items(): # apply diffusers per-scheduler defaults
self.config[key] = value
for key, value in kwargs.items(): # apply user args, if any
@@ -267,15 +267,22 @@ class DiffusionSampler:
if key not in possible:
# shared.log.warning(f'Sampler: sampler="{name}" config={self.config} invalid={key}')
del self.config[key]
debug(f'Sampler: name="{name}"')
debug(f'Sampler: config={self.config}')
debug(f'Sampler: signature={possible}')
# shared.log.debug(f'Sampler: sampler="{name}" config={self.config}')
sampler = constructor(**self.config)
debug_log(f'Sampler: name="{name}"')
debug_log(f'Sampler: config={self.config}')
debug_log(f'Sampler: signature={possible}')
# shared.log.debug_log(f'Sampler: sampler="{name}" config={self.config}')
try:
sampler = constructor(**self.config)
except Exception as e:
shared.log.error(f'Sampler: sampler="{name}" {e}')
if debug:
errors.display(e, 'Samplers')
self.sampler = None
return
accept_sigmas = "sigmas" in set(inspect.signature(sampler.set_timesteps).parameters.keys())
accepts_timesteps = "timesteps" in set(inspect.signature(sampler.set_timesteps).parameters.keys())
accept_scale_noise = hasattr(sampler, "scale_noise")
debug(f'Sampler: sampler="{name}" sigmas={accept_sigmas} timesteps={accepts_timesteps}')
debug_log(f'Sampler: sampler="{name}" sigmas={accept_sigmas} timesteps={accepts_timesteps}')
if ('Flux' in model.__class__.__name__) and (not accept_sigmas):
shared.log.warning(f'Sampler: sampler="{name}" does not accept sigmas')
self.sampler = None
@@ -289,5 +296,5 @@ class DiffusionSampler:
if not hasattr(self.sampler, 'dc_ratios'):
pass
# self.sampler.dc_ratios = self.sampler.cascade_polynomial_regression(test_CFG=6.0, test_NFE=10, cpr_path='tmp/sd2.1.npy')
# shared.log.debug(f'Sampler: class="{self.sampler.__class__.__name__}" config={self.sampler.config}')
# shared.log.debug_log(f'Sampler: class="{self.sampler.__class__.__name__}" config={self.sampler.config}')
self.sampler.name = name