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Disty0
2024-10-17 00:25:03 +03:00
parent 1427a4f06b
commit 899c896f23
2 changed files with 8 additions and 13 deletions
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modules/model_stablecascade.py
+3 -6
View File
@@ -132,11 +132,6 @@ def load_cascade_combined(checkpoint_info, diffusers_load_config):
else:
sd_model = StableCascadeCombinedPipeline.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
shared.log.debug(f'StableCascade combined: {sd_model.__class__.__name__}')
return sd_model
def cascade_post_load(sd_model):
sd_model.prior_pipe.scheduler.config.clip_sample = False
sd_model.default_scheduler = copy.deepcopy(sd_model.prior_pipe.scheduler)
sd_model.prior_pipe.get_timestep_ratio_conditioning = get_timestep_ratio_conditioning
@@ -162,10 +157,12 @@ def cascade_post_load(sd_model):
text_encoder=None,
latent_dim_scale=sd_model.decoder_pipe.config.latent_dim_scale,
)
shared.log.debug(f'StableCascade combined: {sd_model.__class__.__name__}')
return sd_model
# Custom sampler support. Remove after the changes gets upstreamed: https://github.com/huggingface/diffusers/pull/9132
# Balanced offload hooks:
class StableCascadeDecoderPipelineFixed(diffusers.StableCascadeDecoderPipeline):
def guidance_scale(self):
return self._guidance_scale
modules/sd_models.py
+5 -7
View File
@@ -611,7 +611,7 @@ def detect_pipeline(f: str, op: str = 'model', warning=True, quiet=False):
guess = 'PixArt-Alpha'
if 'stable-diffusion-3' in f.lower():
guess = 'Stable Diffusion 3'
if 'stable-cascade' in f.lower() or 'stablecascade' in f.lower() or 'wuerstchen3' in f.lower() or 'sotediffusion' in f.lower():
if 'stable-cascade' in f.lower() or 'stablecascade' in f.lower() or 'wuerstchen3' in f.lower() or ('sotediffusion' in f.lower() and "v2" in f.lower()):
if devices.dtype == torch.float16:
warn('Stable Cascade does not support Float16')
guess = 'Stable Cascade'
@@ -853,7 +853,7 @@ def apply_balanced_offload(sd_model):
def apply_balanced_offload_to_module(pipe):
for module_name in pipe._internal_dict.keys(): # pylint: disable=protected-access
module = getattr(pipe, module_name)
module = getattr(pipe, module_name, None)
if isinstance(module, torch.nn.Module):
checkpoint_name = pipe.sd_checkpoint_info.name if getattr(pipe, "sd_checkpoint_info", None) is not None else None
if checkpoint_name is None:
@@ -1058,9 +1058,8 @@ def load_diffuser_force(model_type, checkpoint_info, diffusers_load_config, op='
sd_model = None
try:
if model_type in ['Stable Cascade']: # forced pipeline
from modules.model_stablecascade import load_cascade_combined, cascade_post_load
from modules.model_stablecascade import load_cascade_combined
sd_model = load_cascade_combined(checkpoint_info, diffusers_load_config)
cascade_post_load(sd_model)
elif model_type in ['InstaFlow']: # forced pipeline
pipeline = diffusers.utils.get_class_from_dynamic_module('instaflow_one_step', module_file='pipeline.py')
sd_model = pipeline.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
@@ -1856,9 +1855,8 @@ def disable_offload(sd_model):
if not getattr(sd_model, 'has_accelerate', False):
return
for _name, model in sd_model.components.items():
if not isinstance(model, torch.nn.Module):
continue
remove_hook_from_module(model, recurse=True)
if isinstance(model, torch.nn.Module):
remove_hook_from_module(model, recurse=True)
sd_model.has_accelerate = False