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pulid with hidiffusion

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Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2025-02-14 09:32:22 -05:00
parent bb8368e52e
commit 877c488fa8
5 changed files with 21 additions and 14 deletions
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CHANGELOG.md
+2 -1
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@@ -88,7 +88,8 @@ We're back with another update with over 50 commits!
- validate output before hires/refine
- scheduler fix sigma index out of bounds
- force pydantic version reinstall/reload
- multi-unit when using controlnet-union
- multi-unit when using controlnet-union
- pulid with hidiffusion
## Update for 2025-02-05
modules/hidiffusion/__init__.py
+5 -3
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@@ -32,12 +32,14 @@ def apply(p, model_type):
hidiffusion.switching_threshold_ratio_dict['sdxl_4096']['T2_ratio'] = t2
hidiffusion.switching_threshold_ratio_dict['sdxl_turbo_1024']['T2_ratio'] = t2
p.extra_generation_params['HiDiffusion Ratios'] = f'{shared.opts.hidiffusion_t1}/{shared.opts.hidiffusion_t2}'
hidiffusion.apply_hidiffusion(shared.sd_model, apply_raunet=shared.opts.hidiffusion_raunet, apply_window_attn=shared.opts.hidiffusion_attn, model_type=model_type)
pipe = shared.sd_model.pipe if hasattr(shared.sd_model, 'pipe') else shared.sd_model
hidiffusion.apply_hidiffusion(pipe, apply_raunet=shared.opts.hidiffusion_raunet, apply_window_attn=shared.opts.hidiffusion_attn, model_type=model_type, steps=p.steps)
p.extra_generation_params['HiDiffusion'] = f'{shared.opts.hidiffusion_raunet}/{shared.opts.hidiffusion_attn}/{shared.opts.hidiffusion_steps > 0}:{shared.opts.hidiffusion_steps}'
t1 = time.time()
shared.log.debug(f'HiDiffusion apply: raunet={shared.opts.hidiffusion_raunet} attn={shared.opts.hidiffusion_attn} aggressive={shared.opts.hidiffusion_steps > 0}:{shared.opts.hidiffusion_steps} t1={shared.opts.hidiffusion_t1} t2={shared.opts.hidiffusion_t2} time={t1-t0:.2f} type={shared.sd_model_type} width={p.width} height={p.height}')
def unapply():
if hasattr(shared.sd_model, "unet"):
hidiffusion.remove_hidiffusion(shared.sd_model)
pipe = shared.sd_model.pipe if hasattr(shared.sd_model, 'pipe') else shared.sd_model
if hasattr(pipe, 'unet'):
hidiffusion.remove_hidiffusion(pipe)
modules/hidiffusion/hidiffusion.py
+13 -6
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@@ -6,6 +6,7 @@ from diffusers.utils.torch_utils import is_torch_version
from diffusers.pipelines import auto_pipeline
current_steps = 50
def sd15_hidiffusion_key():
modified_key = dict()
modified_key['down_module_key'] = ['down_blocks.0.downsamplers.0.conv']
@@ -163,12 +164,14 @@ def make_diffusers_transformer_block(block_class: Type[torch.nn.Module]) -> Type
widow_size = (math.ceil(H/2), math.ceil(W/2))
if rand_num <= 0.25:
shift_size = (0,0)
if rand_num > 0.25 and rand_num <= 0.5:
elif rand_num > 0.25 and rand_num <= 0.5:
shift_size = (widow_size[0]//4, widow_size[1]//4)
if rand_num > 0.5 and rand_num <= 0.75:
elif rand_num > 0.5 and rand_num <= 0.75:
shift_size = (widow_size[0]//4*2, widow_size[1]//4*2)
if rand_num > 0.75 and rand_num <= 1:
elif rand_num > 0.75 and rand_num <= 1:
shift_size = (widow_size[0]//4*3, widow_size[1]//4*3)
else:
shift_size = (0,0)
norm_hidden_states = window_partition(norm_hidden_states, widow_size, shift_size, H, W)
# 1. Retrieve lora scale.
@@ -261,7 +264,7 @@ def make_diffusers_cross_attn_down_block(block_class: Type[torch.nn.Module]) ->
T1_start = 0
T1_end = 0
T1 = 0 # to avoid confict with sdxl-turbo
max_timestep = 50
max_timestep = current_steps
def forward(
self,
@@ -273,6 +276,8 @@ def make_diffusers_cross_attn_down_block(block_class: Type[torch.nn.Module]) ->
encoder_attention_mask: Optional[torch.FloatTensor] = None,
additional_residuals: Optional[torch.FloatTensor] = None,
) -> Tuple[torch.FloatTensor, Tuple[torch.FloatTensor, ...]]:
if not hasattr(self.info['pipeline'], '_num_timesteps'):
self.info['pipeline']._num_timesteps = self.max_timestep # pylint: disable=protected-access
self.max_timestep = self.info['pipeline']._num_timesteps # pylint: disable=protected-access
# self.max_timestep = len(self.info['scheduler'].timesteps)
ori_H, ori_W = self.info['size']
@@ -618,13 +623,15 @@ def apply_hidiffusion(
model: torch.nn.Module,
apply_raunet: bool = True,
apply_window_attn: bool = True,
model_type: str = 'None'):
model_type: str = 'None',
steps: int = 50):
"""
model: diffusers model. We support SD 1.5, 2.1, XL, XL Turbo.
apply_raunet: whether to apply RAU-Net
apply_window_attn: whether to apply MSW-MSA.
"""
global current_steps # pylint: disable=global-statement
current_steps = steps
if hasattr(model, 'controlnet'):
from .hidiffusion_controlnet import make_diffusers_sdxl_contrtolnet_ppl, make_diffusers_unet_2d_condition
make_ppl_fn = make_diffusers_sdxl_contrtolnet_ppl
modules/pulid/pulid_sdxl.py
+1 -1
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@@ -372,7 +372,7 @@ class StableDiffusionXLPuLIDPipeline:
# sigmas
sigmas = self.get_sigmas_karras(num_inference_steps).to(self.device)
if image is not None and strength > 0:
_, num_inference_steps = self.pipe.get_timesteps(num_inference_steps, strength, self.device, None) # denoising_start disabled
_timesteps, num_inference_steps = self.pipe.get_timesteps(num_inference_steps, strength, self.device, None) # denoising_start disabled
sigmas = sigmas[-(num_inference_steps + 1):].to(self.device) # shorten sigmas in i2i
debug(f'PulID sigmas: sigmas={sigmas.shape} dtype={sigmas.dtype}')
modules/ui_extensions.py
-3
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@@ -171,9 +171,6 @@ def install_extension_from_url(dirname, url, branch_name, search_text, sort_colu
if ssh:
args['env'] = {'GIT_SSH_COMMAND':ssh}
shared.log.debug(f'GIT: {args}')
# from installer import run
# ssh_test = run('ssh', '-v -c chacha20-poly1305@openssh.com -T git@github.com')
# shared.log.debug('GIT SSH TEST', ssh_test)
with git.Repo.clone_from(**args) as repo:
repo.remote().fetch(verbose=True)
for submodule in repo.submodules: