hitmare-patch-1 #2

Merged
Hitmare merged 7 commits from hitmare-patch-1 into main 2023-12-23 15:10:34 +00:00
1 changed files with 94 additions and 92 deletions
Showing only changes of commit e0000cab58 - Show all commits

View File

@ -1,92 +1,94 @@
import torch.nn
import ldm.modules.diffusionmodules.openaimodel
from modules import script_callbacks, shared, devices
unet_options = []
current_unet_option = None
current_unet = None
def list_unets():
new_unets = script_callbacks.list_unets_callback()
unet_options.clear()
unet_options.extend(new_unets)
def get_unet_option(option=None):
option = option or shared.opts.sd_unet
if option == "None":
return None
if option == "Automatic":
name = shared.sd_model.sd_checkpoint_info.model_name
options = [x for x in unet_options if x.model_name == name]
option = options[0].label if options else "None"
return next(iter([x for x in unet_options if x.label == option]), None)
def apply_unet(option=None):
global current_unet_option
global current_unet
new_option = get_unet_option(option)
if new_option == current_unet_option:
return
if current_unet is not None:
print(f"Dectivating unet: {current_unet.option.label}")
current_unet.deactivate()
current_unet_option = new_option
if current_unet_option is None:
current_unet = None
if not shared.sd_model.lowvram:
shared.sd_model.model.diffusion_model.to(devices.device)
return
shared.sd_model.model.diffusion_model.to(devices.cpu)
devices.torch_gc()
current_unet = current_unet_option.create_unet()
current_unet.option = current_unet_option
print(f"Activating unet: {current_unet.option.label}")
current_unet.activate()
class SdUnetOption:
model_name = None
"""name of related checkpoint - this option will be selected automatically for unet if the name of checkpoint matches this"""
label = None
"""name of the unet in UI"""
def create_unet(self):
"""returns SdUnet object to be used as a Unet instead of built-in unet when making pictures"""
raise NotImplementedError()
class SdUnet(torch.nn.Module):
def forward(self, x, timesteps, context, *args, **kwargs):
raise NotImplementedError()
def activate(self):
pass
def deactivate(self):
pass
def UNetModel_forward(self, x, timesteps=None, context=None, *args, **kwargs):
if current_unet is not None:
return current_unet.forward(x, timesteps, context, *args, **kwargs)
return ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui(self, x, timesteps, context, *args, **kwargs)
import torch.nn
from modules import script_callbacks, shared, devices
unet_options = []
current_unet_option = None
current_unet = None
original_forward = None # not used, only left temporarily for compatibility
def list_unets():
new_unets = script_callbacks.list_unets_callback()
unet_options.clear()
unet_options.extend(new_unets)
def get_unet_option(option=None):
option = option or shared.opts.sd_unet
if option == "None":
return None
if option == "Automatic":
name = shared.sd_model.sd_checkpoint_info.model_name
options = [x for x in unet_options if x.model_name == name]
option = options[0].label if options else "None"
return next(iter([x for x in unet_options if x.label == option]), None)
def apply_unet(option=None):
global current_unet_option
global current_unet
new_option = get_unet_option(option)
if new_option == current_unet_option:
return
if current_unet is not None:
print(f"Dectivating unet: {current_unet.option.label}")
current_unet.deactivate()
current_unet_option = new_option
if current_unet_option is None:
current_unet = None
if not shared.sd_model.lowvram:
shared.sd_model.model.diffusion_model.to(devices.device)
return
shared.sd_model.model.diffusion_model.to(devices.cpu)
devices.torch_gc()
current_unet = current_unet_option.create_unet()
current_unet.option = current_unet_option
print(f"Activating unet: {current_unet.option.label}")
current_unet.activate()
class SdUnetOption:
model_name = None
"""name of related checkpoint - this option will be selected automatically for unet if the name of checkpoint matches this"""
label = None
"""name of the unet in UI"""
def create_unet(self):
"""returns SdUnet object to be used as a Unet instead of built-in unet when making pictures"""
raise NotImplementedError()
class SdUnet(torch.nn.Module):
def forward(self, x, timesteps, context, *args, **kwargs):
raise NotImplementedError()
def activate(self):
pass
def deactivate(self):
pass
def create_unet_forward(original_forward):
def UNetModel_forward(self, x, timesteps=None, context=None, *args, **kwargs):
if current_unet is not None:
return current_unet.forward(x, timesteps, context, *args, **kwargs)
return original_forward(self, x, timesteps, context, *args, **kwargs)
return UNetModel_forward