lllyasviel/stable-diffusion-webui-forge
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lllyasviel
2024-01-25 07:52:29 -08:00
parent 4b7f788f54
commit b641c5a68a
2 changed files with 11 additions and 2 deletions
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2
modules/sd_samplers_cfg_denoiser.py
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@@ -95,7 +95,7 @@ class CFGDenoiser(torch.nn.Module):
if state.interrupted or state.skipped: if state.interrupted or state.skipped:
raise sd_samplers_common.InterruptedException raise sd_samplers_common.InterruptedException
if sd_samplers_common.apply_refiner(self): if sd_samplers_common.apply_refiner(self, x):
cond = self.sampler.sampler_extra_args['cond'] cond = self.sampler.sampler_extra_args['cond']
uncond = self.sampler.sampler_extra_args['uncond'] uncond = self.sampler.sampler_extra_args['uncond']

11
modules/sd_samplers_common.py
View File

@@ -5,6 +5,7 @@ import torch
from PIL import Image from PIL import Image
from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared, sd_models from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared, sd_models
from modules.shared import opts, state from modules.shared import opts, state
from ldm_patched.modules import model_management
import k_diffusion.sampling import k_diffusion.sampling
@@ -151,7 +152,7 @@ def replace_torchsde_browinan():
replace_torchsde_browinan() replace_torchsde_browinan()
def apply_refiner(cfg_denoiser): def apply_refiner(cfg_denoiser, x):
completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps
refiner_switch_at = cfg_denoiser.p.refiner_switch_at refiner_switch_at = cfg_denoiser.p.refiner_switch_at
refiner_checkpoint_info = cfg_denoiser.p.refiner_checkpoint_info refiner_checkpoint_info = cfg_denoiser.p.refiner_checkpoint_info
@@ -180,6 +181,14 @@ def apply_refiner(cfg_denoiser):
with sd_models.SkipWritingToConfig(): with sd_models.SkipWritingToConfig():
sd_models.reload_model_weights(info=refiner_checkpoint_info) sd_models.reload_model_weights(info=refiner_checkpoint_info)
refiner = sd_models.model_data.get_sd_model()
inference_memory = 0
unet_patcher = refiner.unet_patcher
model_management.load_models_gpu(
[unet_patcher],
unet_patcher.memory_required([x.shape[0]] + list(x.shape[1:])) + inference_memory)
devices.torch_gc() devices.torch_gc()
cfg_denoiser.p.setup_conds() cfg_denoiser.p.setup_conds()
cfg_denoiser.update_inner_model() cfg_denoiser.update_inner_model()