lllyasviel/stable-diffusion-webui-forge
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Gradio 4 + WebUI 1.10

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layerdiffusion
2024-07-26 08:51:34 -07:00
parent e95333c556
commit e26abf87ec
201 changed files with 7562 additions and 4834 deletions
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16
modules/sd_models_config.py
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@@ -23,6 +23,8 @@ config_inpainting = os.path.join(sd_configs_path, "v1-inpainting-inference.yaml"
config_instruct_pix2pix = os.path.join(sd_configs_path, "instruct-pix2pix.yaml")
config_alt_diffusion = os.path.join(sd_configs_path, "alt-diffusion-inference.yaml")
config_alt_diffusion_m18 = os.path.join(sd_configs_path, "alt-diffusion-m18-inference.yaml")
config_sd3 = os.path.join(sd_configs_path, "sd3-inference.yaml")
def is_using_v_parameterization_for_sd2(state_dict):
"""
@@ -31,11 +33,11 @@ def is_using_v_parameterization_for_sd2(state_dict):
import ldm.modules.diffusionmodules.openaimodel
device = devices.cpu
device = devices.device
with sd_disable_initialization.DisableInitialization():
unet = ldm.modules.diffusionmodules.openaimodel.UNetModel(
use_checkpoint=True,
use_checkpoint=False,
use_fp16=False,
image_size=32,
in_channels=4,
@@ -56,12 +58,13 @@ def is_using_v_parameterization_for_sd2(state_dict):
with torch.no_grad():
unet_sd = {k.replace("model.diffusion_model.", ""): v for k, v in state_dict.items() if "model.diffusion_model." in k}
unet.load_state_dict(unet_sd, strict=True)
unet.to(device=device, dtype=torch.float)
unet.to(device=device, dtype=devices.dtype_unet)
test_cond = torch.ones((1, 2, 1024), device=device) * 0.5
x_test = torch.ones((1, 4, 8, 8), device=device) * 0.5
out = (unet(x_test, torch.asarray([999], device=device), context=test_cond) - x_test).mean().item()
with devices.autocast():
out = (unet(x_test, torch.asarray([999], device=device), context=test_cond) - x_test).mean().cpu().item()
return out < -1
@@ -71,11 +74,15 @@ def guess_model_config_from_state_dict(sd, filename):
diffusion_model_input = sd.get('model.diffusion_model.input_blocks.0.0.weight', None)
sd2_variations_weight = sd.get('embedder.model.ln_final.weight', None)
if "model.diffusion_model.x_embedder.proj.weight" in sd:
return config_sd3
if sd.get('conditioner.embedders.1.model.ln_final.weight', None) is not None:
if diffusion_model_input.shape[1] == 9:
return config_sdxl_inpainting
else:
return config_sdxl
if sd.get('conditioner.embedders.0.model.ln_final.weight', None) is not None:
return config_sdxl_refiner
elif sd.get('depth_model.model.pretrained.act_postprocess3.0.project.0.bias', None) is not None:
@@ -99,7 +106,6 @@ def guess_model_config_from_state_dict(sd, filename):
if diffusion_model_input.shape[1] == 8:
return config_instruct_pix2pix
if sd.get('cond_stage_model.roberta.embeddings.word_embeddings.weight', None) is not None:
if sd.get('cond_stage_model.transformation.weight').size()[0] == 1024:
return config_alt_diffusion_m18