|
import json |
|
import os |
|
|
|
import ldm_patched.modules.sd |
|
|
|
def first_file(path, filenames): |
|
for f in filenames: |
|
p = os.path.join(path, f) |
|
if os.path.exists(p): |
|
return p |
|
return None |
|
|
|
def load_diffusers(model_path, output_vae=True, output_clip=True, embedding_directory=None): |
|
diffusion_model_names = ["diffusion_pytorch_model.fp16.safetensors", "diffusion_pytorch_model.safetensors", "diffusion_pytorch_model.fp16.bin", "diffusion_pytorch_model.bin"] |
|
unet_path = first_file(os.path.join(model_path, "unet"), diffusion_model_names) |
|
vae_path = first_file(os.path.join(model_path, "vae"), diffusion_model_names) |
|
|
|
text_encoder_model_names = ["model.fp16.safetensors", "model.safetensors", "pytorch_model.fp16.bin", "pytorch_model.bin"] |
|
text_encoder1_path = first_file(os.path.join(model_path, "text_encoder"), text_encoder_model_names) |
|
text_encoder2_path = first_file(os.path.join(model_path, "text_encoder_2"), text_encoder_model_names) |
|
|
|
text_encoder_paths = [text_encoder1_path] |
|
if text_encoder2_path is not None: |
|
text_encoder_paths.append(text_encoder2_path) |
|
|
|
unet = ldm_patched.modules.sd.load_unet(unet_path) |
|
|
|
clip = None |
|
if output_clip: |
|
clip = ldm_patched.modules.sd.load_clip(text_encoder_paths, embedding_directory=embedding_directory) |
|
|
|
vae = None |
|
if output_vae: |
|
sd = ldm_patched.modules.utils.load_torch_file(vae_path) |
|
vae = ldm_patched.modules.sd.VAE(sd=sd) |
|
|
|
return (unet, clip, vae) |
|
|