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Merge pull request #6528 from PlasmaPower/vae-safetensors

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Add support for loading VAEs from safetensors files
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AUTOMATIC1111 2023-01-09 19:40:28 +03:00 committed by GitHub
commit 99da2c5af6
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1 changed files with 18 additions and 3 deletions
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21
modules/sd_vae.py
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@ -1,4 +1,5 @@
import torch
import safetensors.torch
import os
import collections
from collections import namedtuple
@ -72,8 +73,10 @@ def refresh_vae_list(vae_path=vae_path, model_path=model_path):
candidates = [
*glob.iglob(os.path.join(model_path, '**/*.vae.ckpt'), recursive=True),
*glob.iglob(os.path.join(model_path, '**/*.vae.pt'), recursive=True),
*glob.iglob(os.path.join(model_path, '**/*.vae.safetensors'), recursive=True),
*glob.iglob(os.path.join(vae_path, '**/*.ckpt'), recursive=True),
*glob.iglob(os.path.join(vae_path, '**/*.pt'), recursive=True)
*glob.iglob(os.path.join(vae_path, '**/*.pt'), recursive=True),
*glob.iglob(os.path.join(vae_path, '**/*.safetensors'), recursive=True),
]
if shared.cmd_opts.vae_path is not None and os.path.isfile(shared.cmd_opts.vae_path):
candidates.append(shared.cmd_opts.vae_path)
@ -137,6 +140,12 @@ def resolve_vae(checkpoint_file=None, vae_file="auto"):
if os.path.isfile(vae_file_try):
vae_file = vae_file_try
print(f"Using VAE found similar to selected model: {vae_file}")
# if still not found, try look for ".vae.safetensors" beside model
if vae_file == "auto":
vae_file_try = model_path + ".vae.safetensors"
if os.path.isfile(vae_file_try):
vae_file = vae_file_try
print(f"Using VAE found similar to selected model: {vae_file}")
# No more fallbacks for auto
if vae_file == "auto":
vae_file = None
@ -163,8 +172,14 @@ def load_vae(model, vae_file=None):
assert os.path.isfile(vae_file), f"VAE file doesn't exist: {vae_file}"
print(f"Loading VAE weights from: {vae_file}")
store_base_vae(model)
vae_ckpt = torch.load(vae_file, map_location=shared.weight_load_location)
vae_dict_1 = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss" and k not in vae_ignore_keys}
_, extension = os.path.splitext(vae_file)
if extension.lower() == ".safetensors":
vae_ckpt = safetensors.torch.load_file(vae_file, device=shared.weight_load_location)
else:
vae_ckpt = torch.load(vae_file, map_location=shared.weight_load_location)
if "state_dict" in vae_ckpt:
vae_ckpt = vae_ckpt["state_dict"]
vae_dict_1 = {k: v for k, v in vae_ckpt.items() if k[0:4] != "loss" and k not in vae_ignore_keys}
_load_vae_dict(model, vae_dict_1)
if cache_enabled: