diff options
Diffstat (limited to 'modules/sd_models.py')
| -rw-r--r-- | modules/sd_models.py | 31 |
1 files changed, 22 insertions, 9 deletions
diff --git a/modules/sd_models.py b/modules/sd_models.py index c59151e0..283cf1cd 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -5,6 +5,7 @@ import gc from collections import namedtuple
import torch
import re
+import safetensors.torch
from omegaconf import OmegaConf
from ldm.util import instantiate_from_config
@@ -45,7 +46,7 @@ def checkpoint_tiles(): def list_models():
checkpoints_list.clear()
- model_list = modelloader.load_models(model_path=model_path, command_path=shared.cmd_opts.ckpt_dir, ext_filter=[".ckpt"])
+ model_list = modelloader.load_models(model_path=model_path, command_path=shared.cmd_opts.ckpt_dir, ext_filter=[".ckpt", ".safetensors"])
def modeltitle(path, shorthash):
abspath = os.path.abspath(path)
@@ -143,8 +144,8 @@ def transform_checkpoint_dict_key(k): def get_state_dict_from_checkpoint(pl_sd):
- if "state_dict" in pl_sd:
- pl_sd = pl_sd["state_dict"]
+ pl_sd = pl_sd.pop("state_dict", pl_sd)
+ pl_sd.pop("state_dict", None)
sd = {}
for k, v in pl_sd.items():
@@ -159,6 +160,20 @@ def get_state_dict_from_checkpoint(pl_sd): return pl_sd
+def read_state_dict(checkpoint_file, print_global_state=False, map_location=None):
+ _, extension = os.path.splitext(checkpoint_file)
+ if extension.lower() == ".safetensors":
+ pl_sd = safetensors.torch.load_file(checkpoint_file, device=map_location or shared.weight_load_location)
+ else:
+ pl_sd = torch.load(checkpoint_file, map_location=map_location or shared.weight_load_location)
+
+ if print_global_state and "global_step" in pl_sd:
+ print(f"Global Step: {pl_sd['global_step']}")
+
+ sd = get_state_dict_from_checkpoint(pl_sd)
+ return sd
+
+
def load_model_weights(model, checkpoint_info, vae_file="auto"):
checkpoint_file = checkpoint_info.filename
sd_model_hash = checkpoint_info.hash
@@ -173,12 +188,7 @@ def load_model_weights(model, checkpoint_info, vae_file="auto"): # load from file
print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}")
- pl_sd = torch.load(checkpoint_file, map_location=shared.weight_load_location)
- if "global_step" in pl_sd:
- print(f"Global Step: {pl_sd['global_step']}")
-
- sd = get_state_dict_from_checkpoint(pl_sd)
- del pl_sd
+ sd = read_state_dict(checkpoint_file)
model.load_state_dict(sd, strict=False)
del sd
@@ -244,6 +254,9 @@ def load_model(checkpoint_info=None): do_inpainting_hijack()
+ if shared.cmd_opts.no_half:
+ sd_config.model.params.unet_config.params.use_fp16 = False
+
sd_model = instantiate_from_config(sd_config.model)
load_model_weights(sd_model, checkpoint_info)
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