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-rw-r--r--modules/sd_models.py41
1 files changed, 17 insertions, 24 deletions
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 90007da3..883639d1 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -9,7 +9,7 @@ from omegaconf import OmegaConf
from ldm.util import instantiate_from_config
-from modules import shared, modelloader, devices, script_callbacks
+from modules import shared, modelloader, devices, script_callbacks, sd_vae
from modules.paths import models_path
from modules.sd_hijack_inpainting import do_inpainting_hijack, should_hijack_inpainting
@@ -159,14 +159,15 @@ def get_state_dict_from_checkpoint(pl_sd):
return pl_sd
-vae_ignore_keys = {"model_ema.decay", "model_ema.num_updates"}
-
-
-def load_model_weights(model, checkpoint_info):
+def load_model_weights(model, checkpoint_info, vae_file="auto"):
checkpoint_file = checkpoint_info.filename
sd_model_hash = checkpoint_info.hash
- if checkpoint_info not in checkpoints_loaded:
+ vae_file = sd_vae.resolve_vae(checkpoint_file, vae_file=vae_file)
+
+ checkpoint_key = checkpoint_info
+
+ if checkpoint_key not in checkpoints_loaded:
print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}")
pl_sd = torch.load(checkpoint_file, map_location=shared.weight_load_location)
@@ -187,32 +188,24 @@ def load_model_weights(model, checkpoint_info):
devices.dtype = torch.float32 if shared.cmd_opts.no_half else torch.float16
devices.dtype_vae = torch.float32 if shared.cmd_opts.no_half or shared.cmd_opts.no_half_vae else torch.float16
- vae_file = os.path.splitext(checkpoint_file)[0] + ".vae.pt"
-
- if not os.path.exists(vae_file) and shared.cmd_opts.vae_path is not None:
- vae_file = shared.cmd_opts.vae_path
-
- if os.path.exists(vae_file):
- print(f"Loading VAE weights from: {vae_file}")
- vae_ckpt = torch.load(vae_file, map_location=shared.weight_load_location)
- vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss" and k not in vae_ignore_keys}
- model.first_stage_model.load_state_dict(vae_dict)
-
- model.first_stage_model.to(devices.dtype_vae)
-
if shared.opts.sd_checkpoint_cache > 0:
- checkpoints_loaded[checkpoint_info] = model.state_dict().copy()
+ # if PR #4035 were to get merged, restore base VAE first before caching
+ checkpoints_loaded[checkpoint_key] = model.state_dict().copy()
while len(checkpoints_loaded) > shared.opts.sd_checkpoint_cache:
checkpoints_loaded.popitem(last=False) # LRU
+
else:
- print(f"Loading weights [{sd_model_hash}] from cache")
- checkpoints_loaded.move_to_end(checkpoint_info)
- model.load_state_dict(checkpoints_loaded[checkpoint_info])
+ vae_name = sd_vae.get_filename(vae_file)
+ print(f"Loading weights [{sd_model_hash}] with {vae_name} VAE from cache")
+ checkpoints_loaded.move_to_end(checkpoint_key)
+ model.load_state_dict(checkpoints_loaded[checkpoint_key])
model.sd_model_hash = sd_model_hash
model.sd_model_checkpoint = checkpoint_file
model.sd_checkpoint_info = checkpoint_info
+ sd_vae.load_vae(model, vae_file)
+
def load_model(checkpoint_info=None):
from modules import lowvram, sd_hijack
@@ -263,7 +256,7 @@ def load_model(checkpoint_info=None):
def reload_model_weights(sd_model=None, info=None):
from modules import lowvram, devices, sd_hijack
checkpoint_info = info or select_checkpoint()
-
+
if not sd_model:
sd_model = shared.sd_model