Checkpoint cache by combination key of checkpoint and vae

This commit is contained in:
Muhammad Rizqi Nur 2022-10-31 15:19:34 +07:00
parent b96d0c4e9e
commit 726769da35
2 changed files with 23 additions and 12 deletions

View File

@ -160,11 +160,15 @@ def get_state_dict_from_checkpoint(pl_sd):
vae_ignore_keys = {"model_ema.decay", "model_ema.num_updates"}
def load_model_weights(model, checkpoint_info, force=False):
def load_model_weights(model, checkpoint_info, vae_file="auto"):
checkpoint_file = checkpoint_info.filename
sd_model_hash = checkpoint_info.hash
if force or checkpoint_info not in checkpoints_loaded:
vae_file = sd_vae.resolve_vae(checkpoint_file, vae_file=vae_file)
checkpoint_key = (checkpoint_info, vae_file)
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)
@ -185,24 +189,25 @@ def load_model_weights(model, checkpoint_info, force=False):
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
sd_vae.load_vae(model, checkpoint_file)
sd_vae.load_vae(model, vae_file)
model.first_stage_model.to(devices.dtype_vae)
if shared.opts.sd_checkpoint_cache > 0:
checkpoints_loaded[checkpoint_info] = model.state_dict().copy()
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
def load_model(checkpoint_info=None, force=False):
def load_model(checkpoint_info=None):
from modules import lowvram, sd_hijack
checkpoint_info = checkpoint_info or select_checkpoint()
@ -223,7 +228,7 @@ def load_model(checkpoint_info=None, force=False):
do_inpainting_hijack()
sd_model = instantiate_from_config(sd_config.model)
load_model_weights(sd_model, checkpoint_info, force=force)
load_model_weights(sd_model, checkpoint_info)
if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
lowvram.setup_for_low_vram(sd_model, shared.cmd_opts.medvram)
@ -250,7 +255,7 @@ def reload_model_weights(sd_model, info=None, force=False):
if sd_model.sd_checkpoint_info.config != checkpoint_info.config or should_hijack_inpainting(checkpoint_info) != should_hijack_inpainting(sd_model.sd_checkpoint_info):
checkpoints_loaded.clear()
load_model(checkpoint_info, force=force)
load_model(checkpoint_info)
return shared.sd_model
if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
@ -260,7 +265,7 @@ def reload_model_weights(sd_model, info=None, force=False):
sd_hijack.model_hijack.undo_hijack(sd_model)
load_model_weights(sd_model, checkpoint_info, force=force)
load_model_weights(sd_model, checkpoint_info)
sd_hijack.model_hijack.hijack(sd_model)
script_callbacks.model_loaded_callback(sd_model)

View File

@ -43,7 +43,7 @@ def refresh_vae_list(vae_path=vae_path, model_path=model_path):
vae_dict.update(res)
return vae_list
def load_vae(model, checkpoint_file, vae_file="auto"):
def resolve_vae(checkpoint_file, vae_file="auto"):
global first_load, vae_dict, vae_list
# save_settings = False
@ -94,6 +94,12 @@ def load_vae(model, checkpoint_file, vae_file="auto"):
if vae_file and not os.path.exists(vae_file):
vae_file = None
return vae_file
def load_vae(model, vae_file):
global first_load, vae_dict, vae_list
# save_settings = False
if vae_file:
print(f"Loading VAE weights from: {vae_file}")
vae_ckpt = torch.load(vae_file, map_location=shared.weight_load_location)