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OpenVINO fix Lora

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Disty0
2024-12-31 04:15:37 +03:00
parent 92fd7b6c8e
commit 9adf777e38
1 changed files with 10 additions and 6 deletions
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modules/lora/networks.py
+10 -6
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@@ -146,6 +146,7 @@ def load_safetensors(name, network_on_disk) -> Union[network.Network, None]:
def maybe_recompile_model(names, te_multipliers):
recompile_model = False
skip_lora_load = False
if shared.compiled_model_state is not None and shared.compiled_model_state.is_compiled:
if len(names) == len(shared.compiled_model_state.lora_model):
for i, name in enumerate(names):
@@ -155,19 +156,23 @@ def maybe_recompile_model(names, te_multipliers):
shared.compiled_model_state.lora_model = []
break
if not recompile_model:
skip_lora_load = True
if len(loaded_networks) > 0 and debug:
shared.log.debug('Model Compile: Skipping LoRa loading')
return recompile_model
return recompile_model, skip_lora_load
else:
recompile_model = True
shared.compiled_model_state.lora_model = []
if recompile_model:
backup_cuda_compile = shared.opts.cuda_compile
backup_scheduler = getattr(shared.sd_model, "scheduler", None)
sd_models.unload_model_weights(op='model')
shared.opts.cuda_compile = []
sd_models.reload_model_weights(op='model')
shared.opts.cuda_compile = backup_cuda_compile
return recompile_model
if backup_scheduler is not None:
shared.sd_model.scheduler = backup_scheduler
return recompile_model, skip_lora_load
def list_available_networks():
@@ -230,7 +235,7 @@ def network_load(names, te_multipliers=None, unet_multipliers=None, dyn_dims=Non
if names[i].startswith('/'):
networks_on_disk[i] = network_download(names[i])
failed_to_load_networks = []
recompile_model = maybe_recompile_model(names, te_multipliers)
recompile_model, skip_lora_load = maybe_recompile_model(names, te_multipliers)
loaded_networks.clear()
diffuser_loaded.clear()
@@ -272,7 +277,7 @@ def network_load(names, te_multipliers=None, unet_multipliers=None, dyn_dims=Non
name = next(iter(lora_cache))
lora_cache.pop(name, None)
if len(diffuser_loaded) > 0:
if not skip_lora_load and len(diffuser_loaded) > 0:
shared.log.debug(f'Load network: type=LoRA loaded={diffuser_loaded} available={shared.sd_model.get_list_adapters()} active={shared.sd_model.get_active_adapters()} scales={diffuser_scales}')
try:
t0 = time.time()
@@ -294,7 +299,6 @@ def network_load(names, te_multipliers=None, unet_multipliers=None, dyn_dims=Non
backup_lora_model = shared.compiled_model_state.lora_model
if 'Model' in shared.opts.cuda_compile:
shared.sd_model = sd_models_compile.compile_diffusers(shared.sd_model)
shared.compiled_model_state.lora_model = backup_lora_model
if len(loaded_networks) > 0:
@@ -498,7 +502,7 @@ def network_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn
def network_deactivate(include=[], exclude=[]):
if not shared.opts.lora_fuse_diffusers:
if not shared.opts.lora_fuse_diffusers or shared.opts.lora_force_diffusers:
return
t0 = time.time()
sd_model = getattr(shared.sd_model, "pipe", shared.sd_model) # wrapped model compatiblility