Public/automatic
1
0
Fork 0
mirror of https://github.com/vladmandic/automatic synced 2026-09-18 16:54:33 +02:00
Code Issues Packages Projects Releases Wiki Activity

lora loading for wrapped models (pulid)

Browse Source
This commit is contained in:
AI-Casanova
2024-11-11 19:18:38 -06:00
parent d495a4bb7d
commit e2124bc6f6
1 changed files with 14 additions and 13 deletions
Download Patch File Download Diff File Expand all files Collapse all files
extensions-builtin/Lora/networks.py
+14 -13
View File
@@ -50,44 +50,45 @@ convert_diffusers_name_to_compvis = lora_convert.convert_diffusers_name_to_compv
def assign_network_names_to_compvis_modules(sd_model):
if sd_model is None:
return
sd_model = getattr(shared.sd_model, "pipe", shared.sd_model) # wrapped model compatiblility
network_layer_mapping = {}
if shared.native:
if hasattr(shared.sd_model, 'text_encoder') and shared.sd_model.text_encoder is not None:
for name, module in shared.sd_model.text_encoder.named_modules():
prefix = "lora_te1_" if hasattr(shared.sd_model, 'text_encoder_2') else "lora_te_"
if hasattr(sd_model, 'text_encoder') and sd_model.text_encoder is not None:
for name, module in sd_model.text_encoder.named_modules():
prefix = "lora_te1_" if hasattr(sd_model, 'text_encoder_2') else "lora_te_"
network_name = prefix + name.replace(".", "_")
network_layer_mapping[network_name] = module
module.network_layer_name = network_name
if hasattr(shared.sd_model, 'text_encoder_2'):
for name, module in shared.sd_model.text_encoder_2.named_modules():
if hasattr(sd_model, 'text_encoder_2'):
for name, module in sd_model.text_encoder_2.named_modules():
network_name = "lora_te2_" + name.replace(".", "_")
network_layer_mapping[network_name] = module
module.network_layer_name = network_name
if hasattr(shared.sd_model, 'unet'):
for name, module in shared.sd_model.unet.named_modules():
if hasattr(sd_model, 'unet'):
for name, module in sd_model.unet.named_modules():
network_name = "lora_unet_" + name.replace(".", "_")
network_layer_mapping[network_name] = module
module.network_layer_name = network_name
if hasattr(shared.sd_model, 'transformer'):
for name, module in shared.sd_model.transformer.named_modules():
if hasattr(sd_model, 'transformer'):
for name, module in sd_model.transformer.named_modules():
network_name = "lora_transformer_" + name.replace(".", "_")
network_layer_mapping[network_name] = module
if "norm" in network_name and "linear" not in network_name:
continue
module.network_layer_name = network_name
else:
if not hasattr(shared.sd_model, 'cond_stage_model'):
if not hasattr(sd_model, 'cond_stage_model'):
sd_model.network_layer_mapping = {}
return
for name, module in shared.sd_model.cond_stage_model.wrapped.named_modules():
for name, module in sd_model.cond_stage_model.wrapped.named_modules():
network_name = name.replace(".", "_")
network_layer_mapping[network_name] = module
module.network_layer_name = network_name
for name, module in shared.sd_model.model.named_modules():
for name, module in sd_model.model.named_modules():
network_name = name.replace(".", "_")
network_layer_mapping[network_name] = module
module.network_layer_name = network_name
sd_model.network_layer_mapping = network_layer_mapping
shared.sd_model.network_layer_mapping = network_layer_mapping
def load_diffusers(name, network_on_disk, lora_scale=shared.opts.extra_networks_default_multiplier) -> network.Network: