| import torch |
| import torch.nn as nn |
|
|
| from .base import LycorisBaseModule |
| from .locon import LoConModule |
| from .loha import LohaModule |
| from .lokr import LokrModule |
| from .full import FullModule |
| from .norms import NormModule |
| from .diag_oft import DiagOFTModule |
| from .boft import ButterflyOFTModule |
| from .glora import GLoRAModule |
| from .dylora import DyLoraModule |
| from .ia3 import IA3Module |
|
|
| from ..functional.general import factorization |
|
|
|
|
| MODULE_LIST = [ |
| LoConModule, |
| LohaModule, |
| IA3Module, |
| LokrModule, |
| FullModule, |
| NormModule, |
| DiagOFTModule, |
| ButterflyOFTModule, |
| GLoRAModule, |
| DyLoraModule, |
| ] |
|
|
|
|
| def get_module(lyco_state_dict, lora_name): |
| for module in MODULE_LIST: |
| if module.algo_check(lyco_state_dict, lora_name): |
| return module, tuple(module.extract_state_dict(lyco_state_dict, lora_name)) |
| return None, None |
|
|
|
|
| @torch.no_grad() |
| def make_module(lyco_type: LycorisBaseModule, params, lora_name, orig_module): |
| try: |
| module = lyco_type.make_module_from_state_dict(lora_name, orig_module, *params) |
| except NotImplementedError: |
| module = None |
| return module |
|
|
