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store patches for Lora in a specialized module

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AUTOMATIC1111
2023-08-15 19:23:27 +03:00
parent 7327be97aa
commit f01682ee01
4 changed files with 118 additions and 61 deletions
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52
extensions-builtin/Lora/scripts/lora_script.py
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@@ -7,17 +7,14 @@ from fastapi import FastAPI
import network
import networks
import lora # noqa:F401
import lora_patches
import extra_networks_lora
import ui_extra_networks_lora
from modules import script_callbacks, ui_extra_networks, extra_networks, shared
from modules import script_callbacks, ui_extra_networks, extra_networks, shared, patches
def unload():
torch.nn.Linear.forward = torch.nn.Linear_forward_before_network
torch.nn.Linear._load_from_state_dict = torch.nn.Linear_load_state_dict_before_network
torch.nn.Conv2d.forward = torch.nn.Conv2d_forward_before_network
torch.nn.Conv2d._load_from_state_dict = torch.nn.Conv2d_load_state_dict_before_network
torch.nn.MultiheadAttention.forward = torch.nn.MultiheadAttention_forward_before_network
torch.nn.MultiheadAttention._load_from_state_dict = torch.nn.MultiheadAttention_load_state_dict_before_network
networks.originals.undo()
def before_ui():
@@ -28,46 +25,7 @@ def before_ui():
extra_networks.register_extra_network_alias(networks.extra_network_lora, "lyco")
if not hasattr(torch.nn, 'Linear_forward_before_network'):
torch.nn.Linear_forward_before_network = torch.nn.Linear.forward
if not hasattr(torch.nn, 'Linear_load_state_dict_before_network'):
torch.nn.Linear_load_state_dict_before_network = torch.nn.Linear._load_from_state_dict
if not hasattr(torch.nn, 'Conv2d_forward_before_network'):
torch.nn.Conv2d_forward_before_network = torch.nn.Conv2d.forward
if not hasattr(torch.nn, 'Conv2d_load_state_dict_before_network'):
torch.nn.Conv2d_load_state_dict_before_network = torch.nn.Conv2d._load_from_state_dict
if not hasattr(torch.nn, 'GroupNorm_forward_before_network'):
torch.nn.GroupNorm_forward_before_network = torch.nn.GroupNorm.forward
if not hasattr(torch.nn, 'GroupNorm_load_state_dict_before_network'):
torch.nn.GroupNorm_load_state_dict_before_network = torch.nn.GroupNorm._load_from_state_dict
if not hasattr(torch.nn, 'LayerNorm_forward_before_network'):
torch.nn.LayerNorm_forward_before_network = torch.nn.LayerNorm.forward
if not hasattr(torch.nn, 'LayerNorm_load_state_dict_before_network'):
torch.nn.LayerNorm_load_state_dict_before_network = torch.nn.LayerNorm._load_from_state_dict
if not hasattr(torch.nn, 'MultiheadAttention_forward_before_network'):
torch.nn.MultiheadAttention_forward_before_network = torch.nn.MultiheadAttention.forward
if not hasattr(torch.nn, 'MultiheadAttention_load_state_dict_before_network'):
torch.nn.MultiheadAttention_load_state_dict_before_network = torch.nn.MultiheadAttention._load_from_state_dict
torch.nn.Linear.forward = networks.network_Linear_forward
torch.nn.Linear._load_from_state_dict = networks.network_Linear_load_state_dict
torch.nn.Conv2d.forward = networks.network_Conv2d_forward
torch.nn.Conv2d._load_from_state_dict = networks.network_Conv2d_load_state_dict
torch.nn.GroupNorm.forward = networks.network_GroupNorm_forward
torch.nn.GroupNorm._load_from_state_dict = networks.network_GroupNorm_load_state_dict
torch.nn.LayerNorm.forward = networks.network_LayerNorm_forward
torch.nn.LayerNorm._load_from_state_dict = networks.network_LayerNorm_load_state_dict
torch.nn.MultiheadAttention.forward = networks.network_MultiheadAttention_forward
torch.nn.MultiheadAttention._load_from_state_dict = networks.network_MultiheadAttention_load_state_dict
networks.originals = lora_patches.LoraPatches()
script_callbacks.on_model_loaded(networks.assign_network_names_to_compvis_modules)
script_callbacks.on_script_unloaded(unload)