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import re
import torch
import gradio as gr
from fastapi import FastAPI
import network
import networks
import lora # noqa:F401
import extra_networks_lora
import ui_extra_networks_lora
from modules import script_callbacks, ui_extra_networks, extra_networks, shared
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
def before_ui():
ui_extra_networks.register_page(ui_extra_networks_lora.ExtraNetworksPageLora())
extra_network = extra_networks_lora.ExtraNetworkLora()
extra_networks.register_extra_network(extra_network)
extra_networks.register_extra_network_alias(extra_network, "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, '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.MultiheadAttention.forward = networks.network_MultiheadAttention_forward
torch.nn.MultiheadAttention._load_from_state_dict = networks.network_MultiheadAttention_load_state_dict
script_callbacks.on_model_loaded(networks.assign_network_names_to_compvis_modules)
script_callbacks.on_script_unloaded(unload)
script_callbacks.on_before_ui(before_ui)
script_callbacks.on_infotext_pasted(networks.infotext_pasted)
shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), {
"sd_lora": shared.OptionInfo("None", "Add network to prompt", gr.Dropdown, lambda: {"choices": ["None", *networks.available_networks]}, refresh=networks.list_available_networks),
"lora_preferred_name": shared.OptionInfo("Alias from file", "When adding to prompt, refer to Lora by", gr.Radio, {"choices": ["Alias from file", "Filename"]}),
"lora_add_hashes_to_infotext": shared.OptionInfo(True, "Add Lora hashes to infotext"),
"lora_show_all": shared.OptionInfo(False, "Always show all networks on the Lora page").info("otherwise, those detected as for incompatible version of Stable Diffusion will be hidden"),
"lora_hide_unknown_for_versions": shared.OptionInfo([], "Hide networks of unknown versions for model versions", gr.CheckboxGroup, {"choices": ["SD1", "SD2", "SDXL"]}),
}))
shared.options_templates.update(shared.options_section(('compatibility', "Compatibility"), {
"lora_functional": shared.OptionInfo(False, "Lora/Networks: use old method that takes longer when you have multiple Loras active and produces same results as kohya-ss/sd-webui-additional-networks extension"),
}))
def create_lora_json(obj: network.NetworkOnDisk):
return {
"name": obj.name,
"alias": obj.alias,
"path": obj.filename,
"metadata": obj.metadata,
}
def api_networks(_: gr.Blocks, app: FastAPI):
@app.get("/sdapi/v1/loras")
async def get_loras():
return [create_lora_json(obj) for obj in networks.available_networks.values()]
@app.post("/sdapi/v1/refresh-loras")
async def refresh_loras():
return networks.list_available_networks()
script_callbacks.on_app_started(api_networks)
re_lora = re.compile("<lora:([^:]+):")
def infotext_pasted(infotext, d):
hashes = d.get("Lora hashes")
if not hashes:
return
hashes = [x.strip().split(':', 1) for x in hashes.split(",")]
hashes = {x[0].strip().replace(",", ""): x[1].strip() for x in hashes}
def network_replacement(m):
alias = m.group(1)
shorthash = hashes.get(alias)
if shorthash is None:
return m.group(0)
network_on_disk = networks.available_network_hash_lookup.get(shorthash)
if network_on_disk is None:
return m.group(0)
return f'<lora:{network_on_disk.get_alias()}:'
d["Prompt"] = re.sub(re_lora, network_replacement, d["Prompt"])
script_callbacks.on_infotext_pasted(infotext_pasted)
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