colomi
0eb61f3e60
包含： - hair_service_sd: 换发型/换发色算法服务 (端口 8801) - photo_service: LoRA 训练调度服务 (端口 32678) - stable-diffusion-webui: SD WebUI 推理服务 (端口 57860) - kohya_ss_home: 训练环境代码 - meidaojia: 监控测试脚本 - setup.sh: 一键部署脚本 (conda环境恢复 + 配置生成 + 完整性检查) - start_all_services.sh: 启动3个服务 - configure.ini.template: 路径模板化 (BASE_DIR自动推导) - conda_envs/py310.yml: py310 环境定义 大文件 (weights/, models/, data/, conda_envs/*.tar.gz 等) 通过 .gitignore 排除， 由网盘单独上传。
65 lines
2.2 KiB
Python
Executable File
65 lines
2.2 KiB
Python
Executable File
import torch
|
|
|
|
import lyco_helpers
|
|
import network
|
|
|
|
|
|
class ModuleTypeLokr(network.ModuleType):
|
|
def create_module(self, net: network.Network, weights: network.NetworkWeights):
|
|
has_1 = "lokr_w1" in weights.w or ("lokr_w1_a" in weights.w and "lokr_w1_b" in weights.w)
|
|
has_2 = "lokr_w2" in weights.w or ("lokr_w2_a" in weights.w and "lokr_w2_b" in weights.w)
|
|
if has_1 and has_2:
|
|
return NetworkModuleLokr(net, weights)
|
|
|
|
return None
|
|
|
|
|
|
def make_kron(orig_shape, w1, w2):
|
|
if len(w2.shape) == 4:
|
|
w1 = w1.unsqueeze(2).unsqueeze(2)
|
|
w2 = w2.contiguous()
|
|
return torch.kron(w1, w2).reshape(orig_shape)
|
|
|
|
|
|
class NetworkModuleLokr(network.NetworkModule):
|
|
def __init__(self, net: network.Network, weights: network.NetworkWeights):
|
|
super().__init__(net, weights)
|
|
|
|
self.w1 = weights.w.get("lokr_w1")
|
|
self.w1a = weights.w.get("lokr_w1_a")
|
|
self.w1b = weights.w.get("lokr_w1_b")
|
|
self.dim = self.w1b.shape[0] if self.w1b is not None else self.dim
|
|
self.w2 = weights.w.get("lokr_w2")
|
|
self.w2a = weights.w.get("lokr_w2_a")
|
|
self.w2b = weights.w.get("lokr_w2_b")
|
|
self.dim = self.w2b.shape[0] if self.w2b is not None else self.dim
|
|
self.t2 = weights.w.get("lokr_t2")
|
|
|
|
def calc_updown(self, orig_weight):
|
|
if self.w1 is not None:
|
|
w1 = self.w1.to(orig_weight.device)
|
|
else:
|
|
w1a = self.w1a.to(orig_weight.device)
|
|
w1b = self.w1b.to(orig_weight.device)
|
|
w1 = w1a @ w1b
|
|
|
|
if self.w2 is not None:
|
|
w2 = self.w2.to(orig_weight.device)
|
|
elif self.t2 is None:
|
|
w2a = self.w2a.to(orig_weight.device)
|
|
w2b = self.w2b.to(orig_weight.device)
|
|
w2 = w2a @ w2b
|
|
else:
|
|
t2 = self.t2.to(orig_weight.device)
|
|
w2a = self.w2a.to(orig_weight.device)
|
|
w2b = self.w2b.to(orig_weight.device)
|
|
w2 = lyco_helpers.make_weight_cp(t2, w2a, w2b)
|
|
|
|
output_shape = [w1.size(0) * w2.size(0), w1.size(1) * w2.size(1)]
|
|
if len(orig_weight.shape) == 4:
|
|
output_shape = orig_weight.shape
|
|
|
|
updown = make_kron(output_shape, w1, w2)
|
|
|
|
return self.finalize_updown(updown, orig_weight, output_shape)
|