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。
56 lines
1.9 KiB
Python
Executable File
56 lines
1.9 KiB
Python
Executable File
import lyco_helpers
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import network
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class ModuleTypeHada(network.ModuleType):
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def create_module(self, net: network.Network, weights: network.NetworkWeights):
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if all(x in weights.w for x in ["hada_w1_a", "hada_w1_b", "hada_w2_a", "hada_w2_b"]):
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return NetworkModuleHada(net, weights)
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return None
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class NetworkModuleHada(network.NetworkModule):
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def __init__(self, net: network.Network, weights: network.NetworkWeights):
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super().__init__(net, weights)
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if hasattr(self.sd_module, 'weight'):
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self.shape = self.sd_module.weight.shape
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self.w1a = weights.w["hada_w1_a"]
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self.w1b = weights.w["hada_w1_b"]
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self.dim = self.w1b.shape[0]
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self.w2a = weights.w["hada_w2_a"]
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self.w2b = weights.w["hada_w2_b"]
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self.t1 = weights.w.get("hada_t1")
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self.t2 = weights.w.get("hada_t2")
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def calc_updown(self, orig_weight):
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w1a = self.w1a.to(orig_weight.device)
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w1b = self.w1b.to(orig_weight.device)
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w2a = self.w2a.to(orig_weight.device)
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w2b = self.w2b.to(orig_weight.device)
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output_shape = [w1a.size(0), w1b.size(1)]
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if self.t1 is not None:
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output_shape = [w1a.size(1), w1b.size(1)]
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t1 = self.t1.to(orig_weight.device)
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updown1 = lyco_helpers.make_weight_cp(t1, w1a, w1b)
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output_shape += t1.shape[2:]
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else:
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if len(w1b.shape) == 4:
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output_shape += w1b.shape[2:]
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updown1 = lyco_helpers.rebuild_conventional(w1a, w1b, output_shape)
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if self.t2 is not None:
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t2 = self.t2.to(orig_weight.device)
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updown2 = lyco_helpers.make_weight_cp(t2, w2a, w2b)
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else:
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updown2 = lyco_helpers.rebuild_conventional(w2a, w2b, output_shape)
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updown = updown1 * updown2
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return self.finalize_updown(updown, orig_weight, output_shape)
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