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
1.5 KiB
Python
Executable File
65 lines
1.5 KiB
Python
Executable File
import datetime
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import json
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import os
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saved_params_shared = {
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"batch_size",
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"clip_grad_mode",
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"clip_grad_value",
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"create_image_every",
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"data_root",
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"gradient_step",
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"initial_step",
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"latent_sampling_method",
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"learn_rate",
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"log_directory",
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"model_hash",
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"model_name",
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"num_of_dataset_images",
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"steps",
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"template_file",
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"training_height",
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"training_width",
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}
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saved_params_ti = {
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"embedding_name",
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"num_vectors_per_token",
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"save_embedding_every",
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"save_image_with_stored_embedding",
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}
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saved_params_hypernet = {
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"activation_func",
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"add_layer_norm",
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"hypernetwork_name",
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"layer_structure",
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"save_hypernetwork_every",
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"use_dropout",
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"weight_init",
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}
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saved_params_all = saved_params_shared | saved_params_ti | saved_params_hypernet
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saved_params_previews = {
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"preview_cfg_scale",
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"preview_height",
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"preview_negative_prompt",
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"preview_prompt",
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"preview_sampler_index",
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"preview_seed",
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"preview_steps",
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"preview_width",
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}
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def save_settings_to_file(log_directory, all_params):
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now = datetime.datetime.now()
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params = {"datetime": now.strftime("%Y-%m-%d %H:%M:%S")}
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keys = saved_params_all
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if all_params.get('preview_from_txt2img'):
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keys = keys | saved_params_previews
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params.update({k: v for k, v in all_params.items() if k in keys})
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filename = f'settings-{now.strftime("%Y-%m-%d-%H-%M-%S")}.json'
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with open(os.path.join(log_directory, filename), "w") as file:
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json.dump(params, file, indent=4)
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