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。
99 lines
2.5 KiB
YAML
Executable File
99 lines
2.5 KiB
YAML
Executable File
# File modified by authors of InstructPix2Pix from original (https://github.com/CompVis/stable-diffusion).
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# See more details in LICENSE.
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model:
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base_learning_rate: 1.0e-04
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target: modules.models.diffusion.ddpm_edit.LatentDiffusion
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params:
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linear_start: 0.00085
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linear_end: 0.0120
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num_timesteps_cond: 1
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log_every_t: 200
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timesteps: 1000
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first_stage_key: edited
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cond_stage_key: edit
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# image_size: 64
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# image_size: 32
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image_size: 16
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channels: 4
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cond_stage_trainable: false # Note: different from the one we trained before
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conditioning_key: hybrid
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monitor: val/loss_simple_ema
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scale_factor: 0.18215
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use_ema: false
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scheduler_config: # 10000 warmup steps
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target: ldm.lr_scheduler.LambdaLinearScheduler
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params:
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warm_up_steps: [ 0 ]
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cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
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f_start: [ 1.e-6 ]
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f_max: [ 1. ]
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f_min: [ 1. ]
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unet_config:
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target: ldm.modules.diffusionmodules.openaimodel.UNetModel
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params:
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image_size: 32 # unused
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in_channels: 8
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out_channels: 4
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model_channels: 320
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attention_resolutions: [ 4, 2, 1 ]
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num_res_blocks: 2
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channel_mult: [ 1, 2, 4, 4 ]
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num_heads: 8
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use_spatial_transformer: True
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transformer_depth: 1
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context_dim: 768
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use_checkpoint: False
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legacy: False
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first_stage_config:
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target: ldm.models.autoencoder.AutoencoderKL
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params:
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embed_dim: 4
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monitor: val/rec_loss
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ddconfig:
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double_z: true
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z_channels: 4
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resolution: 256
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in_channels: 3
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out_ch: 3
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ch: 128
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ch_mult:
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- 1
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- 2
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- 4
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- 4
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num_res_blocks: 2
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attn_resolutions: []
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dropout: 0.0
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lossconfig:
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target: torch.nn.Identity
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cond_stage_config:
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target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
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data:
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target: main.DataModuleFromConfig
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params:
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batch_size: 128
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num_workers: 1
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wrap: false
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validation:
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target: edit_dataset.EditDataset
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params:
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path: data/clip-filtered-dataset
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cache_dir: data/
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cache_name: data_10k
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split: val
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min_text_sim: 0.2
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min_image_sim: 0.75
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min_direction_sim: 0.2
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max_samples_per_prompt: 1
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min_resize_res: 512
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max_resize_res: 512
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crop_res: 512
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output_as_edit: False
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real_input: True
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