1b87a98261
## 主要更新 - ✨ 更新所有依赖到最新稳定版本 - 📝 添加详细的项目文档和模型推荐 - 🔧 配置 VSCode Cloud Studio 预览功能 - 🐛 修复 PyTorch API 弃用警告 ## 依赖更新 - diffusers: 0.27.2 → 0.35.2 - gradio: 4.21.0 → 5.46.0 - peft: 0.7.1 → 0.18.0 - Pillow: 9.5.0 → 11.3.0 - fastapi: 0.108.0 → 0.116.2 ## 新增文件 - CLAUDE.md - 项目架构和开发指南 - UPGRADE_NOTES.md - 详细的升级说明 - .vscode/preview.yml - 预览配置 - .vscode/LAUNCH_GUIDE.md - 启动指南 - .gitignore - 更新的忽略规则 ## 代码修复 - 修复 iopaint/model/ldm.py 中的 torch.cuda.amp.autocast() 弃用警告 ## 文档更新 - README.md - 添加模型推荐和使用指南 - 完整的项目源码（iopaint/） - Web 前端源码（web_app/） 🤖 Generated with Claude Code
94 lines
2.7 KiB
YAML
94 lines
2.7 KiB
YAML
model:
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target: sgm.models.diffusion.DiffusionEngine
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params:
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scale_factor: 0.13025
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disable_first_stage_autocast: True
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denoiser_config:
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target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser
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params:
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num_idx: 1000
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scaling_config:
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target: sgm.modules.diffusionmodules.denoiser_scaling.EpsScaling
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discretization_config:
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target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
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network_config:
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target: sgm.modules.diffusionmodules.openaimodel.UNetModel
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params:
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adm_in_channels: 2816
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num_classes: sequential
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use_checkpoint: True
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in_channels: 4
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out_channels: 4
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model_channels: 320
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attention_resolutions: [4, 2]
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num_res_blocks: 2
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channel_mult: [1, 2, 4]
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num_head_channels: 64
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use_linear_in_transformer: True
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transformer_depth: [1, 2, 10]
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context_dim: 2048
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spatial_transformer_attn_type: softmax-xformers
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conditioner_config:
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target: sgm.modules.GeneralConditioner
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params:
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emb_models:
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- is_trainable: False
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input_key: txt
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target: sgm.modules.encoders.modules.FrozenCLIPEmbedder
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params:
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layer: hidden
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layer_idx: 11
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- is_trainable: False
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input_key: txt
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target: sgm.modules.encoders.modules.FrozenOpenCLIPEmbedder2
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params:
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arch: ViT-bigG-14
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version: laion2b_s39b_b160k
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freeze: True
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layer: penultimate
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always_return_pooled: True
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legacy: False
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- is_trainable: False
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input_key: original_size_as_tuple
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target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
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params:
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outdim: 256
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- is_trainable: False
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input_key: crop_coords_top_left
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target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
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params:
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outdim: 256
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- is_trainable: False
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input_key: target_size_as_tuple
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target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
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params:
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outdim: 256
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first_stage_config:
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target: sgm.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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attn_type: vanilla-xformers
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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: [1, 2, 4, 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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