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
49 lines
1.2 KiB
Python
Executable File
49 lines
1.2 KiB
Python
Executable File
from torch import nn
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class CTCHead(nn.Module):
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def __init__(self,
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in_channels,
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out_channels=6625,
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fc_decay=0.0004,
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mid_channels=None,
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return_feats=False,
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**kwargs):
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super(CTCHead, self).__init__()
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if mid_channels is None:
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self.fc = nn.Linear(
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in_channels,
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out_channels,
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bias=True,)
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else:
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self.fc1 = nn.Linear(
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in_channels,
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mid_channels,
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bias=True,
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)
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self.fc2 = nn.Linear(
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mid_channels,
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out_channels,
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bias=True,
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)
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self.out_channels = out_channels
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self.mid_channels = mid_channels
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self.return_feats = return_feats
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def forward(self, x, labels=None):
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if self.mid_channels is None:
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predicts = self.fc(x)
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else:
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x = self.fc1(x)
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predicts = self.fc2(x)
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if self.return_feats:
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result = dict()
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result['ctc'] = predicts
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result['ctc_neck'] = x
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else:
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result = predicts
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return result
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