Feature/rqvae

[lw-xundong]

Pull Request / 拉取请求

What does this PR do? / 这个PR做了什么？

This PR implements the RQVAE feature branch, introducing a new semantic ID quantization model for recommendation systems.
It includes updates to the model architecture, training pipeline, and example scripts for evaluation.

Type of Change / 变更类型

• 🐛 Bug fix / Bug修复
• ✨ New model/feature / 新模型/功能
• 📝 Documentation / 文档
• 🔧 Maintenance / 维护

Related Issues / 相关Issues

How to Test / 如何测试

cd examples/generative
python run_rqvae_amazon_books.py --data_path ./data/amazon-books/processed/item_embeddings_tinyllama.pt --device cuda:1

Checklist / 检查清单

• Code follows project style (ran python config/format_code.py) / 代码遵循项目风格（运行了格式化脚本）
• Added tests for new functionality / 为新功能添加了测试
• Updated documentation if needed / 如需要已更新文档
• All tests pass locally / 所有测试在本地通过

Additional Notes / 附加说明

Any other information for reviewers / 给审查者的其他信息

[codecov-commenter]

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Codecov Report

❌ Patch coverage is 1.08992% with 363 lines in your changes missing coverage. Please review.
✅ Project coverage is 36.19%. Comparing base (01bd90b) to head (f5f8066).
⚠️ Report is 73 commits behind head on main.

Files with missing lines	Patch %	Lines
torch_rechub/models/generative/rqvae.py	0.00%	224 Missing ⚠️
torch_rechub/trainers/rqvae_trainer.py	0.00%	122 Missing ⚠️
torch_rechub/utils/data.py	21.05%	15 Missing ⚠️
torch_rechub/models/generative/__init__.py	0.00%	2 Missing ⚠️
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Additional details and impacted files

@@            Coverage Diff             @@
##             main     #156      +/-   ##
==========================================
- Coverage   36.88%   36.19%   -0.70%     
==========================================
  Files          60       69       +9     
  Lines        4042     5009     +967     
==========================================
+ Hits         1491     1813     +322     
- Misses       2551     3196     +645     

Flag	Coverage Δ
unittests	36.19% <1.08%> (-0.70%)	⬇️

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