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Direction-Speed 动作分解实验数据集。对应 GitHub 仓库 [chainpray/qc](https://github.com/chainpray/qc)。
## 结构
```
cube-triple-play-singletask/
└── {task}/
└── {horizon}/
└── {method}/
└── {ds_mode}/
└── seed{N}/
├── eval.csv # step, success, episode.return, ...
├── flags.json # ds_mode, horizon_length, seed, ...
├── online_agent.csv # critic_loss, actor_loss, alpha, ...
├── env.csv # qpos, qvel, time, ...
└── params_*.pkl # 模型 checkpoint（仅 seed0）
```
## 目录
| 目录 | 内容 | Seeds | Eval | Runs |
|------|------|:---:|:---:|:---:|
| `task1/h1/rlpd/` | cube-triple-task1 RLPD H=1 | 4 | 50 | 16 |
| `task1/h5/rlpd/` | cube-triple-task1 RLPD-AC H=5 | 10 | 100 | 40 |
| `task1/h5/rlpd-4s/` | cube-triple-task1 RLPD-AC H=5（旧） | 4 | 50 | 16 |
| `task2/h1/rlpd/` | cube-triple-task2 RLPD H=1 | 4 | 50 | 16 |
| `task2/h5/rlpd/` | cube-triple-task2 RLPD-AC H=5 | 4 | 50 | 16 |
| `task2/h5/fql/` | cube-triple-task2 FQL H=5 | 3 | 50 | 6 |
| `task3/h1/rlpd/` | cube-triple-task3 RLPD H=1 | 10 | 100 | 40 |
| `task3/h5/rlpd/` | cube-triple-task3 RLPD-AC H=5 | 10 | 100 | 40 |
| `task4/h1/rlpd/` | cube-triple-task4 RLPD H=1 | 10 | 100 | 40 |
| `task4/h5/rlpd/` | cube-triple-task4 RLPD-AC H=5 | 10 | 100 | 40 |
| `task5/h1/rlpd/` | cube-triple-task5 RLPD H=1 | 10 | 100 | 40 |
| `task5/h5/rlpd/` | cube-triple-task5 RLPD-AC H=5 | 10 | 100 | 40 |
| 其他目录 | 内容 | 实验数 |
|------|------|:---:|
| `reproduce/` | QC 论文复现实验 | 4 |
| `parallel_benchmark/` | 并行训练压力测试 | 2 |
> **命名约定**：`h1`/`h5` = horizon length；`none` = TanhNormal baseline；`posthoc`/`stereographic`/`spherical` = DS 模式。`rlpd-4s` 为旧版 4-seed 实验，与新 10-seed 版区分。
## 使用
```python
from huggingface_hub import hf_hub_download
# 下载 task4 H=5 stereographic seed0 的 eval.csv
hf_hub_download("SZUEAILab/ds-experiments",
"ds_experiments/cube-triple-play-singletask/task4/h5/rlpd/stereographic/seed0/eval.csv",
repo_type="dataset")
```
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