| # Markovian Task Classification — Run Commands |
|
|
| > Chạy từ thư mục gốc: |
| > `cd /pfss/mlde/workspaces/mlde_wsp_IAS_SAMMerge/VLA/doanh/video_world/video_gen_physics` |
|
|
| --- |
|
|
| ## Bước 1 — Khởi động vLLM server (Terminal riêng, giữ chạy nền) |
|
|
| ```bash |
| bash scripts/launch_qwen3vl_server.sh |
| ``` |
|
|
| Chờ đến khi thấy: `Application startup complete` (~2–5 phút lần đầu tải model). |
|
|
| --- |
|
|
| ## Bước 2 — Phân loại DROID (20 chunks) |
|
|
| ```bash |
| python scripts/classify_markovian_qwen.py |
| ``` |
|
|
| Output: |
| - `scripts/task_labels_cache.jsonl` — cache resumable |
| - `scripts/task_labels.csv` — ~49k task labels |
|
|
| --- |
|
|
| ## Bước 3 — Join labels về episodes + sample 130/label (DROID) |
|
|
| ```bash |
| python scripts/join_labels_to_episodes.py |
| ``` |
|
|
| Output: |
| - `scripts/episode_markovian_split_full.csv` — toàn bộ episodes trong 20 chunks |
| - `scripts/episode_markovian_split.csv` — **130 markovian + 130 non_markovian** |
| |
| --- |
| |
| ## Bước 4 — Phân loại GR1 humanoid (DreamDojo-HV + EgoDex) |
| |
| ```bash |
| python scripts/classify_markovian_gr1.py |
| ``` |
| |
| Output: |
| - `scripts/gr1_task_labels_cache.jsonl` — cache resumable |
| - `scripts/gr1_task_labels.csv` — toàn bộ 133 episodes |
| - `scripts/gr1_episode_sampled.csv` — **≤33/label/source** (cân bằng 2 nguồn) |
|
|
| --- |
|
|
| ## Tóm tắt output files |
|
|
| | File | Mô tả | |
| |---|---| |
| | `scripts/task_labels.csv` | DROID: 49k task strings + label | |
| | `scripts/episode_markovian_split_full.csv` | DROID: tất cả episodes trong 20 chunks | |
| | `scripts/episode_markovian_split.csv` | DROID: 260 episodes sampled (130×2) | |
| | `scripts/gr1_task_labels.csv` | GR1: 133 episodes + label | |
| | `scripts/gr1_episode_sampled.csv` | GR1: ~132 episodes sampled (33×2×2) | |
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|
