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.gitattributes

@@ -58,3 +58,10 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+robomimic/hdf5/can/mh/demo_v15.hdf5 filter=lfs diff=lfs merge=lfs -text
+robomimic/hdf5/can_mh_image.hdf5 filter=lfs diff=lfs merge=lfs -text
+robomimic/hdf5/can/mh/image_v15.hdf5 filter=lfs diff=lfs merge=lfs -text
+robocasa/hdf5/CoffeePressButton/human/demo_gentex_im128_randcams.hdf5 filter=lfs diff=lfs merge=lfs -text
+robocasa/hdf5/CloseDrawer/human/demo_gentex_im128_randcams.hdf5 filter=lfs diff=lfs merge=lfs -text
+robomimic/hdf5/lift_mh_image.hdf5 filter=lfs diff=lfs merge=lfs -text
+robomimic/hdf5/square_mh_image.hdf5 filter=lfs diff=lfs merge=lfs -text

MANIFEST.json

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+{
+  "upload_date": "2026-08-13",
+  "source_cluster_path": "/home/askhabaliev_gs/mipt_paper/oat/data",
+  "total_approx_gb": 18,
+  "suites": {
+    "robomimic": {
+      "paper_table_p": true,
+      "zarr": [
+        {"path": "robomimic/zarr/lift_N200.zarr", "episodes": 200, "action_dim": 7},
+        {"path": "robomimic/zarr/can_N200.zarr", "episodes": 200, "action_dim": 7},
+        {"path": "robomimic/zarr/square_N200.zarr", "episodes": 200, "action_dim": 7}
+      ],
+      "hdf5": [
+        "robomimic/hdf5/lift_mh_image.hdf5",
+        "robomimic/hdf5/can_mh_image.hdf5",
+        "robomimic/hdf5/square_mh_image.hdf5",
+        "robomimic/hdf5/can/mh/demo_v15.hdf5",
+        "robomimic/hdf5/can/mh/image_v15.hdf5"
+      ]
+    },
+    "metaworld": {
+      "paper_table_p": "single-task only",
+      "generated_locally": true,
+      "success_rule": "any_timestep_success",
+      "zarr": [
+        {"path": "metaworld/zarr/mt4_N50.zarr", "episodes": 200, "paper": false},
+        {"path": "metaworld/zarr/box-close_N50.zarr", "episodes": 50, "paper": true},
+        {"path": "metaworld/zarr/coffee-pull_N50.zarr", "episodes": 50, "paper": true},
+        {"path": "metaworld/zarr/disassemble_N50.zarr", "episodes": 50, "paper": true},
+        {"path": "metaworld/zarr/stick-pull_N50.zarr", "episodes": 50, "paper": true}
+      ]
+    },
+    "robocasa": {
+      "paper_table_p": true,
+      "mix": "50_human_150_mg_seed0",
+      "action_dim": 12,
+      "zarr": [
+        "robocasa/zarr/close_drawer_N200.zarr",
+        "robocasa/zarr/coffee_press_button_N200.zarr",
+        "robocasa/zarr/turn_off_sink_faucet_N200.zarr",
+        "robocasa/zarr/turn_off_microwave_N200.zarr"
+      ],
+      "hdf5_retained": [
+        "robocasa/hdf5/CloseDrawer/human/demo_gentex_im128_randcams.hdf5",
+        "robocasa/hdf5/CoffeePressButton/human/demo_gentex_im128_randcams.hdf5"
+      ]
+    }
+  }
+}

README.md

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+---
+license: mit
+task_categories:
+  - robotics
+language:
+  - en
+tags:
+  - oat
+  - imitation-learning
+  - robomimic
+  - metaworld
+  - robocasa
+  - zarr
+  - hdf5
+pretty_name: AAAI OAT Paper Training Datasets (HDF5 + Zarr)
+size_categories:
+  - 10G<n<100G
+---
+
+# AAAI paper datasets — OAT training data (HDF5 sources + Zarr)
+
+Canonical **training datasets** used to reproduce our AAAI submission  
+*"Spend Compute on Selection, Not Reduction"* (Consensus Selection / CS-D on **OAT** policies).
+
+**Hub repo:** `hackhackhack66666/aaai-datasets`  
+**Code / eval artifacts:** separate repos (`mipt_paper/oat` on cluster, HF model/eval repos for RoboCasa Wave1–2).  
+**This dataset repo contains only raw + converted training data** (HDF5 where retained, Zarr for all suites).
+
+---
+
+## Quick map — what is used in the paper?
+
+| Suite | Zarr (train) | HDF5 (source) | In paper **Table P**? | Paper role |
+|-------|--------------|---------------|----------------------|------------|
+| **RoboMimic** Lift | `robomimic/zarr/lift_N200.zarr` | `robomimic/hdf5/lift_mh_image.hdf5` | **Yes** (Lift run B ep-1400) | Generalization baseline |
+| **RoboMimic** Can | `robomimic/zarr/can_N200.zarr` | `robomimic/hdf5/can_mh_image.hdf5` (+ raw `can/mh/*`) | **Yes** | Generalization baseline |
+| **RoboMimic** Square | `robomimic/zarr/square_N200.zarr` | `robomimic/hdf5/square_mh_image.hdf5` | **Yes** | Generalization baseline |
+| **MetaWorld** coffee-pull | `metaworld/zarr/coffee-pull_N50.zarr` | — (generated) | **Yes** | Generalization baseline |
+| **MetaWorld** stick-pull | `metaworld/zarr/stick-pull_N50.zarr` | — | **Yes** | Generalization baseline |
+| **MetaWorld** disassemble | `metaworld/zarr/disassemble_N50.zarr` | — | **Yes** | Generalization baseline |
+| **MetaWorld** box-close | `metaworld/zarr/box-close_N50.zarr` | — | **Yes** | Generalization baseline |
+| **MetaWorld MT4** multitask | `metaworld/zarr/mt4_N50.zarr` | — | **No** (exploratory only) | Early multitask probe; **not** Table P |
+| **RoboCasa** close_drawer | `robocasa/zarr/close_drawer_N200.zarr` | partial human HDF5 | **Yes** | Generalization baseline |
+| **RoboCasa** coffee_press_button | `robocasa/zarr/coffee_press_button_N200.zarr` | partial human HDF5 | **Yes** | Generalization baseline |
+| **RoboCasa** turn_off_sink_faucet | `robocasa/zarr/turn_off_sink_faucet_N200.zarr` | — (zarr only) | **Yes** | Generalization baseline |
+| **RoboCasa** turn_off_microwave | `robocasa/zarr/turn_off_microwave_N200.zarr` | — (zarr only) | **Yes** | Generalization baseline |
+
+**LIBERO** is **not** included here (separate diagnosis track; different `n_test` protocol).
+
+---
+
+## Directory layout
+
+```text
+robomimic/
+  zarr/{lift,can,square}_N200.zarr/     # OAT training format (200 demos each)
+  hdf5/
+    lift_mh_image.hdf5
+    can_mh_image.hdf5
+    square_mh_image.hdf5
+    can/mh/demo_v15.hdf5                  # raw multi-human before image extract
+    can/mh/image_v15.hdf5
+
+metaworld/
+  zarr/
+    mt4_N50.zarr                          # 200 eps = 50×4 tasks (multitask)
+    {box-close,coffee-pull,disassemble,stick-pull}_N50.zarr
+  METAWORLD_GENERATION.md                 # how demos differ from upstream sim-env
+
+robocasa/
+  zarr/<task>_N200.zarr/                  # each includes ROBOCASA_SOURCE.txt
+  hdf5/
+    CloseDrawer/human/demo_gentex_im128_randcams.hdf5
+    CoffeePressButton/human/demo_gentex_im128_randcams.hdf5
+```
+
+Approximate sizes (cluster, 2026-08-13):
+
+| Path | ~Size |
+|------|-------|
+| RoboMimic HDF5 total | 10.5 GB |
+| RoboMimic Zarr total | 1.0 GB |
+| MetaWorld Zarr total | 1.4 GB |
+| RoboCasa Zarr total | 4.6 GB |
+| RoboCasa HDF5 (retained) | 0.6 GB |
+| **Total** | **~18 GB** |
+
+---
+
+## Common Zarr schema (OAT)
+
+All Zarr stores follow the OAT pipeline layout:
+
+- `data/` — time-major arrays (`action`, RGB, proprioception)
+- `meta/episode_ends` — cumulative step indices per episode
+- RoboCasa only: `ROBOCASA_SOURCE.txt` inside each zarr (provenance + sha256 in paper log)
+
+Validate locally (from `oat/` repo):
+
+```bash
+python scripts/validate_robomimic_data.py
+python scripts/validate_robocasa_data.py
+python scripts/validate_metaworld_data.py data/metaworld/box-close_N50.zarr --num-tasks 1
+python scripts/validate_metaworld_data.py data/metaworld/mt4_N50.zarr --num-tasks 4 --require-subtask-counts
+```
+
+---
+
+## 1. RoboMimic (official mh demos → Zarr)
+
+### Source
+
+- Benchmark: **RoboMimic multi-human (mh)** image demonstrations.
+- Tasks: **Lift**, **Can**, **Square**.
+- **200 demonstrations** per task (subsampled from 300 mh demos).
+- Lift: direct download `lift_mh_image.hdf5`.
+- Can / Square: download raw `demo_v15.hdf5`, replay through robosuite 1.5 to extract `image_v15.hdf5` (see `scripts/extract_robomimic_mh_image.sh`).
+
+### Zarr keys (train)
+
+| Key | Shape (per step) |
+|-----|------------------|
+| `action` | 7 |
+| `agentview_image` | 84×84×3 |
+| `robot0_eye_in_hand_image` | 84×84×3 |
+| (+ proprio keys per converter) | |
+
+### Paper linkage
+
+- Tokenizer: top MSE checkpoint per task (`ep-0690` square, `ep-1970` lift, etc.).
+- Policy TopK @ `test_start_seed=1000`; **Table P report** @ `test_start_seed=10000`, `-n 5`, OAT8.
+- Locked Table P ckpts: Can ep-1700, Square ep-0700, Lift ep-1400 (run B).
+
+### Notes
+
+- **Do not** use legacy `OAT-RoboMimic-Fine-tune/BLT-OAT/data/robomimic/` (old ph layout) — unrelated to this paper track.
+
+---
+
+## 2. MetaWorld (locally generated expert demos → Zarr)
+
+### ⚠️ Important — not the official MetaWorld HDF5 download
+
+All MetaWorld data here was **generated on our cluster** with:
+
+```bash
+python scripts/gen_metaworld_data.py --task_name <task> --num_episodes 50 --force
+```
+
+(log: `logs/metaworld_single_data_regen.log`; multitask: `logs/gen_metaworld_mt4_N50.log`)
+
+Environment code is ported from **[sim-env](https://github.com/Chaoqi-LIU/sim-env)** into `oat/oat/env/metaworld/` (MuJoCo **2.1.0** / MetaWorld v2 stack — **different** from RoboMimic/LIBERO robosuite 1.4).
+
+### Demo acceptance rule (differs from stricter filters)
+
+An episode is kept iff **`info["success"] == True` on at least one timestep** during the expert rollout:
+
+```python
+episode_success_count += int(bool(info.get("success", False)))
+if episode_success_count == 0:
+    continue  # reject episode, retry with new seed
+```
+
+We **do not** require success only on the terminal step. This matches **`mt4_N50`** generation and the four **single-task** regen runs used for Table P.
+
+### Reset / seed fix (July 2026)
+
+Single-task regen originally hung because `MetaworldEnv.reset()` without `seed` restored a **fixed** MuJoCo snapshot. Fix:
+
+```python
+roll_seed = episode_idx * 1_000_000 + attempt_idx
+obs_dict, _ = env.reset(seed=roll_seed)
+```
+
+Without incrementing `attempt_idx` on reject, retries repeat the same failed init.
+
+### Tasks & episode counts (validated 2026-08-13)
+
+| Zarr | Episodes | Action dim | Cameras | Steps (total) |
+|------|----------|------------|---------|---------------|
+| `mt4_N50.zarr` | 200 (50×4) | 4 | 4×128² RGB + `agent_pos` 9D | 20 316 |
+| `box-close_N50.zarr` | 50 | 4 | same | 5 616 |
+| `coffee-pull_N50.zarr` | 50 | 4 | same | 4 088 |
+| `disassemble_N50.zarr` | 50 | 4 | same | 5 220 |
+| `stick-pull_N50.zarr` | 50 | 4 | same | 6 101 |
+
+MT4 task order in `subtask_counts`: `[box-close, coffee-pull, disassemble, stick-pull]`.
+
+Single-task files can also be obtained deterministically by splitting `mt4_N50.zarr` (`scripts/split_metaworld_mt4_zarr.py`, round-robin `i % 4`); **paper Table P uses freshly regen single-task zarr**, byte-identical to split for the episodes that were completed before regen.
+
+### How this differs from “original sim-env / paper MetaWorld”
+
+1. **Success timing:** our collector accepts **any-time success** during the demo rollout (see above). A stricter **terminal-only** filter was tested and rejected for compatibility with `mt4_N50`.
+2. **Implementation port:** same *intent* as sim-env, but our wrapper had the **reset-without-seed bug** (fixed before final single-task zarr). Treat MW numbers as **valid within this port**, not as a claim of bit-identical reproduction of Chaoqi sim-env demo files.
+3. **Paper limitation (explicit):** *“MetaWorld demo port — controlled limitation; interpret MW within our implementation.”* (see `RESULTS.md` / `RESOLUTIONPLAN.md` in code repo).
+
+### Paper linkage
+
+- **Table P** uses **single-task specialists** (one zarr → one tokenizer → one policy per task).
+- `mt4_N50.zarr` is **exploratory multitask** (shared model); **not** reported in Table P.
+
+---
+
+## 3. RoboCasa (official v0.2 HDF5 → Zarr)
+
+### Source (G0 protocol)
+
+- RoboCasa **v0.2** registry: `human_im` + `mg_im` from UT Austin Box (`demo_gentex_im128_randcams.hdf5`).
+- Mix per task: **50 human + 150 MimicGen**, subsample **seed 0**, **action_dim = 12**.
+- Converter: `scripts/convert_robocasa_dataset.py`.
+
+### Tasks (paper Table P)
+
+| Task slug | Zarr | Human+MG eps | TopK lock (selection @ seed 2000) |
+|-----------|------|--------------|-----------------------------------|
+| `close_drawer` | `close_drawer_N200.zarr` | 200 | ep-0500 @ SR 0.700 |
+| `coffee_press_button` | `coffee_press_button_N200.zarr` | 200 | ep-0500 @ SR 0.600 |
+| `turn_off_sink_faucet` | `turn_off_sink_faucet_N200.zarr` | 200 | ep-0500 @ SR 0.580 |
+| `turn_off_microwave` | `turn_off_microwave_N200.zarr` | 200 | ep-0500 @ SR 0.620 |
+
+Each zarr contains `ROBOCASA_SOURCE.txt` listing exact human/MG HDF5 keys used before MG files were deleted on cluster (disk policy).
+
+### HDF5 retention policy on cluster
+
+After Zarr conversion we **deleted MimicGen HDF5** to save disk. **Human** HDF5 for **CloseDrawer** and **CoffeePressButton** were kept (~614 MB).  
+**Microwave** and **sink** human HDF5 were also removed post-convert — **full training data is in Zarr only** for those two tasks.
+
+### Obs keys (Zarr)
+
+`action`, `robot0_agentview_{left,right}_rgb`, `robot0_eye_in_hand_rgb`, `robot0_eef_pos`, `robot0_eef_quat`, `robot0_gripper_qpos` (128×128 RGB).
+
+### Paper eval protocol (not in this repo)
+
+- Selection TopK: `test_start_seed=2000`, `n_test=50`.
+- Table P report: literal seeds **`10000…10004`**, each `-n 1 --n_test 50`, OAT8 + BoN8 `vote`.
+
+---
+
+## Regeneration pointers (code repo)
+
+| Suite | Script |
+|-------|--------|
+| MetaWorld gen | `scripts/gen_metaworld_data.py`, `scripts/cluster_gen_metaworld_single_data.sh` |
+| MetaWorld split | `scripts/split_metaworld_mt4_zarr.py` |
+| RoboMimic convert | `scripts/convert_robomimic_dataset.py`, `scripts/prepare_robomimic_{lift,can,square}.sh` |
+| RoboCasa convert | `scripts/convert_robocasa_dataset.py` |
+
+Cluster path when uploaded (2026-08): `/home/askhabaliev_gs/mipt_paper/oat/data/`.
+
+---
+
+## Citation
+
+If you use these datasets, cite **OAT** (ordered action tokenization) and our AAAI paper (anonymous submission at upload time). RoboMimic / MetaWorld / RoboCasa have their own benchmark citations — see respective papers.
+
+---
+
+## Changelog
+
+| Date | Note |
+|------|------|
+| 2026-08-13 | Initial public upload: all paper Zarr + retained HDF5 from MIPT cluster `mipt_paper/oat`. |

metaworld/METAWORLD_GENERATION.md

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+# MetaWorld demo generation — technical notes (AAAI datasets)
+
+This file documents **how our MetaWorld Zarr differs** from downloading pre-built demos elsewhere.
+
+## Generator
+
+- Script: `scripts/gen_metaworld_data.py`
+- Cluster log (single-task regen): `logs/metaworld_single_data_regen.log`
+- Multitask log: `logs/gen_metaworld_mt4_N50.log`
+
+## Expert
+
+- MetaWorld v2 **oracle / expert policies** roll out until horizon or success.
+- **4× RGB** 128×128: `corner`, `corner2`, `corner3`, `behindGripper`
+- **`agent_pos`**: 9D
+- **Action**: 4D
+
+## Episode filter (critical)
+
+```python
+episode_success_count += int(bool(info.get("success", False)))
+if episode_success_count == 0:
+    attempt_idx += 1
+    continue  # reject — do not advance episode_idx
+```
+
+→ Episode is **accepted if success is True on any step**, not only the last step.
+
+We briefly tested **terminal-only** success; on successful rollouts it was equivalent, but we kept the any-step rule to match `mt4_N50` and avoid rejecting valid expert demos.
+
+## Reset seed (critical fix, 2026-07-10)
+
+Without `seed`, our `MetaworldEnv.reset()` restored the **same** MuJoCo init snapshot → infinite reject loop on hard inits.
+
+```python
+roll_seed = episode_idx * 1_000_000 + attempt_idx
+obs_dict, _ = env.reset(seed=roll_seed)
+```
+
+## Relation to sim-env
+
+Env/runner ported from [Chaoqi-LIU/sim-env](https://github.com/Chaoqi-LIU/sim-env).  
+We do **not** ship sim-env's original demo files; we **regenerated** 50 eps/task under our port.
+
+**Paper stance:** MetaWorld results are interpreted **within this demo port** (see paper limitations).
+
+## Single-task vs MT4
+
+| File | Use in paper |
+|------|----------------|
+| `{task}_N50.zarr` | **Table P** (single-task specialist training) |
+| `mt4_N50.zarr` | Exploratory multitask only |
+
+Split from MT4 (`scripts/split_metaworld_mt4_zarr.py`, round-robin `episode i → task i%4`) is byte-identical to source episodes for those indices.

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