README.md

---
task_categories:
- robotics
tags:
- robotics
- action-selection
- search
- branch-and-rollback
configs:
- config_name: searches
  data_files:
  - split: train
    path: meta/searches/*__seed5*.parquet
- config_name: nodes
  data_files:
  - split: train
    path: data/nodes/**/*__seed5*.parquet
- config_name: steps
  data_files:
  - split: train
    path: data/steps/**/*__seed5*.parquet
---

# scoring_data

**At a state: several action chunks proposed from it, and how each one actually ended.**
A branch the search dropped was cut off mid-episode, so it is resumed from its own snapshot
and carried to a finish — the action nobody executed still gets an answer to *would this
have worked*.

1037 searches · 13 tasks · 39,016 nodes, each with its own
state and image.

This repo hosts the data. **What it means, how it was produced and how to use it live in
the code that wrote it:** [https://github.com/EAI-RSM/rewind](https://github.com/EAI-RSM/rewind) — see its README for the format, the
search strategies, and worked examples of loading a record.

## Splits

Both halves live here, told apart by the `split` column of `meta/searches` rather than by
path. The blocks are disjoint by construction, so a scorer trained on one can be measured
on the other without having seen it.

| split | seeds | in this repo |
|---|---|---|
| `train` | collection seeds (50000+) — fans to learn from | 1037 searches |
| `test` | the benchmark's own evaluation seeds (40000+) — what a scorer is measured on | **not collected yet** |

```python
from rewind.record.hub import index
runs  = index("mahgoobi/scoring_data")
train = [r for r in runs if r["split"] == "train"]
test  = [r for r in runs if r["split"] == "test"]
```

## Tasks

One row per task: how many searches it contributed, which splits, which scene configs, the
seeds, and the **benchmark commit** whose code built those scenes.

That last column is not bookkeeping. The benchmark's success criteria change over time —
`put_milktea_on_shelf` gained an upright requirement, `put_milktea_next_to_laptop` a 15°
tolerance — so two runs of one task under different commits are scored by different rules
and should not be pooled. Runs of a task the change did not touch stay comparable.

| task | runs | splits | configs | seeds | benchmark commit |
|---|---|---|---|---|---|
| `drop_apple_in_bin_ks` | 81 | train | kitchens_clean | 50000, 50001, 50002, 50003, 50004, 50005, 50006, 50007, 50008, 50009, 50010, 50011, 50012, 50013, 50014, 50015, 50016, 50017, 50018, 50019, 50020, 50021, 50022, 50023, 50024, 50025, 50026, 50027, 50028, 50029, 50030, 50031, 50032, 50033, 50034, 50035, 50036, 50037, 50038, 50039, 50040, 50041, 50042, 50043, 50044, 50045, 50046, 50047, 50048, 50049, 50050, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50063, 50064, 50065, 50066, 50067, 50068, 50069, 50070, 50071, 50072, 50073, 50074, 50075, 50076, 50077, 50078, 50079, 50082 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |
| `move_cup_put_pen_in_cup` | 78 | train | study_clean | 50000, 50001, 50002, 50003, 50004, 50005, 50006, 50007, 50008, 50009, 50010, 50011, 50012, 50013, 50014, 50015, 50016, 50017, 50018, 50019, 50020, 50021, 50022, 50023, 50024, 50025, 50026, 50027, 50028, 50029, 50030, 50031, 50032, 50033, 50034, 50035, 50036, 50037, 50038, 50039, 50040, 50041, 50042, 50043, 50044, 50045, 50046, 50047, 50048, 50049, 50050, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50063, 50064, 50065, 50066, 50067, 50068, 50069, 50070, 50071, 50072, 50073, 50074, 50075, 50078, 50081 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |
| `move_hamburger_onto_plate_ks` | 69 | train | kitchens_clean | 50000, 50001, 50003, 50005, 50006, 50007, 50009, 50010, 50011, 50012, 50013, 50015, 50018, 50019, 50020, 50021, 50022, 50023, 50026, 50027, 50028, 50029, 50030, 50032, 50033, 50034, 50035, 50036, 50037, 50041, 50043, 50044, 50045, 50047, 50048, 50049, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50064, 50065, 50068, 50070, 50071, 50073, 50074, 50075, 50076, 50077, 50078, 50079, 50082, 50084, 50085, 50086, 50090, 50092, 50094, 50096, 50098 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |
| `move_pen_to_box` | 82 | train | study_clean | 50000, 50001, 50002, 50003, 50004, 50005, 50006, 50007, 50008, 50009, 50010, 50011, 50012, 50013, 50014, 50015, 50016, 50017, 50018, 50019, 50020, 50021, 50022, 50023, 50024, 50025, 50026, 50027, 50028, 50029, 50030, 50031, 50032, 50033, 50034, 50035, 50036, 50037, 50038, 50039, 50040, 50041, 50042, 50043, 50044, 50045, 50046, 50047, 50048, 50049, 50050, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50063, 50064, 50065, 50066, 50067, 50068, 50069, 50070, 50071, 50072, 50073, 50074, 50075, 50076, 50077, 50079, 50080, 50081, 50082 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |
| `place_bowl_in_dishrack_ks` | 80 | train | kitchens_clean | 50000, 50001, 50002, 50003, 50004, 50005, 50006, 50007, 50008, 50009, 50010, 50011, 50012, 50013, 50014, 50015, 50016, 50017, 50018, 50019, 50020, 50021, 50022, 50023, 50024, 50025, 50026, 50027, 50028, 50029, 50030, 50031, 50032, 50033, 50034, 50035, 50036, 50037, 50038, 50039, 50040, 50041, 50042, 50043, 50044, 50045, 50046, 50047, 50048, 50049, 50050, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50063, 50064, 50065, 50066, 50067, 50068, 50069, 50070, 50071, 50072, 50073, 50074, 50075, 50076, 50077, 50078, 50082 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |
| `put_bottle_in_basket` | 79 | train | kitchenl_clean | 50000, 50001, 50002, 50003, 50004, 50005, 50006, 50007, 50008, 50009, 50010, 50011, 50012, 50013, 50014, 50015, 50016, 50017, 50018, 50019, 50020, 50021, 50022, 50023, 50024, 50025, 50027, 50028, 50029, 50030, 50031, 50032, 50033, 50034, 50035, 50036, 50037, 50038, 50039, 50040, 50041, 50042, 50043, 50044, 50045, 50046, 50047, 50048, 50049, 50050, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50063, 50064, 50065, 50066, 50067, 50068, 50069, 50070, 50071, 50072, 50073, 50074, 50075, 50076, 50077, 50078, 50079 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |
| `put_bottle_in_fridge` | 80 | train | kitchenl_clean | 50000, 50001, 50002, 50003, 50004, 50005, 50006, 50007, 50008, 50009, 50010, 50011, 50012, 50013, 50014, 50015, 50016, 50017, 50018, 50019, 50020, 50021, 50022, 50023, 50024, 50025, 50026, 50027, 50028, 50029, 50030, 50031, 50032, 50033, 50034, 50035, 50036, 50037, 50038, 50039, 50040, 50041, 50042, 50043, 50044, 50045, 50046, 50047, 50048, 50049, 50050, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50063, 50064, 50065, 50066, 50067, 50068, 50069, 50070, 50071, 50072, 50073, 50074, 50075, 50076, 50077, 50078, 50080 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |
| `put_can_in_cabinet` | 82 | train | kitchenl_clean | 50000, 50001, 50002, 50003, 50004, 50005, 50006, 50007, 50008, 50009, 50010, 50011, 50012, 50013, 50014, 50015, 50016, 50017, 50018, 50019, 50020, 50021, 50022, 50023, 50024, 50025, 50026, 50027, 50028, 50029, 50030, 50031, 50032, 50033, 50034, 50035, 50036, 50037, 50038, 50039, 50040, 50041, 50042, 50043, 50044, 50045, 50046, 50047, 50048, 50049, 50050, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50063, 50064, 50065, 50066, 50067, 50068, 50069, 50070, 50071, 50072, 50073, 50074, 50075, 50076, 50077, 50078, 50079, 50080, 50082 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |
| `put_cup_on_coaster` | 79 | train | study_clean | 50000, 50001, 50002, 50003, 50004, 50005, 50006, 50007, 50008, 50009, 50010, 50011, 50012, 50013, 50014, 50015, 50016, 50017, 50018, 50019, 50020, 50021, 50022, 50023, 50024, 50025, 50026, 50027, 50028, 50029, 50030, 50031, 50032, 50033, 50034, 50035, 50036, 50037, 50038, 50039, 50040, 50041, 50042, 50043, 50044, 50045, 50046, 50047, 50048, 50049, 50050, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50063, 50064, 50065, 50066, 50067, 50068, 50069, 50070, 50071, 50072, 50073, 50074, 50075, 50076, 50077, 50080 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |
| `put_milktea_on_shelf` | 81 | train | office_clean | 50000, 50001, 50002, 50003, 50004, 50005, 50006, 50007, 50008, 50009, 50010, 50011, 50012, 50013, 50014, 50015, 50016, 50017, 50018, 50019, 50020, 50021, 50022, 50023, 50024, 50025, 50026, 50027, 50028, 50029, 50030, 50031, 50032, 50033, 50034, 50035, 50036, 50037, 50038, 50039, 50040, 50041, 50042, 50043, 50044, 50045, 50046, 50047, 50048, 50049, 50050, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50063, 50064, 50065, 50066, 50067, 50068, 50069, 50070, 50071, 50072, 50073, 50074, 50075, 50076, 50077, 50078, 50081, 50085 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |
| `put_mouse_on_pad` | 83 | train | office_clean | 50000, 50001, 50002, 50003, 50004, 50005, 50006, 50007, 50008, 50009, 50010, 50011, 50012, 50013, 50014, 50015, 50016, 50017, 50018, 50019, 50020, 50021, 50022, 50023, 50024, 50025, 50026, 50027, 50028, 50029, 50030, 50031, 50032, 50033, 50034, 50035, 50036, 50037, 50038, 50039, 50040, 50041, 50042, 50043, 50044, 50045, 50046, 50047, 50048, 50049, 50050, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50063, 50064, 50065, 50066, 50067, 50068, 50069, 50070, 50071, 50072, 50073, 50074, 50075, 50076, 50077, 50078, 50079, 50080, 50081, 50083 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |
| `put_phone_on_holder` | 82 | train | office_clean | 50000, 50001, 50002, 50003, 50004, 50005, 50006, 50007, 50008, 50009, 50010, 50011, 50012, 50013, 50014, 50015, 50016, 50017, 50018, 50019, 50020, 50021, 50022, 50023, 50024, 50025, 50026, 50027, 50028, 50029, 50030, 50031, 50032, 50033, 50034, 50035, 50036, 50037, 50038, 50039, 50040, 50041, 50042, 50043, 50044, 50045, 50046, 50047, 50048, 50049, 50050, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50063, 50064, 50065, 50066, 50067, 50068, 50069, 50070, 50071, 50072, 50073, 50074, 50075, 50076, 50077, 50079, 50080, 50081, 50084 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |
| `put_stapler_next_to_mouse` | 81 | train | office_clean | 50000, 50001, 50002, 50003, 50004, 50005, 50006, 50007, 50008, 50009, 50010, 50011, 50012, 50013, 50014, 50015, 50016, 50017, 50018, 50019, 50020, 50021, 50022, 50023, 50024, 50025, 50026, 50027, 50028, 50029, 50030, 50031, 50032, 50033, 50034, 50035, 50036, 50037, 50038, 50039, 50040, 50041, 50042, 50043, 50044, 50045, 50046, 50047, 50048, 50049, 50050, 50051, 50052, 50053, 50054, 50055, 50056, 50057, 50058, 50059, 50060, 50061, 50062, 50063, 50064, 50065, 50066, 50067, 50068, 50069, 50070, 50071, 50072, 50073, 50074, 50075, 50076, 50077, 50078, 50080, 50081 | [RoboPRO @ `2a1adee`](https://github.com/EAI-RSM/RoboPRO/commit/2a1adee49dbaebe06379398745233b8f0b43c85f) |

## Contents

| | |
|---|---|
| tasks | `drop_apple_in_bin_ks`, `move_cup_put_pen_in_cup`, `move_hamburger_onto_plate_ks`, `move_pen_to_box`, `place_bowl_in_dishrack_ks`, `put_bottle_in_basket`, `put_bottle_in_fridge`, `put_can_in_cabinet`, `put_cup_on_coaster`, `put_milktea_on_shelf`, `put_mouse_on_pad`, `put_phone_on_holder`, `put_stapler_next_to_mouse` |
| scene seeds | 50000–50098 |
| search | `branch_once`, fan of 5, horizon 12 |
| policy | `roboresearch_policy` — None @ 0 |
| cameras | countertop_camera, right_camera, left_camera |
| action chunk | 50 steps |

| table | rows | files | columns |
|---|---|---|---|
| `nodes` | 39,016 | 1037 | 10 |
| `steps` | 1,898,950 | 1037 | 5 |

Outcomes, best to worst: `hard_success` solved it cleanly, `soft_success` solved it after
a collision, `soft_failure` missed, `hard_failure` missed and collided. `terminal` says
whether the episode had ended when the outcome was read — `tier` is an outcome only where
it is true, and only those are counted here.

| outcome | branches |
|---|---|
| `hard_success` | 3,299 |
| `soft_success` | 29 |
| `soft_failure` | 1,761 |
| `hard_failure` | 96 |

## Loading it

```python
from datasets import load_dataset
train = load_dataset("mahgoobi/scoring_data", "nodes", split="train")   # the collection seeds
```

The library's splits ARE the `split` column of `meta/searches`: the frontmatter above
names each run's shard under the block that column puts it in, so the two cannot drift.
Only the blocks this repo actually holds are declared.

Every node carries its own state — poses, the robot's command, and one JPEG per camera —
so `nodes` alone answers most questions. `steps` is what happened between two nodes.
There is no video: `rewind video` builds one from these frames when you want to watch a
branch.

Data is partitioned as `data/<table>/task=<task>/<search_id>.parquet`, so one task is one
directory:

```python
from huggingface_hub import snapshot_download
snapshot_download("mahgoobi/scoring_data", repo_type="dataset",
                  allow_patterns=["meta/**", "data/*/task=drop_apple_in_bin_ks/*"])
```

Each run's config is stored verbatim at `meta/configs/<search_id>.yml`, so any run can be
repeated from the record itself.

Full format, and everything else: [https://github.com/EAI-RSM/rewind](https://github.com/EAI-RSM/rewind).