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---
dataset_info:
features:
- name: images
list:
image:
decode: false
- name: image_group_id
dtype: string
- name: qa
list:
- name: inputs
dtype: string
- name: choices_list
list: string
- name: labels
dtype: int64
- name: metadata
dtype: string
splits:
- name: train
num_bytes: 1073898773
num_examples: 92114
- name: validation
num_bytes: 1087431
num_examples: 100
download_size: 1074000270
dataset_size: 1074986204
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
language:
- en
license: apache-2.0
source_datasets: []
task_categories:
- multiple-choice
- visual-question-answering
tags:
- decision-model
- procedural
---
# visgym-mcq
Balanced static VisGym: mazes, equation repair, stick rotation and block legality.
One mirror, with 25,000 training and 25 held-out examples per family at the
default limits. Every choice is verified against its instance. Fresh native
procedural images only; no photographic assets or published benchmark rows.
Metadata records family, seed, geometry and verification. Apache-2.0.
Original data: [original distribution](https://github.com/visgym/visgym). Repackaged as parquet for [tasksource](https://github.com/sileod/tasksource) by [scripts/repackage_dataset/procedural/balanced_visgym.py](https://github.com/sileod/tasksource/blob/main/scripts/repackage_dataset/procedural/balanced_visgym.py#L43).
[Conversion provenance](provenance.json): source revisions, hashes, configuration and exclusions.
[Upstream asset credits and licenses](asset-notices.json) accompany the original rendered images.
The training split contains **100,000 QAs**, 25,000 per family, stored in 92,114 image groups. Validation has 100 QAs, 25 per family. Images shared by several questions are stored once; `load_task("visgym/mcq", vision=True)` exposes the flattened examples. Both splits are shuffled with seed 42.