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BabyARC

Baby Abstract Reasoning Corpus (BabyARC) dataset engine, for generating grid-world-based abstract reasoning tasks on a large scale. BabyARC's name is inspired by the Abstract Reasoning Corpus (ARC). The goal of this dataset engine is to generate concept, relation and reasoning pretraining data source for solving the ARC corpus.

Contents

Example

Here, we show concept and relation canvases can be generated using BabyARC:

Here, we show some simplified abstract reasoning tasks can be generated using BabyARC:

Usage

# generating concepts and relation canvases.
from code.dataset.dataset import *
demo_dataset = \
    BabyARCDataset(pretrained_obj_cache=os.path.join(get_root_dir(), 'concept_env/datasets/arc_objs.pt'),
                   save_directory="./BabyARCDataset/", 
                   object_limit=1, noise_level=0, 
                   canvas_size=8) # canvas makes w=h canvas

# Inplace object placement.
canvas_dict = demo_dataset.sample_single_canvas_by_core_edges(
    OrderedDict(
        [(('obj_0', 'obj_1'), 'SameColor'),
         (('obj_0', 'obj_2'), 'IsTouch')]
    ), 
    color_avail=[1,2,3],
    rainbow_prob=0.0,
    allow_connect=True, 
)