Welcome. This code representation is related to the Active Word Learning through Self-supervision study.
If you use this work please cite us as:
Gelderloos, L., Mahmoudi Kamelabad, A., & Alishahi, A. (2020). Active Word Learning through Self-supervision. In S. Denison, M. Mack, Y. Xu, & B. C. Armstrong (Eds.), Proceedings for the 42nd Annual Meeting of the Cognitive Science Society (pp. 1050–1056). Cognitive Science Society.
Alternatively you can download the bib file here as well:
{img_id:(str): {
obj_id:(str): {
'bnbox': a list of four coordinations,
'word': the linguistic representation of the object
},
},
Regular data (dictionary with all images and their object ids, corresponding words).
a tensor of word indexes.
The shape of input to main.py
< Number of Batches: int > < Learning Rate: float > < Curiosity Setting: str > < Seed >
- Number of Batches: int, (default= 40)
- Learning Rate: [.1, .01, .001, .0001, .00001] : float
- Curiosity Setting: ["curious", "plasticity", "sn", "random"], (sn: Subjective Novelty)
- Seed: The ones used to run the experiment: [123, 234, 345, 456, 567, 678, 789, 890, 901, 12, 23, 34, 45, 56, 67, 78, 89, 90, 1, 100]
In order to manage constants I made the class UniversalConstants
for constants in toolbox.py
. All the code files should import this class and make an object of it with specific name uc
.
Here is how you do it:
from toolbox import UniversalConstants
uc = UniversalConstants()
please feel free to raise up issue in case you face problems.