Awesome
ServiceNow completed its acquisition of Element AI on January 8, 2021. All references to Element AI in the materials that are part of this project should refer to ServiceNow.
Probing Learning Algorithms with Synthetic Datasets
Description
This repository contains the code for reproducing experiments in [1].
To use the Synbols tool for generating new datasets, please visit https://github.com/ElementAI/synbols
Pytorch Dataset Quick Setup
from pytorch_examples.datasets import Synbols
from torchvision import transforms as tt
dataset_path = "./"
dataset_name = "default_n=100000_2020-Oct-19.h5py"
synbols = Synbols(args.data_path,
dataset_name=args.dataset)
train_dataset = synbols.get_split('train', tt.ToTensor())
val_dataset = synbols.get_split('val', tt.ToTensor())
For a complete example run ./pytorch_examples/minimal_classification.py
from the root folder of this project:
python -m pytorch_examples.minimal_classification
It should reach >70% accuracy.
Bibliography
[1] Lacoste, A., Rodríguez, P., Branchaud-Charron, F., Atighehchian, P., Caccia, M., Laradji, I., Drouin, A., Craddock, M., Charlin, L. and Vázquez, D., 2020. Synbols: Probing Learning Algorithms with Synthetic Datasets.