Fork Changes

  • Refactored code
  • Added dependencies in environment.txt (but don't use it for creating new env it contains dependencies carried over from a last project)
  • Added dropout layers + config and weight decay.
  • Added a script to generate commands multiple configs
  • Removed wandb loggers and added custom logger
  • Added class imbalanced training
  • Added Curriculum learning with pretrained ResNet18

Example config

python train.py --batchsize 1028 --workers 2 --epochs 80 --opt adam --arch 'mlp[16384,16384,512]' --reg wd --iid

See exps.sh more details.

deep-bootstrap-code

Code for the paper The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers.

The main training code is here, and a sample configuration of hyperparameter sweep (using Caliban) is here.

The CIFAR-5m dataset is released at: https://github.com/preetum/cifar5m