Representations in Neural Networks

• See the VDL page for more information.
• See also the GitHub repository.

Contributors: Dan Saunders (djsaunde@cs.umass.edu), Ryan McCormick (rmccorm4@binghamton.edu)

Setting things up

Clone the GitHub repository in a directory of your choosing using git clone https://github.com/djsaunde/rinns_python.git. This will create a directory named rinns_python inside of your current directory. This statement should be run in a terminal in *nix or Mac systems, or in a Git Bash shell on Windows.

Consult requirements.txt for the packages which the project code depends on. If you have pip installed (which you should), use pip install -r requirements.txt to recursively install the packages listed.

Training

CIFAR-10

Navigate to the 'cifar10' folder

Run 'train_cifar10_lenet.py'

• python train_cifar10_lenet.py

Optional flags are included in the code for your preferences and hardware capability

• --hardware=(string)
  • 'cpu' (Default)
  • 'gpu'
  • '2gpu'
• --batch_size=(int)
  • 100 (Default)
• --num_epochs=(int)
  • 25 (Default)
• --best_criterion=(string)
  • 'val_loss' (Default)
  • 'val_acc'
  • 'train_loss'
  • 'train_acc'

Tiny-Imagenet

Navigate to the 'tiny-imagenet' folder

Run 'train_tiny_imagenet.py'

• python train_tiny_imagenet.py

Optional flags

• --hardware
• --batch_size
• --num_epochs
• --best_criterion
• --num_classes=(int)
  • 200 (Default)
  • 1-200
• --data_augmentation=(bool)
  • False (Default)
  • True