cifar100

CIFAR-100 Example

This is a simple example showing how to use the AUMCalculator and DatasetWithIndex in a training script. This script trains Resnet-34 on the CIFAR-100 dataset. At training completion, the aum artifacts will be located in the output directory. The samples with the lowest aum values are most likely mislabeled.

Requirements

• pytorch >= 1.3
• torchvision >= 0.4
• numpy
• pandas
• aum
• tensorboard

Usage

You can call the script as follows:

# for the compressed version of the AUMCalculator
python train.py

# For the uncompressed version of the AUMCalculator
python train.py --detailed-aum

The script will run without any specified arguments as all have defaults, but to see all available arguments:

python train.py --help