autoaug documentation

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Introduction:

• Installation
• Introduction to the Automatic Image Augmentation Problem Setting

Tutorials (for accomplishing common goals):

• How to use the AaLearner class to find a good augmentation for an image dataset
  • Necessary Imports
  • Defining the problem setting
  • Defining our auto-augmentation learner
  • Training the learner
  • Viewing the results
  • Using the results
• How to apply AutoAugment image augmentation policies to a torchvision.datasets.VisionDataset object

Explanations (of the theory behind the learners):

• Introduction to the Automatic Image Augmentation Problem Setting
• The Theory Behind the Learners
  • Random Search Learner (RsLearner)
  • Genetic Learner (GenLearner)
  • Evolutionary Learner (EvoLearner)
  • GRU Learner (GruLearner)
  • UCB Learner (UcbLearner)

API References (Technical specifications):

• AutoAugment learners
  • autoaug.autoaugment_learners.AaLearner
  • autoaug.autoaugment_learners.EvoLearner
  • autoaug.autoaugment_learners.GenLearner
  • autoaug.autoaugment_learners.GruLearner
  • autoaug.autoaugment_learners.RsLearner
  • autoaug.autoaugment_learners.UcbLearner