robustness
stable
  • Training and evaluating networks via command line
    • Training a standard (nonrobust) model
    • Training a robust model (adversarial training)
    • Evaluating trained models
    • Examples
      • Training a non-robust ResNet-18 for the CIFAR dataset:
      • Training a robust ResNet-50 for the Restricted-ImageNet dataset:
    • Reading and analyzing training results
  • Input manipulation with pre-trained models
    • Generating Untargeted Adversarial Examples
    • Generating Targeted Adversarial Examples
    • Custom Input Manipulation (e.g. Representation Inversion)
      • Changing optimization methods
    • Advanced usage
      • Gradient Estimation/NES
      • Custom optimization methods
  • Using robustness as a general training library (Part 1: Getting started)
    • Step 1: Imports
    • Step 2: Dealing with arguments
      • Step 2.1: Setting up command-line args
      • Step 2.2: Sanity checks and defaults
    • Step 3: Creating the model, dataset, and loader
    • Step 4: Training the model
  • Using robustness as a general training library (Part 2: Customizing training)
    • Training networks with custom loss functions
    • Training networks with custom data loaders
      • Using LambdaLoader to train with label noise
      • Using TransformedLoader to train with random labels
    • Training networks with custom logging
    • Training on custom datasets
    • Training with custom architectures
  • Creating a custom dataset by superclassing ImageNet
    • Requirements/Setup
    • Basic Usage: Loading Pre-Packaged ImageNet-based Datasets
    • Advanced Usage (Making Custom Datasets) Part 1: Browsing the WordNet Hierarchy
    • Advanced Usage (Making Custom Datasets) Part 2: Making the Datasets
  • Creating BREEDS subpopulation shift benchmarks
    • Requirements/Setup
    • Part 1: Browsing through the Class Hierarchy
    • Part 2: Creating BREEDS Datasets
    • Part 3: Loading in-built BREEDS Datasets
  • CHANGELOG
    • robustness 1.2
    • robustness 1.1.post2
    • robustness 1.1
  • API Reference
    • robustness.attack_steps module
    • robustness.attacker module
    • robustness.data_augmentation module
    • robustness.datasets module
    • robustness.defaults module
    • robustness.loaders module
    • robustness.main module
    • robustness.model_utils module
    • robustness.train module
    • robustness.tools package
      • Submodules
        • robustness.tools.constants module
        • robustness.tools.folder module
        • robustness.tools.helpers module
        • robustness.tools.label_maps module
        • robustness.tools.vis_tools module
        • robustness.tools.breeds_helpers module
      • Module contents
robustness
  • Docs »
  • API Reference »
  • robustness.tools package
  • Edit on GitHub

robustness.tools package¶

Submodules¶

  • robustness.tools.constants module
  • robustness.tools.folder module
  • robustness.tools.helpers module
  • robustness.tools.label_maps module
  • robustness.tools.vis_tools module
  • robustness.tools.breeds_helpers module

Module contents¶

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