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PyHopper 0.0.1 documentation
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  • Quickstart
  • PyHopper’s Philosophy
  • Code Recipes
    • Array parameters
    • Tracking sampled hyperparameters
    • Discontinuing unpromising candidates during evaluation
    • Dealing with NaNs and exceptions
    • Tracking with Tensorboard
    • Tracking with MLflow and Weights & Biases
    • Multiple validation splits
    • Custom sampling strategies
    • Custom parameter types
    • Custom Callbacks
  • Examples
    • MLP with TensorFlow on MNIST
    • CIFAR-10 with PyTorch and a ResNet34
    • Gradient-free RL with Cartpole-v1
    • Travelling Salesman Problem with PyHopper
  • API Reference
    • Search Object
    • Parameters
    • Utilities
    • Callbacks
    • Early Cancelers

Examples¶

  • MLP with TensorFlow on MNIST
  • CIFAR-10 with PyTorch and a ResNet34
  • Gradient-free RL with Cartpole-v1
  • Travelling Salesman Problem with PyHopper
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MLP with TensorFlow on MNIST
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Custom Callbacks
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