Syne Tune

Getting Started

  • Installation
  • What Is Hyperparameter Optimization?
  • First Example
  • Supported HPO Methods
  • Security
  • Citing Syne Tune
  • License

Next Steps

  • Frequently Asked Questions
  • Examples

Tutorials

  • Basics of Syne Tune
  • How to Choose a Configuration Space
  • Using the Built-in Schedulers
  • Multi-Fidelity Hyperparameter Optimization
  • How to Contribute a New Scheduler
  • PASHA: Efficient HPO and NAS with Progressive Resource Allocation
  • Using Syne Tune for Transfer Learning

API docs

  • API Reference
    • benchmarking package
    • setup module
    • syne_tune package
      • StoppingCriterion
      • Tuner
      • Reporter
      • Subpackages
        • syne_tune.backend package
        • syne_tune.blackbox_repository package
        • syne_tune.callbacks package
        • syne_tune.experiments package
        • syne_tune.optimizer package
        • syne_tune.utils package
      • Submodules
Syne Tune
  • API Reference
  • syne_tune package
  • syne_tune.optimizer package
  • syne_tune.optimizer.schedulers package
  • syne_tune.optimizer.schedulers.searchers package
  • syne_tune.optimizer.schedulers.searchers.bayesopt package
  • syne_tune.optimizer.schedulers.searchers.bayesopt.models package
  • syne_tune.optimizer.schedulers.searchers.bayesopt.models.cost package
  • View page source

syne_tune.optimizer.schedulers.searchers.bayesopt.models.cost package

Submodules

  • syne_tune.optimizer.schedulers.searchers.bayesopt.models.cost.cost_model module
    • CostValue
      • CostValue.c0
      • CostValue.c1
    • CostModel
      • CostModel.cost_metric_name
      • CostModel.update()
      • CostModel.resample()
      • CostModel.sample_joint()
      • CostModel.event_time()
      • CostModel.predict_times()
  • syne_tune.optimizer.schedulers.searchers.bayesopt.models.cost.linear_cost_model module
  • syne_tune.optimizer.schedulers.searchers.bayesopt.models.cost.sklearn_cost_model module
    • ScikitLearnCostModel
      • ScikitLearnCostModel.transform_dataset()
      • ScikitLearnCostModel.fit_regressor()
      • ScikitLearnCostModel.predict_c1_values()
    • UnivariateSplineCostModel
      • UnivariateSplineCostModel.transform_dataset()
      • UnivariateSplineCostModel.fit_regressor()
      • UnivariateSplineCostModel.predict_c1_values()
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