syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.hypertune package

Submodules

• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.hypertune.gp_model module
  • HyperTuneDistributionArguments
    • HyperTuneDistributionArguments.num_samples
    • HyperTuneDistributionArguments.num_brackets
  • HyperTuneModelMixin
    • HyperTuneModelMixin.hypertune_bracket_distribution()
    • HyperTuneModelMixin.hypertune_ensemble_distribution()
    • HyperTuneModelMixin.fit_distributions()
  • HyperTuneIndependentGPModel
    • HyperTuneIndependentGPModel.create_likelihood()
    • HyperTuneIndependentGPModel.hypertune_ensemble_distribution()
    • HyperTuneIndependentGPModel.fit()
  • HyperTuneJointGPModel
    • HyperTuneJointGPModel.create_likelihood()
    • HyperTuneJointGPModel.hypertune_ensemble_distribution()
    • HyperTuneJointGPModel.fit()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.hypertune.likelihood module
  • HyperTuneIndependentGPMarginalLikelihood
    • HyperTuneIndependentGPMarginalLikelihood.ensemble_distribution
    • HyperTuneIndependentGPMarginalLikelihood.set_ensemble_distribution()
    • HyperTuneIndependentGPMarginalLikelihood.get_posterior_state()
  • HyperTuneJointGPMarginalLikelihood
    • HyperTuneJointGPMarginalLikelihood.ensemble_distribution
    • HyperTuneJointGPMarginalLikelihood.set_ensemble_distribution()
    • HyperTuneJointGPMarginalLikelihood.get_posterior_state()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.hypertune.posterior_state module
  • assert_ensemble_distribution()
  • HyperTuneIndependentGPPosteriorState
    • HyperTuneIndependentGPPosteriorState.predict()
    • HyperTuneIndependentGPPosteriorState.sample_marginals()
    • HyperTuneIndependentGPPosteriorState.sample_joint()
    • HyperTuneIndependentGPPosteriorState.backward_gradient()
  • HyperTuneJointGPPosteriorState
    • HyperTuneJointGPPosteriorState.predict()
    • HyperTuneJointGPPosteriorState.sample_marginals()
    • HyperTuneJointGPPosteriorState.sample_joint()
    • HyperTuneJointGPPosteriorState.backward_gradient()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.hypertune.utils module
  • ExtendFeaturesByResourceMixin
    • ExtendFeaturesByResourceMixin.extend_features_by_resource()
  • PosteriorStateClampedResource
    • PosteriorStateClampedResource.num_data
    • PosteriorStateClampedResource.num_features
    • PosteriorStateClampedResource.num_fantasies
    • PosteriorStateClampedResource.neg_log_likelihood()
    • PosteriorStateClampedResource.predict()
    • PosteriorStateClampedResource.sample_marginals()
    • PosteriorStateClampedResource.sample_joint()
    • PosteriorStateClampedResource.backward_gradient()
  • MeanFunctionClampedResource
    • MeanFunctionClampedResource.param_encoding_pairs()
    • MeanFunctionClampedResource.get_params()
    • MeanFunctionClampedResource.set_params()
    • MeanFunctionClampedResource.forward()
  • KernelFunctionClampedResource
    • KernelFunctionClampedResource.param_encoding_pairs()
    • KernelFunctionClampedResource.get_params()
    • KernelFunctionClampedResource.set_params()
    • KernelFunctionClampedResource.diagonal()
    • KernelFunctionClampedResource.diagonal_depends_on_X()
    • KernelFunctionClampedResource.forward()
  • GaussProcPosteriorStateAndRungLevels
    • GaussProcPosteriorStateAndRungLevels.poster_state
    • GaussProcPosteriorStateAndRungLevels.num_data
    • GaussProcPosteriorStateAndRungLevels.num_features
    • GaussProcPosteriorStateAndRungLevels.num_fantasies
    • GaussProcPosteriorStateAndRungLevels.neg_log_likelihood()
    • GaussProcPosteriorStateAndRungLevels.predict()
    • GaussProcPosteriorStateAndRungLevels.sample_marginals()
    • GaussProcPosteriorStateAndRungLevels.sample_joint()
    • GaussProcPosteriorStateAndRungLevels.backward_gradient()
    • GaussProcPosteriorStateAndRungLevels.rung_levels
  • hypertune_ranking_losses()
  • number_supported_levels_and_data_highest_level()