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

exception syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.SliceException

Bases: Exception

Subpackages

• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.hypertune package
  • Submodules
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.hypertune.gp_model module
      • HyperTuneDistributionArguments
      • HyperTuneModelMixin
      • HyperTuneIndependentGPModel
      • HyperTuneJointGPModel
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.hypertune.likelihood module
      • HyperTuneIndependentGPMarginalLikelihood
      • HyperTuneJointGPMarginalLikelihood
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.hypertune.posterior_state module
      • assert_ensemble_distribution()
      • HyperTuneIndependentGPPosteriorState
      • HyperTuneJointGPPosteriorState
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.hypertune.utils module
      • ExtendFeaturesByResourceMixin
      • PosteriorStateClampedResource
      • MeanFunctionClampedResource
      • KernelFunctionClampedResource
      • GaussProcPosteriorStateAndRungLevels
      • hypertune_ranking_losses()
      • number_supported_levels_and_data_highest_level()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.independent package
  • Submodules
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.independent.gpind_model module
      • IndependentGPPerResourceModel
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.independent.likelihood module
      • IndependentGPPerResourceMarginalLikelihood
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.independent.posterior_state module
      • IndependentGPPerResourcePosteriorState
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.kernel package
  • KernelFunction
    • KernelFunction.dimension
    • KernelFunction.diagonal()
    • KernelFunction.diagonal_depends_on_X()
  • Matern52
    • Matern52.ARD
    • Matern52.forward()
    • Matern52.diagonal()
    • Matern52.diagonal_depends_on_X()
    • Matern52.param_encoding_pairs()
    • Matern52.get_covariance_scale()
    • Matern52.set_covariance_scale()
    • Matern52.get_params()
    • Matern52.set_params()
  • ExponentialDecayResourcesKernelFunction
    • ExponentialDecayResourcesKernelFunction.forward()
    • ExponentialDecayResourcesKernelFunction.diagonal()
    • ExponentialDecayResourcesKernelFunction.diagonal_depends_on_X()
    • ExponentialDecayResourcesKernelFunction.param_encoding_pairs()
    • ExponentialDecayResourcesKernelFunction.mean_function()
    • ExponentialDecayResourcesKernelFunction.get_params()
    • ExponentialDecayResourcesKernelFunction.set_params()
  • ExponentialDecayResourcesMeanFunction
    • ExponentialDecayResourcesMeanFunction.forward()
    • ExponentialDecayResourcesMeanFunction.param_encoding_pairs()
    • ExponentialDecayResourcesMeanFunction.get_params()
    • ExponentialDecayResourcesMeanFunction.set_params()
  • FabolasKernelFunction
    • FabolasKernelFunction.forward()
    • FabolasKernelFunction.diagonal()
    • FabolasKernelFunction.diagonal_depends_on_X()
    • FabolasKernelFunction.param_encoding_pairs()
    • FabolasKernelFunction.get_params()
    • FabolasKernelFunction.set_params()
  • ProductKernelFunction
    • ProductKernelFunction.forward()
    • ProductKernelFunction.diagonal()
    • ProductKernelFunction.diagonal_depends_on_X()
    • ProductKernelFunction.param_encoding_pairs()
    • ProductKernelFunction.get_params()
    • ProductKernelFunction.set_params()
  • FreezeThawKernelFunction
    • FreezeThawKernelFunction.forward()
    • FreezeThawKernelFunction.diagonal()
    • FreezeThawKernelFunction.diagonal_depends_on_X()
    • FreezeThawKernelFunction.param_encoding_pairs()
    • FreezeThawKernelFunction.mean_function()
    • FreezeThawKernelFunction.get_params()
    • FreezeThawKernelFunction.set_params()
  • FreezeThawMeanFunction
    • FreezeThawMeanFunction.forward()
    • FreezeThawMeanFunction.param_encoding_pairs()
    • FreezeThawMeanFunction.get_params()
    • FreezeThawMeanFunction.set_params()
  • CrossValidationMeanFunction
    • CrossValidationMeanFunction.forward()
    • CrossValidationMeanFunction.param_encoding_pairs()
    • CrossValidationMeanFunction.get_params()
    • CrossValidationMeanFunction.set_params()
  • CrossValidationKernelFunction
    • CrossValidationKernelFunction.forward()
    • CrossValidationKernelFunction.diagonal()
    • CrossValidationKernelFunction.diagonal_depends_on_X()
    • CrossValidationKernelFunction.param_encoding_pairs()
    • CrossValidationKernelFunction.mean_function()
    • CrossValidationKernelFunction.get_params()
    • CrossValidationKernelFunction.set_params()
  • RangeKernelFunction
    • RangeKernelFunction.forward()
    • RangeKernelFunction.diagonal()
    • RangeKernelFunction.diagonal_depends_on_X()
    • RangeKernelFunction.param_encoding_pairs()
    • RangeKernelFunction.get_params()
    • RangeKernelFunction.set_params()
  • Submodules
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.kernel.base module
      • KernelFunction
      • SquaredDistance
      • Matern52
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.kernel.cross_validation module
      • decode_resource_values()
      • CrossValidationKernelFunction
      • CrossValidationMeanFunction
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.kernel.exponential_decay module
      • ExponentialDecayResourcesKernelFunction
      • ExponentialDecayResourcesMeanFunction
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.kernel.fabolas module
      • FabolasKernelFunction
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.kernel.freeze_thaw module
      • FreezeThawKernelFunction
      • FreezeThawMeanFunction
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.kernel.product_kernel module
      • ProductKernelFunction
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.kernel.range_kernel module
      • RangeKernelFunction
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.learncurve package
  • Submodules
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.learncurve.freeze_thaw module
      • ZeroKernel
      • ZeroMean
      • ExponentialDecayBaseKernelFunction
      • logdet_cholfact_cov_resource()
      • resource_kernel_likelihood_precomputations()
      • resource_kernel_likelihood_computations()
      • resource_kernel_likelihood_slow_computations()
      • predict_posterior_marginals_extended()
      • sample_posterior_joint()
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.learncurve.gpiss_model module
      • GaussianProcessLearningCurveModel
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.learncurve.issm module
      • prepare_data()
      • prepare_data_with_pending()
      • issm_likelihood_precomputations()
      • issm_likelihood_computations()
      • posterior_computations()
      • predict_posterior_marginals()
      • sample_posterior_marginals()
      • predict_posterior_marginals_extended()
      • sample_posterior_joint()
      • issm_likelihood_slow_computations()
      • update_posterior_state()
      • update_posterior_pvec()
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.learncurve.likelihood module
      • GaussAdditiveMarginalLikelihood
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.learncurve.model_params module
      • ISSModelParameters
      • IndependentISSModelParameters
    • syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.learncurve.posterior_state module
      • GaussProcAdditivePosteriorState
      • IncrementalUpdateGPAdditivePosteriorState
      • GaussProcISSMPosteriorState
      • GaussProcExpDecayPosteriorState

Submodules

• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.constants module
  • OptimizationConfig
    • OptimizationConfig.lbfgs_tol
    • OptimizationConfig.lbfgs_maxiter
    • OptimizationConfig.verbose
    • OptimizationConfig.n_starts
  • MCMCConfig
    • MCMCConfig.n_samples
    • MCMCConfig.n_burnin
    • MCMCConfig.n_thinning
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.custom_op module
  • AddJitterOp()
  • flatten_and_concat()
  • cholesky_factorization()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.distribution module
  • Distribution
    • Distribution.negative_log_density()
  • Gamma
    • Gamma.negative_log_density()
  • Uniform
    • Uniform.negative_log_density()
  • Normal
    • Normal.negative_log_density()
  • LogNormal
    • LogNormal.negative_log_density()
  • Horseshoe
    • Horseshoe.negative_log_density()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.gluon module
  • Block
    • Block.prefix
    • Block.name
    • Block.name_scope()
    • Block.params
    • Block.collect_params()
    • Block.register_child()
    • Block.apply()
    • Block.initialize()
    • Block.hybridize()
    • Block.cast()
    • Block.forward()
    • Block.hybrid_forward()
  • Parameter
    • Parameter.grad_req
    • Parameter.dtype
    • Parameter.shape
    • Parameter.initialize()
    • Parameter.reset_ctx()
    • Parameter.set_data()
    • Parameter.data()
    • Parameter.list_data()
    • Parameter.grad()
    • Parameter.list_grad()
    • Parameter.list_ctx()
    • Parameter.zero_grad()
    • Parameter.cast()
  • ParameterDict
    • ParameterDict.items()
    • ParameterDict.keys()
    • ParameterDict.values()
    • ParameterDict.prefix
    • ParameterDict.get()
    • ParameterDict.update()
    • ParameterDict.initialize()
    • ParameterDict.reset_ctx()
    • ParameterDict.list_ctx()
    • ParameterDict.setattr()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.gluon_blocks_helpers module
  • ConstantPositiveVector
    • ConstantPositiveVector.forward()
    • ConstantPositiveVector.set()
    • ConstantPositiveVector.get()
    • ConstantPositiveVector.get_box_constraints_internal()
    • ConstantPositiveVector.log_parameters()
    • ConstantPositiveVector.get_parameters()
    • ConstantPositiveVector.switch_updating()
    • ConstantPositiveVector.has_regularizer()
    • ConstantPositiveVector.eval_regularizer()
  • PositiveScalarEncoding
    • PositiveScalarEncoding.get()
    • PositiveScalarEncoding.decode()
  • IdentityScalarEncoding
    • IdentityScalarEncoding.get()
    • IdentityScalarEncoding.decode()
  • LogarithmScalarEncoding
    • LogarithmScalarEncoding.get()
    • LogarithmScalarEncoding.decode()
  • unwrap_parameter()
  • encode_unwrap_parameter()
  • param_to_pretty_string()
  • register_parameter()
  • create_encoding()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.gp_model module
  • GaussianProcessModel
    • GaussianProcessModel.random_state
    • GaussianProcessModel.states
    • GaussianProcessModel.fit()
    • GaussianProcessModel.recompute_states()
    • GaussianProcessModel.predict()
    • GaussianProcessModel.multiple_targets()
    • GaussianProcessModel.sample_marginals()
    • GaussianProcessModel.sample_joint()
  • GaussianProcessOptimizeModel
    • GaussianProcessOptimizeModel.states
    • GaussianProcessOptimizeModel.likelihood
    • GaussianProcessOptimizeModel.fit()
    • GaussianProcessOptimizeModel.recompute_states()
    • GaussianProcessOptimizeModel.get_params()
    • GaussianProcessOptimizeModel.set_params()
    • GaussianProcessOptimizeModel.reset_params()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.gp_regression module
  • GaussianProcessRegression
    • GaussianProcessRegression.likelihood
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.gpr_mcmc module
  • GPRegressionMCMC
    • GPRegressionMCMC.states
    • GPRegressionMCMC.number_samples
    • GPRegressionMCMC.fit()
    • GPRegressionMCMC.recompute_states()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.likelihood module
  • MarginalLikelihood
    • MarginalLikelihood.get_posterior_state()
    • MarginalLikelihood.forward()
    • MarginalLikelihood.param_encoding_pairs()
    • MarginalLikelihood.box_constraints_internal()
    • MarginalLikelihood.get_noise_variance()
    • MarginalLikelihood.get_params()
    • MarginalLikelihood.set_params()
    • MarginalLikelihood.reset_params()
    • MarginalLikelihood.data_precomputations()
    • MarginalLikelihood.on_fit_start()
  • GaussianProcessMarginalLikelihood
    • GaussianProcessMarginalLikelihood.assert_data_entries()
    • GaussianProcessMarginalLikelihood.get_posterior_state()
    • GaussianProcessMarginalLikelihood.forward()
    • GaussianProcessMarginalLikelihood.param_encoding_pairs()
    • GaussianProcessMarginalLikelihood.get_noise_variance()
    • GaussianProcessMarginalLikelihood.get_params()
    • GaussianProcessMarginalLikelihood.set_params()
    • GaussianProcessMarginalLikelihood.on_fit_start()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.mean module
  • MeanFunction
    • MeanFunction.param_encoding_pairs()
    • MeanFunction.get_params()
    • MeanFunction.set_params()
  • ScalarMeanFunction
    • ScalarMeanFunction.forward()
    • ScalarMeanFunction.param_encoding_pairs()
    • ScalarMeanFunction.get_mean_value()
    • ScalarMeanFunction.set_mean_value()
    • ScalarMeanFunction.get_params()
    • ScalarMeanFunction.set_params()
  • ZeroMeanFunction
    • ZeroMeanFunction.forward()
    • ZeroMeanFunction.param_encoding_pairs()
    • ZeroMeanFunction.get_params()
    • ZeroMeanFunction.set_params()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.optimization_utils module
  • apply_lbfgs()
  • apply_lbfgs_with_multiple_starts()
  • add_regularizer_to_criterion()
  • create_lbfgs_arguments()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.posterior_state module
  • PosteriorState
    • PosteriorState.num_data
    • PosteriorState.num_features
    • PosteriorState.num_fantasies
    • PosteriorState.neg_log_likelihood()
    • PosteriorState.predict()
    • PosteriorState.sample_marginals()
    • PosteriorState.backward_gradient()
  • PosteriorStateWithSampleJoint
    • PosteriorStateWithSampleJoint.sample_joint()
  • GaussProcPosteriorState
    • GaussProcPosteriorState.num_data
    • GaussProcPosteriorState.num_features
    • GaussProcPosteriorState.num_fantasies
    • GaussProcPosteriorState.neg_log_likelihood()
    • GaussProcPosteriorState.predict()
    • GaussProcPosteriorState.sample_marginals()
    • GaussProcPosteriorState.backward_gradient()
    • GaussProcPosteriorState.sample_joint()
  • backward_gradient_given_predict()
  • IncrementalUpdateGPPosteriorState
    • IncrementalUpdateGPPosteriorState.update()
    • IncrementalUpdateGPPosteriorState.sample_and_update()
    • IncrementalUpdateGPPosteriorState.expand_fantasies()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.posterior_utils module
  • cholesky_computations()
  • predict_posterior_marginals()
  • sample_posterior_marginals()
  • sample_posterior_joint()
  • cholesky_update()
  • sample_and_cholesky_update()
  • negative_log_marginal_likelihood()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.slice module
  • SliceSampler
    • SliceSampler.sample()
  • gen_random_direction()
  • slice_sampler_step_out()
  • slice_sampler_step_in()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.target_transform module
  • ScalarTargetTransform
    • ScalarTargetTransform.forward()
    • ScalarTargetTransform.negative_log_jacobian()
    • ScalarTargetTransform.inverse()
    • ScalarTargetTransform.on_fit_start()
  • IdentityTargetTransform
    • IdentityTargetTransform.forward()
    • IdentityTargetTransform.negative_log_jacobian()
    • IdentityTargetTransform.inverse()
    • IdentityTargetTransform.param_encoding_pairs()
    • IdentityTargetTransform.get_params()
    • IdentityTargetTransform.set_params()
  • BoxCoxTargetTransform
    • BoxCoxTargetTransform.param_encoding_pairs()
    • BoxCoxTargetTransform.get_boxcox_lambda()
    • BoxCoxTargetTransform.set_boxcox_lambda()
    • BoxCoxTargetTransform.get_params()
    • BoxCoxTargetTransform.set_params()
    • BoxCoxTargetTransform.negative_log_jacobian()
    • BoxCoxTargetTransform.forward()
    • BoxCoxTargetTransform.inverse()
    • BoxCoxTargetTransform.on_fit_start()
• syne_tune.optimizer.schedulers.searchers.bayesopt.gpautograd.warping module
  • Warping
    • Warping.forward()
    • Warping.param_encoding_pairs()
    • Warping.get_params()
    • Warping.set_params()
  • warpings_for_hyperparameters()
  • kernel_with_warping()
  • WarpedKernel
    • WarpedKernel.forward()
    • WarpedKernel.diagonal()
    • WarpedKernel.diagonal_depends_on_X()
    • WarpedKernel.param_encoding_pairs()
    • WarpedKernel.get_params()
    • WarpedKernel.set_params()