ax.storage¶

ax.storage.json_store.decoder module¶

ax.storage.json_store.decoder.ax_class_from_json_dict(_class: Type, object_json: Dict[str, Any], decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}) → Any[source]¶

Reinstantiates an Ax class registered in DECODER_REGISTRY from a JSON dict.

ax.storage.json_store.decoder.data_from_json(data_by_trial_json: Dict[str, Any], decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}) → Dict[int, OrderedDict[int, Data]][source]¶

Load Ax Data from JSON.

ax.storage.json_store.decoder.experiment_from_json(object_json: Dict[str, Any], decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}) → ax.core.experiment.Experiment[source]¶

Load Ax Experiment from JSON.

ax.storage.json_store.decoder.generation_step_from_json(generation_step_json: Dict[str, Any], decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}) → ax.modelbridge.generation_node.GenerationStep[source]¶

Load generation step from JSON.

ax.storage.json_store.decoder.generation_strategy_from_json(generation_strategy_json: Dict[str, Any], decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}, experiment: Optional[ax.core.experiment.Experiment] = None) → ax.modelbridge.generation_strategy.GenerationStrategy[source]¶

Load generation strategy from JSON.

ax.storage.json_store.decoder.generator_run_from_json(object_json: Dict[str, Any], decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}) → ax.core.generator_run.GeneratorRun[source]¶

Load Ax GeneratorRun from JSON.

ax.storage.json_store.decoder.multi_type_experiment_from_json(object_json: Dict[str, Any], decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}) → ax.core.multi_type_experiment.MultiTypeExperiment[source]¶

Load AE MultiTypeExperiment from JSON.

ax.storage.json_store.decoder.object_from_json(object_json: Any, decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}) → Any[source]¶

Recursively load objects from a JSON-serializable dictionary.

ax.storage.json_store.decoder.parameter_constraints_from_json(parameter_constraint_json: List[Dict[str, Any]], parameters: List[ax.core.parameter.Parameter], decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}) → List[ax.core.parameter_constraint.ParameterConstraint][source]¶

Load ParameterConstraints from JSON.

Order and SumConstraint are tied to a search space, and require that SearchSpace’s parameters to be passed in for decoding.

Parameters

• parameter_constraint_json – JSON representation of parameter constraints.

• parameters – Parameter definitions for decoding via parameter names.

Returns

Python classes for parameter constraints.

Return type

parameter_constraints

ax.storage.json_store.decoder.search_space_from_json(search_space_json: Dict[str, Any], decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}) → ax.core.search_space.SearchSpace[source]¶

Load a SearchSpace from JSON.

This function is necessary due to the coupled loading of SearchSpace and parameter constraints.

ax.storage.json_store.decoder.simple_benchmark_problem_from_json(object_json: Dict[str, Any], decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}) → ax.benchmark.benchmark_problem.SimpleBenchmarkProblem[source]¶

Load a benchmark problem from JSON.

ax.storage.json_store.decoder.trials_from_json(experiment: ax.core.experiment.Experiment, trials_json: Dict[str, Any], decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}) → Dict[int, ax.core.base_trial.BaseTrial][source]¶

Load Ax Trials from JSON.

ax.storage.json_store.decoders module¶

ax.storage.json_store.decoders.batch_trial_from_json(experiment: core.experiment.Experiment, index: int, trial_type: Optional[str], status: TrialStatus, time_created: datetime, time_completed: Optional[datetime], time_staged: Optional[datetime], time_run_started: Optional[datetime], abandoned_reason: Optional[str], run_metadata: Optional[Dict[str, Any]], generator_run_structs: List[GeneratorRunStruct], runner: Optional[Runner], abandoned_arms_metadata: Dict[str, AbandonedArm], num_arms_created: int, status_quo: Optional[Arm], status_quo_weight_override: float, optimize_for_power: Optional[bool], ttl_seconds: Optional[int] = None, generation_step_index: Optional[int] = None, properties: Optional[Dict[str, Any]] = None, stop_metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → BatchTrial[source]¶

Load Ax BatchTrial from JSON.

Other classes don’t need explicit deserializers, because we can just use their constructors (see decoder.py). However, the constructor for Batch does not allow us to exactly recreate an existing object.

ax.storage.json_store.decoders.class_from_json(json: Dict[str, Any]) → Type[Any][source]¶

Load any class registered in CLASS_DECODER_REGISTRY from JSON.

ax.storage.json_store.decoders.transform_type_from_json(object_json: Dict[str, Any]) → Type[ax.modelbridge.transforms.base.Transform][source]¶

Load the transform type from JSON.

ax.storage.json_store.decoders.trial_from_json(experiment: core.experiment.Experiment, index: int, trial_type: Optional[str], status: TrialStatus, time_created: datetime, time_completed: Optional[datetime], time_staged: Optional[datetime], time_run_started: Optional[datetime], abandoned_reason: Optional[str], run_metadata: Optional[Dict[str, Any]], generator_run: GeneratorRun, runner: Optional[Runner], num_arms_created: int, ttl_seconds: Optional[int] = None, generation_step_index: Optional[int] = None, properties: Optional[Dict[str, Any]] = None, stop_metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Trial[source]¶

Load Ax trial from JSON.

Other classes don’t need explicit deserializers, because we can just use their constructors (see decoder.py). However, the constructor for Trial does not allow us to exactly recreate an existing object.

ax.storage.json_store.encoder module¶

ax.storage.json_store.encoder.object_to_json(obj: Any, encoder_registry: Dict[Type, Callable[[Any], Dict[str, Any]]] = {<class 'ax.core.arm.Arm'>: <function arm_to_dict>, <class 'ax.metrics.branin.AugmentedBraninMetric'>: <function metric_to_dict>, <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>: <function metric_to_dict>, <class 'ax.core.batch_trial.BatchTrial'>: <function batch_to_dict>, <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>: <function benchmark_problem_to_dict>, <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>: <function botorch_model_to_dict>, <class 'ax.metrics.branin.BraninMetric'>: <function metric_to_dict>, <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>: <function metric_to_dict>, <class 'ax.core.parameter.ChoiceParameter'>: <function choice_parameter_to_dict>, <class 'ax.core.data.Data'>: <function data_to_dict>, <class 'ax.core.experiment.Experiment'>: <function experiment_to_dict>, <class 'ax.metrics.factorial.FactorialMetric'>: <function metric_to_dict>, <class 'ax.core.parameter.FixedParameter'>: <function fixed_parameter_to_dict>, <class 'ax.modelbridge.generation_node.GenerationStep'>: <function generation_step_to_dict>, <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>: <function generation_strategy_to_dict>, <class 'ax.core.generator_run.GeneratorRun'>: <function generator_run_to_dict>, <class 'ax.metrics.hartmann6.Hartmann6Metric'>: <function metric_to_dict>, <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>: <function surrogate_to_dict>, <class 'ax.metrics.l2norm.L2NormMetric'>: <function metric_to_dict>, <class 'ax.core.map_data.MapData'>: <function map_data_to_dict>, <class 'ax.core.map_data.MapKeyInfo'>: <function map_key_info_to_dict>, <class 'ax.core.map_metric.MapMetric'>: <function metric_to_dict>, <class 'ax.core.metric.Metric'>: <function metric_to_dict>, <class 'ax.core.objective.MultiObjective'>: <function multi_objective_to_dict>, <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>: <function multi_objective_optimization_config_to_dict>, <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>: <function multi_type_experiment_to_dict>, <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>: <function percentile_early_stopping_strategy_to_dict>, <class 'ax.metrics.sklearn.SklearnMetric'>: <function metric_to_dict>, <class 'ax.metrics.chemistry.ChemistryMetric'>: <function metric_to_dict>, <class 'ax.metrics.branin.NegativeBraninMetric'>: <function metric_to_dict>, <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>: <function metric_to_dict>, <class 'ax.core.objective.Objective'>: <function objective_to_dict>, <class 'ax.core.outcome_constraint.ObjectiveThreshold'>: <function outcome_constraint_to_dict>, <class 'ax.core.optimization_config.OptimizationConfig'>: <function optimization_config_to_dict>, <class 'ax.core.parameter_constraint.OrderConstraint'>: <function order_parameter_constraint_to_dict>, <class 'ax.core.outcome_constraint.OutcomeConstraint'>: <function outcome_constraint_to_dict>, <class 'ax.core.parameter_constraint.ParameterConstraint'>: <function parameter_constraint_to_dict>, <class 'ax.core.parameter.RangeParameter'>: <function range_parameter_to_dict>, <class 'ax.core.objective.ScalarizedObjective'>: <function scalarized_objective_to_dict>, <class 'ax.core.search_space.SearchSpace'>: <function search_space_to_dict>, <class 'ax.core.search_space.HierarchicalSearchSpace'>: <function search_space_to_dict>, <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>: <function benchmark_problem_to_dict>, <class 'ax.core.parameter_constraint.SumConstraint'>: <function sum_parameter_constraint_to_dict>, <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>: <function surrogate_to_dict>, <class 'ax.runners.synthetic.SyntheticRunner'>: <function runner_to_dict>, <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>: <function threshold_early_stopping_strategy_to_dict>, <class 'ax.core.trial.Trial'>: <function trial_to_dict>, <class 'ax.core.observation.ObservationFeatures'>: <function observation_features_to_dict>, <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>: <function winsorization_config_to_dict>}, class_encoder_registry: Dict[Type, Callable[[Any], Dict[str, Any]]] = {<class 'ax.models.torch.botorch_modular.acquisition.Acquisition'>: <function botorch_modular_to_dict>, <class 'botorch.acquisition.acquisition.AcquisitionFunction'>: <function botorch_modular_to_dict>, <class 'gpytorch.mlls.marginal_log_likelihood.MarginalLogLikelihood'>: <function botorch_modular_to_dict>, <class 'botorch.models.model.Model'>: <function botorch_modular_to_dict>, <class 'ax.modelbridge.transforms.base.Transform'>: <function transform_type_to_dict>}) → Any[source]¶

Convert an Ax object to a JSON-serializable dictionary.

The root node passed to this function should always be an instance of a core Ax class or a JSON-compatible python builtin. The sub-fields of the input will then be recursively passed to this function.

e.g. if we pass an instance of Experiment, we will first fall through to the line object_dict = ENCODER_REGISTRY[_type](object), which will convert the Experiment to a (shallow) dictionary, where search subfield remains “unconverted”, i.e.: {“name”: <name: string>, “search_space”: <search space: SearchSpace>}. We then pass each item of the dictionary back into this function to recursively convert the entire object.

ax.storage.json_store.encoders module¶

ax.storage.json_store.encoders.arm_to_dict(arm: ax.core.arm.Arm) → Dict[str, Any][source]¶

Convert Ax arm to a dictionary.

ax.storage.json_store.encoders.batch_to_dict(batch: ax.core.batch_trial.BatchTrial) → Dict[str, Any][source]¶

Convert Ax batch to a dictionary.

ax.storage.json_store.encoders.benchmark_problem_to_dict(benchmark_problem: ax.benchmark.benchmark_problem.BenchmarkProblem) → Dict[str, Any][source]¶

Converts an Ax benchmark problem to a serializable dictionary.

ax.storage.json_store.encoders.botorch_model_to_dict(model: ax.models.torch.botorch_modular.model.BoTorchModel) → Dict[str, Any][source]¶

Convert Ax model to a dictionary.

ax.storage.json_store.encoders.botorch_modular_to_dict(class_type: Type[Any]) → Dict[str, Any][source]¶

Convert any class to a dictionary.

ax.storage.json_store.encoders.choice_parameter_to_dict(parameter: ax.core.parameter.ChoiceParameter) → Dict[str, Any][source]¶

Convert Ax choice parameter to a dictionary.

ax.storage.json_store.encoders.data_to_dict(data: ax.core.data.Data) → Dict[str, Any][source]¶

Convert Ax data to a dictionary.

ax.storage.json_store.encoders.experiment_to_dict(experiment: ax.core.experiment.Experiment) → Dict[str, Any][source]¶

Convert Ax experiment to a dictionary.

ax.storage.json_store.encoders.fixed_parameter_to_dict(parameter: ax.core.parameter.FixedParameter) → Dict[str, Any][source]¶

Convert Ax fixed parameter to a dictionary.

ax.storage.json_store.encoders.generation_step_to_dict(generation_step: ax.modelbridge.generation_node.GenerationStep) → Dict[str, Any][source]¶

Converts Ax generation step to a dictionary.

ax.storage.json_store.encoders.generation_strategy_to_dict(generation_strategy: ax.modelbridge.generation_strategy.GenerationStrategy) → Dict[str, Any][source]¶

Converts Ax generation strategy to a dictionary.

ax.storage.json_store.encoders.generator_run_to_dict(generator_run: ax.core.generator_run.GeneratorRun) → Dict[str, Any][source]¶

Convert Ax generator run to a dictionary.

ax.storage.json_store.encoders.map_data_to_dict(map_data: ax.core.map_data.MapData) → Dict[str, Any][source]¶

Convert Ax map data to a dictionary.

ax.storage.json_store.encoders.map_key_info_to_dict(mki: ax.core.map_data.MapKeyInfo) → Dict[str, Any][source]¶

Convert Ax map data metadata to a dictionary.

ax.storage.json_store.encoders.metric_to_dict(metric: ax.core.metric.Metric) → Dict[str, Any][source]¶

Convert Ax metric to a dictionary.

ax.storage.json_store.encoders.multi_objective_optimization_config_to_dict(multi_objective_optimization_config: ax.core.optimization_config.MultiObjectiveOptimizationConfig) → Dict[str, Any][source]¶

Convert Ax optimization config to a dictionary.

ax.storage.json_store.encoders.multi_objective_to_dict(objective: ax.core.objective.MultiObjective) → Dict[str, Any][source]¶

Convert Ax objective to a dictionary.

ax.storage.json_store.encoders.multi_type_experiment_to_dict(experiment: ax.core.multi_type_experiment.MultiTypeExperiment) → Dict[str, Any][source]¶

Convert AE multitype experiment to a dictionary.

ax.storage.json_store.encoders.objective_to_dict(objective: ax.core.objective.Objective) → Dict[str, Any][source]¶

Convert Ax objective to a dictionary.

ax.storage.json_store.encoders.observation_features_to_dict(obs_features: ax.core.observation.ObservationFeatures) → Dict[str, Any][source]¶

Converts Ax observation features to a dictionary

ax.storage.json_store.encoders.optimization_config_to_dict(optimization_config: ax.core.optimization_config.OptimizationConfig) → Dict[str, Any][source]¶

Convert Ax optimization config to a dictionary.

ax.storage.json_store.encoders.order_parameter_constraint_to_dict(parameter_constraint: ax.core.parameter_constraint.OrderConstraint) → Dict[str, Any][source]¶

Convert Ax order parameter constraint to a dictionary.

ax.storage.json_store.encoders.outcome_constraint_to_dict(outcome_constraint: ax.core.outcome_constraint.OutcomeConstraint) → Dict[str, Any][source]¶

Convert Ax outcome constraint to a dictionary.

ax.storage.json_store.encoders.parameter_constraint_to_dict(parameter_constraint: ax.core.parameter_constraint.ParameterConstraint) → Dict[str, Any][source]¶

Convert Ax sum parameter constraint to a dictionary.

ax.storage.json_store.encoders.percentile_early_stopping_strategy_to_dict(strategy: ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy) → Dict[str, Any][source]¶

Convert Ax percentile early stopping strategy to a dictionary.

ax.storage.json_store.encoders.range_parameter_to_dict(parameter: ax.core.parameter.RangeParameter) → Dict[str, Any][source]¶

Convert Ax range parameter to a dictionary.

ax.storage.json_store.encoders.runner_to_dict(runner: ax.runners.synthetic.SyntheticRunner) → Dict[str, Any][source]¶

Convert Ax synthetic runner to a dictionary.

ax.storage.json_store.encoders.scalarized_objective_to_dict(objective: ax.core.objective.ScalarizedObjective) → Dict[str, Any][source]¶

Convert Ax objective to a dictionary.

ax.storage.json_store.encoders.search_space_to_dict(search_space: ax.core.search_space.SearchSpace) → Dict[str, Any][source]¶

Convert Ax search space to a dictionary.

ax.storage.json_store.encoders.sum_parameter_constraint_to_dict(parameter_constraint: ax.core.parameter_constraint.SumConstraint) → Dict[str, Any][source]¶

Convert Ax sum parameter constraint to a dictionary.

ax.storage.json_store.encoders.surrogate_to_dict(surrogate: ax.models.torch.botorch_modular.surrogate.Surrogate) → Dict[str, Any][source]¶

Convert Ax surrogate to a dictionary.

ax.storage.json_store.encoders.threshold_early_stopping_strategy_to_dict(strategy: ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy) → Dict[str, Any][source]¶

Convert Ax metric-threshold early stopping strategy to a dictionary.

ax.storage.json_store.encoders.transform_type_to_dict(transform_type: Type[ax.modelbridge.transforms.base.Transform]) → Dict[str, Any][source]¶

Convert a transform class to a dictionary.

ax.storage.json_store.encoders.trial_to_dict(trial: ax.core.trial.Trial) → Dict[str, Any][source]¶

Convert Ax trial to a dictionary.

ax.storage.json_store.encoders.winsorization_config_to_dict(config: ax.modelbridge.transforms.winsorize.WinsorizationConfig) → Dict[str, Any][source]¶

Convert Ax winsorization config to a dictionary.

ax.storage.json_store.load module¶

ax.storage.json_store.load.load_experiment(filepath: str, decoder_registry: Dict[str, Type] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BraninMetric': <class 'ax.metrics.branin.BraninMetric'>, 'BraninTimestampMapMetric': <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>, 'ChemistryMetric': <class 'ax.metrics.chemistry.ChemistryMetric'>, 'ChemistryProblemType': <enum 'ChemistryProblemType'>, 'ChoiceParameter': <class 'ax.core.parameter.ChoiceParameter'>, 'ComparisonOp': <enum 'ComparisonOp'>, 'Data': <class 'ax.core.data.Data'>, 'DataType': <enum 'DataType'>, 'DomainType': <enum 'DomainType'>, 'Experiment': <class 'ax.core.experiment.Experiment'>, 'FactorialMetric': <class 'ax.metrics.factorial.FactorialMetric'>, 'FixedParameter': <class 'ax.core.parameter.FixedParameter'>, 'GenerationStep': <class 'ax.modelbridge.generation_node.GenerationStep'>, 'GenerationStrategy': <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>, 'GeneratorRun': <class 'ax.core.generator_run.GeneratorRun'>, 'GeneratorRunStruct': <class 'ax.core.batch_trial.GeneratorRunStruct'>, 'Hartmann6Metric': <class 'ax.metrics.hartmann6.Hartmann6Metric'>, 'HierarchicalSearchSpace': <class 'ax.core.search_space.HierarchicalSearchSpace'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'Metric': <class 'ax.core.metric.Metric'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Objective': <class 'ax.core.objective.Objective'>, 'ObjectiveThreshold': <class 'ax.core.outcome_constraint.ObjectiveThreshold'>, 'ObservationFeatures': <class 'ax.core.observation.ObservationFeatures'>, 'OptimizationConfig': <class 'ax.core.optimization_config.OptimizationConfig'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterType': <enum 'ParameterType'>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SimpleBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'WinsorizationConfig': <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>}, class_decoder_registry: Dict[str, Callable[[Dict[str, Any]], Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[Transform]': <function transform_type_from_json>}) → ax.core.experiment.Experiment[source]¶

Load experiment from file.

1. Read file.

2. Convert dictionary to Ax experiment instance.

ax.storage.json_store.registry module¶

ax.storage.json_store.save module¶

ax.storage.json_store.save.save_experiment(experiment: ax.core.experiment.Experiment, filepath: str, encoder_registry: Dict[Type, Callable[[Any], Dict[str, Any]]] = {<class 'ax.core.arm.Arm'>: <function arm_to_dict>, <class 'ax.metrics.branin.AugmentedBraninMetric'>: <function metric_to_dict>, <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>: <function metric_to_dict>, <class 'ax.core.batch_trial.BatchTrial'>: <function batch_to_dict>, <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>: <function benchmark_problem_to_dict>, <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>: <function botorch_model_to_dict>, <class 'ax.metrics.branin.BraninMetric'>: <function metric_to_dict>, <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>: <function metric_to_dict>, <class 'ax.core.parameter.ChoiceParameter'>: <function choice_parameter_to_dict>, <class 'ax.core.data.Data'>: <function data_to_dict>, <class 'ax.core.experiment.Experiment'>: <function experiment_to_dict>, <class 'ax.metrics.factorial.FactorialMetric'>: <function metric_to_dict>, <class 'ax.core.parameter.FixedParameter'>: <function fixed_parameter_to_dict>, <class 'ax.modelbridge.generation_node.GenerationStep'>: <function generation_step_to_dict>, <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>: <function generation_strategy_to_dict>, <class 'ax.core.generator_run.GeneratorRun'>: <function generator_run_to_dict>, <class 'ax.metrics.hartmann6.Hartmann6Metric'>: <function metric_to_dict>, <class 'ax.models.torch.botorch_modular.list_surrogate.ListSurrogate'>: <function surrogate_to_dict>, <class 'ax.metrics.l2norm.L2NormMetric'>: <function metric_to_dict>, <class 'ax.core.map_data.MapData'>: <function map_data_to_dict>, <class 'ax.core.map_data.MapKeyInfo'>: <function map_key_info_to_dict>, <class 'ax.core.map_metric.MapMetric'>: <function metric_to_dict>, <class 'ax.core.metric.Metric'>: <function metric_to_dict>, <class 'ax.core.objective.MultiObjective'>: <function multi_objective_to_dict>, <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>: <function multi_objective_optimization_config_to_dict>, <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>: <function multi_type_experiment_to_dict>, <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>: <function percentile_early_stopping_strategy_to_dict>, <class 'ax.metrics.sklearn.SklearnMetric'>: <function metric_to_dict>, <class 'ax.metrics.chemistry.ChemistryMetric'>: <function metric_to_dict>, <class 'ax.metrics.branin.NegativeBraninMetric'>: <function metric_to_dict>, <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>: <function metric_to_dict>, <class 'ax.core.objective.Objective'>: <function objective_to_dict>, <class 'ax.core.outcome_constraint.ObjectiveThreshold'>: <function outcome_constraint_to_dict>, <class 'ax.core.optimization_config.OptimizationConfig'>: <function optimization_config_to_dict>, <class 'ax.core.parameter_constraint.OrderConstraint'>: <function order_parameter_constraint_to_dict>, <class 'ax.core.outcome_constraint.OutcomeConstraint'>: <function outcome_constraint_to_dict>, <class 'ax.core.parameter_constraint.ParameterConstraint'>: <function parameter_constraint_to_dict>, <class 'ax.core.parameter.RangeParameter'>: <function range_parameter_to_dict>, <class 'ax.core.objective.ScalarizedObjective'>: <function scalarized_objective_to_dict>, <class 'ax.core.search_space.SearchSpace'>: <function search_space_to_dict>, <class 'ax.core.search_space.HierarchicalSearchSpace'>: <function search_space_to_dict>, <class 'ax.benchmark.benchmark_problem.SimpleBenchmarkProblem'>: <function benchmark_problem_to_dict>, <class 'ax.core.parameter_constraint.SumConstraint'>: <function sum_parameter_constraint_to_dict>, <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>: <function surrogate_to_dict>, <class 'ax.runners.synthetic.SyntheticRunner'>: <function runner_to_dict>, <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>: <function threshold_early_stopping_strategy_to_dict>, <class 'ax.core.trial.Trial'>: <function trial_to_dict>, <class 'ax.core.observation.ObservationFeatures'>: <function observation_features_to_dict>, <class 'ax.modelbridge.transforms.winsorize.WinsorizationConfig'>: <function winsorization_config_to_dict>}, class_encoder_registry: Dict[Type, Callable[[Any], Dict[str, Any]]] = {<class 'ax.models.torch.botorch_modular.acquisition.Acquisition'>: <function botorch_modular_to_dict>, <class 'botorch.acquisition.acquisition.AcquisitionFunction'>: <function botorch_modular_to_dict>, <class 'gpytorch.mlls.marginal_log_likelihood.MarginalLogLikelihood'>: <function botorch_modular_to_dict>, <class 'botorch.models.model.Model'>: <function botorch_modular_to_dict>, <class 'ax.modelbridge.transforms.base.Transform'>: <function transform_type_to_dict>}) → None[source]¶

Save experiment to file.

1. Convert Ax experiment to JSON-serializable dictionary.

2. Write to file.

ax.storage.sqa_store.base_decoder module¶

ax.storage.sqa_store.base_encoder module¶

ax.storage.sqa_store.db module¶

class ax.storage.sqa_store.db.SQABase[source]¶

Bases: object

Metaclass for SQLAlchemy classes corresponding to core Ax classes.

ax.storage.sqa_store.db.create_all_tables(engine: sqlalchemy.engine.base.Engine) → None[source]¶

Create all tables that inherit from Base.

Parameters

engine – a SQLAlchemy engine with a connection to a MySQL or SQLite DB.

Note

In order for all tables to be correctly created, all modules that define a mapped class that inherits from Base must be imported.

ax.storage.sqa_store.db.create_mysql_engine_from_creator(creator: Callable, echo: bool = False, pool_recycle: int = 10, **kwargs: Any) → sqlalchemy.engine.base.Engine[source]¶

Create a SQLAlchemy engine with the MySQL dialect given a creator function.

Parameters

• creator – a callable which returns a DBAPI connection.

• echo – if True, set engine to be verbose.

• pool_recycle – number of seconds after which to recycle connections. -1 means no timeout. Default is 10 seconds.

• **kwargs – keyword args passed to create_engine

Returns

SQLAlchemy engine with connection to MySQL DB.

Return type

Engine

ax.storage.sqa_store.db.create_mysql_engine_from_url(url: str, echo: bool = False, pool_recycle: int = 10, **kwargs: Any) → sqlalchemy.engine.base.Engine[source]¶

Create a SQLAlchemy engine with the MySQL dialect given a database url.

Parameters

• url – a database url that can include username, password, hostname, database name as well as optional keyword arguments for additional configuration. e.g. dialect+driver://username:password@host:port/database.

• echo – if True, set engine to be verbose.

• pool_recycle – number of seconds after which to recycle connections. -1 means no timeout. Default is 10 seconds.

• **kwargs – keyword args passed to create_engine

Returns

SQLAlchemy engine with connection to MySQL DB.

Return type

Engine

ax.storage.sqa_store.db.create_test_engine(path: Optional[str] = None, echo: bool = True) → sqlalchemy.engine.base.Engine[source]¶

Creates a SQLAlchemy engine object for use in unit tests.

Parameters

• path – if None, use in-memory SQLite; else attempt to create a SQLite DB in the path provided.

• echo – if True, set engine to be verbose.

Returns

an instance of SQLAlchemy engine.

Return type

Engine

ax.storage.sqa_store.db.get_engine() → sqlalchemy.engine.base.Engine[source]¶

Fetch a SQLAlchemy engine, if already initialized.

If not initialized, need to either call init_engine_and_session_factory or get_session explicitly.

Returns

an instance of a SQLAlchemy engine with a connection to a DB.

Return type

Engine

ax.storage.sqa_store.db.get_session() → sqlalchemy.orm.session.Session[source]¶

Fetch a SQLAlchemy session with a connection to a DB.

Unless init_engine_and_session_factory is called first with custom args, this will automatically initialize a connection to xdb.adaptive_experiment.

Returns

an instance of a SQLAlchemy session.

Return type

Session

ax.storage.sqa_store.db.init_engine_and_session_factory(url: Optional[str] = None, creator: Optional[Callable] = None, echo: bool = False, force_init: bool = False, **kwargs: Any) → None[source]¶

Initialize the global engine and SESSION_FACTORY for SQLAlchemy.

The initialization needs to only happen once. Note that it is possible to re-initialize the engine by setting the force_init flag to True, but this should only be used if you are absolutely certain that you know what you are doing.

Parameters

• url – a database url that can include username, password, hostname, database name as well as optional keyword arguments for additional configuration. e.g. dialect+driver://username:password@host:port/database. Either this argument or creator argument must be specified.

• creator – a callable which returns a DBAPI connection. Either this argument or url argument must be specified.

• echo – if True, logging for engine is enabled.

• force_init – if True, allows re-initializing engine and session factory.

• **kwargs – keyword arguments passed to create_mysql_engine_from_creator

ax.storage.sqa_store.db.init_test_engine_and_session_factory(tier_or_path: Optional[str] = None, echo: bool = False, force_init: bool = False, **kwargs: Any) → None[source]¶

Initialize the global engine and SESSION_FACTORY for SQLAlchemy, using an in-memory SQLite database.

The initialization needs to only happen once. Note that it is possible to re-initialize the engine by setting the force_init flag to True, but this should only be used if you are absolutely certain that you know what you are doing.

Parameters

• tier_or_path – the name of the DB tier.

• echo – if True, logging for engine is enabled.

• force_init – if True, allows re-initializing engine and session factory.

• **kwargs – keyword arguments passed to create_mysql_engine_from_creator

ax.storage.sqa_store.db.optional_session_scope(session: Optional[sqlalchemy.orm.session.Session] = None) → AbstractContextManager[sqlalchemy.orm.session.Session][source]¶

ax.storage.sqa_store.db.remove_test_db_file(tier_or_path: str) → None[source]¶

Remove the test DB file from system, useful for cleanup in tests.

ax.storage.sqa_store.db.session_scope() → Generator[sqlalchemy.orm.session.Session, None, None][source]¶

Provide a transactional scope around a series of operations.

ax.storage.sqa_store.delete module¶

ax.storage.sqa_store.json module¶

class ax.storage.sqa_store.json.JSONEncodedMediumText(object_pairs_hook: Optional[Any] = None, *args: List[Any], **kwargs: Dict[Any, Any])[source]¶

Bases: ax.storage.sqa_store.json.JSONEncodedObject

Class for JSON-encoding objects in SQLAlchemy, backed by MEDIUMTEXT (MySQL).

See description in JSONEncodedObject.

impl: sqlalchemy.sql.sqltypes.VARCHAR = Text(length=16777215)¶

class ax.storage.sqa_store.json.JSONEncodedObject(object_pairs_hook: Optional[Any] = None, *args: List[Any], **kwargs: Dict[Any, Any])[source]¶

Bases: sqlalchemy.sql.type_api.TypeDecorator

Class for JSON-encoding objects in SQLAlchemy.

Represents an object that is automatically marshalled and unmarshalled to/from the corresponding JSON string. By itself, this data structure does not track any changes.

impl: sqlalchemy.sql.sqltypes.VARCHAR = VARCHAR(length=4096)¶

process_bind_param(value: Any, dialect: Any) → Optional[str][source]¶

Receive a bound parameter value to be converted.

Custom subclasses of _types.TypeDecorator should override this method to provide custom behaviors for incoming data values. This method is called at statement execution time and is passed the literal Python data value which is to be associated with a bound parameter in the statement.

The operation could be anything desired to perform custom behavior, such as transforming or serializing data. This could also be used as a hook for validating logic.

Parameters

• value – Data to operate upon, of any type expected by this method in the subclass. Can be None.

• dialect – the Dialect in use.

See also

types_typedecorator

_types.TypeDecorator.process_result_value()

process_result_value(value: Any, dialect: Any) → Any[source]¶

Receive a result-row column value to be converted.

Custom subclasses of _types.TypeDecorator should override this method to provide custom behaviors for data values being received in result rows coming from the database. This method is called at result fetching time and is passed the literal Python data value that’s extracted from a database result row.

The operation could be anything desired to perform custom behavior, such as transforming or deserializing data.

Parameters

• value – Data to operate upon, of any type expected by this method in the subclass. Can be None.

• dialect – the Dialect in use.

See also

types_typedecorator

_types.TypeDecorator.process_bind_param()

class ax.storage.sqa_store.json.JSONEncodedText(object_pairs_hook: Optional[Any] = None, *args: List[Any], **kwargs: Dict[Any, Any])[source]¶

Bases: ax.storage.sqa_store.json.JSONEncodedObject

Class for JSON-encoding objects in SQLAlchemy, backed by TEXT (MySQL).

See description in JSONEncodedObject.

impl¶

alias of sqlalchemy.sql.sqltypes.Text

object_pairs_hook: Any¶

ax.storage.sqa_store.load module¶

ax.storage.sqa_store.save module¶

ax.storage.sqa_store.structs module¶

ax.storage.sqa_store.sqa_classes module¶

class ax.storage.sqa_store.sqa_classes.SQAAbandonedArm(*args: Any, **kwargs: Any)[source]¶

Bases: sqlalchemy.ext.declarative.

abandoned_reason: Optional[str] = Column(None, String(length=255), table=None)¶

id: int = Column(None, Integer(), table=None, primary_key=True, nullable=False)¶

name: str = Column(None, String(length=100), table=None, nullable=False)¶

time_abandoned: datetime.datetime = Column(None, IntTimestamp(), table=None, nullable=False, default=ColumnDefault(<function datetime.now>))¶

trial_id: int = Column(None, Integer(), ForeignKey('trial_v2.id'), table=None)¶

class ax.storage.sqa_store.sqa_classes.SQAArm(*args: Any, **kwargs: Any)[source]¶

Bases: sqlalchemy.ext.declarative.

generator_run_id: int = Column(None, Integer(), ForeignKey('generator_run_v2.id'), table=None)¶

id: int = Column(None, Integer(), table=None, primary_key=True, nullable=False)¶

name: Optional[str] = Column(None, String(length=100), table=None)¶

parameters: Dict[str, Optional[Union[str, bool, float, int]]] = Column(None, JSONEncodedText(), table=None, nullable=False)¶

weight: float = Column(None, Float(), table=None, nullable=False, default=ColumnDefault(1.0))¶

class ax.storage.sqa_store.sqa_classes.SQAData(*args: Any, **kwargs: Any)[source]¶

Bases: sqlalchemy.ext.declarative.

data_json: str = Column(None, Text(length=4294967295), table=None, nullable=False)¶

description: Optional[str] = Column(None, String(length=255), table=None)¶

experiment_id: int = Column(None, Integer(), ForeignKey('experiment_v2.id'), table=None)¶

generation_strategy_id: Optional[int] = Column(None, Integer(), ForeignKey('generation_strategy.id'), table=None)¶

id: int = Column(None, Integer(), table=None, primary_key=True, nullable=False)¶

structure_metadata_json: str = Column(None, Text(length=4294967295), table=None)¶

time_created: int = Column(None, BigInteger(), table=None, nullable=False)¶

trial_index: Optional[int] = Column(None, Integer(), table=None)¶

class ax.storage.sqa_store.sqa_classes.SQAExperiment(*args: Any, **kwargs: Any)[source]¶

Bases: sqlalchemy.ext.declarative.

data: List[ax.storage.sqa_store.sqa_classes.SQAData] = <RelationshipProperty at 0x7efcc8a587a0; no key>¶

default_data_type: ax.core.experiment.DataType = Column(None, IntEnum(), table=None)¶

default_trial_type: Optional[str] = Column(None, String(length=100), table=None)¶

description: Optional[str] = Column(None, String(length=255), table=None)¶

experiment_type: Optional[int] = Column(None, Integer(), table=None)¶

generation_strategy: Optional[ax.storage.sqa_store.sqa_classes.SQAGenerationStrategy] = <RelationshipProperty at 0x7efcc8a58b00; no key>¶

id: int = Column(None, Integer(), table=None, primary_key=True, nullable=False)¶

is_test: bool = Column(None, Boolean(), table=None, nullable=False, default=ColumnDefault(False))¶

metrics: List[ax.storage.sqa_store.sqa_classes.SQAMetric] = <RelationshipProperty at 0x7efcc8a58830; no key>¶

name: str = Column(None, String(length=100), table=None, nullable=False)¶

parameter_constraints: List[ax.storage.sqa_store.sqa_classes.SQAParameterConstraint] = <RelationshipProperty at 0x7efcc8a58950; no key>¶

parameters: List[ax.storage.sqa_store.sqa_classes.SQAParameter] = <RelationshipProperty at 0x7efcc8a588c0; no key>¶

properties: Optional[Dict[str, Any]] = Column(None, JSONEncodedText(), table=None, default=ColumnDefault({}))¶

runners: List[ax.storage.sqa_store.sqa_classes.SQARunner] = <RelationshipProperty at 0x7efcc8a589e0; no key>¶

status_quo_name: Optional[str] = Column(None, String(length=100), table=None)¶

status_quo_parameters: Optional[Dict[str, Optional[Union[str, bool, float, int]]]] = Column(None, JSONEncodedText(), table=None)¶

time_created: datetime.datetime = Column(None, IntTimestamp(), table=None, nullable=False)¶

trials: List[ax.storage.sqa_store.sqa_classes.SQATrial] = <RelationshipProperty at 0x7efcc8a58a70; no key>¶

class ax.storage.sqa_store.sqa_classes.SQAGenerationStrategy(*args: Any, **kwargs: Any)[source]¶

Bases: sqlalchemy.ext.declarative.

curr_index: int = Column(None, Integer(), table=None, nullable=False)¶

experiment_id: Optional[int] = Column(None, Integer(), ForeignKey('experiment_v2.id'), table=None)¶

generator_runs: List[ax.storage.sqa_store.sqa_classes.SQAGeneratorRun] = <RelationshipProperty at 0x7efcc8a46440; no key>¶

id: int = Column(None, Integer(), table=None, primary_key=True, nullable=False)¶

name: str = Column(None, String(length=100), table=None, nullable=False)¶

steps: List[Dict[str, Any]] = Column(None, JSONEncodedObject(length=4096), table=None, nullable=False)¶

class ax.storage.sqa_store.sqa_classes.SQAGeneratorRun(*args: Any, **kwargs: Any)[source]¶

Bases: sqlalchemy.ext.declarative.

arms: List[ax.storage.sqa_store.sqa_classes.SQAArm] = <RelationshipProperty at 0x7efcc8b30dd0; no key>¶

best_arm_name: Optional[str] = Column(None, String(length=100), table=None)¶

best_arm_parameters: Optional[Dict[str, Optional[Union[str, bool, float, int]]]] = Column(None, JSONEncodedText(), table=None)¶

best_arm_predictions: Optional[Tuple[Dict[str, float], Optional[Dict[str, Dict[str, float]]]]] = Column(None, JSONEncodedObject(length=4096), table=None)¶

bridge_kwargs: Optional[Dict[str, Any]] = Column(None, JSONEncodedText(), table=None)¶

candidate_metadata_by_arm_signature: Optional[Dict[str, Any]] = Column(None, JSONEncodedText(), table=None)¶

fit_time: Optional[float] = Column(None, Float(), table=None)¶

gen_metadata: Optional[Dict[str, Any]] = Column(None, JSONEncodedText(), table=None)¶

gen_time: Optional[float] = Column(None, Float(), table=None)¶

generation_step_index: Optional[int] = Column(None, Integer(), table=None)¶

generation_strategy_id: Optional[int] = Column(None, Integer(), ForeignKey('generation_strategy.id'), table=None)¶

generator_run_type: Optional[int] = Column(None, Integer(), table=None)¶

id: int = Column(None, Integer(), table=None, primary_key=True, nullable=False)¶

index: Optional[int] = Column(None, Integer(), table=None)¶

metrics: List[ax.storage.sqa_store.sqa_classes.SQAMetric] = <RelationshipProperty at 0x7efcc8b300e0; no key>¶

model_key: Optional[str] = Column(None, String(length=100), table=None)¶

model_kwargs: Optional[Dict[str, Any]] = Column(None, JSONEncodedText(), table=None)¶

model_predictions: Optional[Tuple[Dict[str, List[float]], Dict[str, Dict[str, List[float]]]]] = Column(None, JSONEncodedObject(length=4096), table=None)¶

model_state_after_gen: Optional[Dict[str, Any]] = Column(None, JSONEncodedText(), table=None)¶

parameter_constraints: List[ax.storage.sqa_store.sqa_classes.SQAParameterConstraint] = <RelationshipProperty at 0x7efcc8a46170; no key>¶

parameters: List[ax.storage.sqa_store.sqa_classes.SQAParameter] = <RelationshipProperty at 0x7efcc8a460e0; no key>¶

time_created: datetime.datetime = Column(None, IntTimestamp(), table=None, nullable=False, default=ColumnDefault(<function datetime.now>))¶

trial_id: Optional[int] = Column(None, Integer(), ForeignKey('trial_v2.id'), table=None)¶

weight: Optional[float] = Column(None, Float(), table=None)¶

class ax.storage.sqa_store.sqa_classes.SQAMetric(*args: Any, **kwargs: Any)[source]¶

Bases: sqlalchemy.ext.declarative.

bound: Optional[float] = Column(None, Float(), table=None)¶

canonical_name: Optional[str] = Column(None, String(length=100), table=None)¶

experiment_id: Optional[int] = Column(None, Integer(), ForeignKey('experiment_v2.id'), table=None)¶

generator_run_id: Optional[int] = Column(None, Integer(), ForeignKey('generator_run_v2.id'), table=None)¶

id: int = Column(None, Integer(), table=None, primary_key=True, nullable=False)¶

intent: ax.storage.utils.MetricIntent = Column(None, StringEnum(length=100), table=None, nullable=False)¶

lower_is_better: Optional[bool] = Column(None, Boolean(), table=None)¶

metric_type: int = Column(None, Integer(), table=None, nullable=False)¶

minimize: Optional[bool] = Column(None, Boolean(), table=None)¶

name: str = Column(None, String(length=255), table=None, nullable=False)¶

op: Optional[ax.core.types.ComparisonOp] = Column(None, IntEnum(), table=None)¶

properties: Optional[Dict[str, Any]] = Column(None, JSONEncodedText(), table=None, default=ColumnDefault({}))¶

relative: Optional[bool] = Column(None, Boolean(), table=None)¶

scalarized_objective_children_metrics = <RelationshipProperty at 0x7efcc8b304d0; no key>¶

scalarized_objective_id = Column(None, Integer(), ForeignKey('metric_v2.id'), table=None)¶

scalarized_objective_weight: Optional[float] = Column(None, Float(), table=None)¶

scalarized_outcome_constraint_children_metrics = <RelationshipProperty at 0x7efcc8b30680; no key>¶

scalarized_outcome_constraint_id = Column(None, Integer(), ForeignKey('metric_v2.id'), table=None)¶

scalarized_outcome_constraint_weight: Optional[float] = Column(None, Float(), table=None)¶

trial_type: Optional[str] = Column(None, String(length=100), table=None)¶

class ax.storage.sqa_store.sqa_classes.SQAParameter(*args: Any, **kwargs: Any)[source]¶

Bases: sqlalchemy.ext.declarative.

choice_values: Optional[List[Optional[Union[str, bool, float, int]]]] = Column(None, JSONEncodedObject(length=4096), table=None)¶

digits: Optional[int] = Column(None, Integer(), table=None)¶

domain_type: ax.storage.utils.DomainType = Column(None, IntEnum(), table=None, nullable=False)¶

experiment_id: Optional[int] = Column(None, Integer(), ForeignKey('experiment_v2.id'), table=None)¶

fixed_value: Optional[Union[str, bool, float, int]] = Column(None, JSONEncodedObject(length=4096), table=None)¶

generator_run_id: Optional[int] = Column(None, Integer(), ForeignKey('generator_run_v2.id'), table=None)¶

id: int = Column(None, Integer(), table=None, primary_key=True, nullable=False)¶

is_fidelity: Optional[bool] = Column(None, Boolean(), table=None)¶

is_ordered: Optional[bool] = Column(None, Boolean(), table=None)¶

is_task: Optional[bool] = Column(None, Boolean(), table=None)¶

log_scale: Optional[bool] = Column(None, Boolean(), table=None)¶

lower: Optional[float] = Column(None, Float(), table=None)¶

name: str = Column(None, String(length=100), table=None, nullable=False)¶

parameter_type: ax.core.parameter.ParameterType = Column(None, IntEnum(), table=None, nullable=False)¶

target_value: Optional[Union[str, bool, float, int]] = Column(None, JSONEncodedObject(length=4096), table=None)¶

upper: Optional[float] = Column(None, Float(), table=None)¶

class ax.storage.sqa_store.sqa_classes.SQAParameterConstraint(*args: Any, **kwargs: Any)[source]¶

Bases: sqlalchemy.ext.declarative.

bound: float = Column(None, Float(), table=None, nullable=False)¶

constraint_dict: Dict[str, float] = Column(None, JSONEncodedObject(length=4096), table=None, nullable=False)¶

experiment_id: Optional[int] = Column(None, Integer(), ForeignKey('experiment_v2.id'), table=None)¶

generator_run_id: Optional[int] = Column(None, Integer(), ForeignKey('generator_run_v2.id'), table=None)¶

id: int = Column(None, Integer(), table=None, primary_key=True, nullable=False)¶

type: ax.storage.sqa_store.sqa_enum.IntEnum = Column(None, IntEnum(), table=None, nullable=False)¶

class ax.storage.sqa_store.sqa_classes.SQARunner(*args: Any, **kwargs: Any)[source]¶

Bases: sqlalchemy.ext.declarative.

experiment_id: Optional[int] = Column(None, Integer(), ForeignKey('experiment_v2.id'), table=None)¶

id: int = Column(None, Integer(), table=None, primary_key=True, nullable=False)¶

properties: Optional[Dict[str, Any]] = Column(None, JSONEncodedText(), table=None, default=ColumnDefault({}))¶

runner_type: int = Column(None, Integer(), table=None, nullable=False)¶

trial_id: Optional[int] = Column(None, Integer(), ForeignKey('trial_v2.id'), table=None)¶

trial_type: Optional[str] = Column(None, String(length=100), table=None)¶

class ax.storage.sqa_store.sqa_classes.SQATrial(*args: Any, **kwargs: Any)[source]¶

Bases: sqlalchemy.ext.declarative.

abandoned_arms: List[ax.storage.sqa_store.sqa_classes.SQAAbandonedArm] = <RelationshipProperty at 0x7efcc8a58290; no key>¶

abandoned_reason: Optional[str] = Column(None, String(length=100), table=None)¶

deployed_name: Optional[str] = Column(None, String(length=100), table=None)¶

experiment_id: int = Column(None, Integer(), ForeignKey('experiment_v2.id'), table=None)¶

generation_step_index: Optional[int] = Column(None, Integer(), table=None)¶

generator_runs: List[ax.storage.sqa_store.sqa_classes.SQAGeneratorRun] = <RelationshipProperty at 0x7efcc8a58320; no key>¶

id: int = Column(None, Integer(), table=None, primary_key=True, nullable=False)¶

index: int = Column(None, Integer(), table=None, nullable=False)¶

is_batch: bool = Column('is_batched', Boolean(), table=None, nullable=False, default=ColumnDefault(True))¶

num_arms_created: int = Column(None, Integer(), table=None, nullable=False, default=ColumnDefault(0))¶

optimize_for_power: Optional[bool] = Column(None, Boolean(), table=None)¶

properties: Optional[Dict[str, Any]] = Column(None, JSONEncodedText(), table=None, default=ColumnDefault({}))¶

run_metadata: Optional[Dict[str, Any]] = Column(None, JSONEncodedText(), table=None)¶

runner: ax.storage.sqa_store.sqa_classes.SQARunner = <RelationshipProperty at 0x7efcc8a583b0; no key>¶

status: ax.core.base_trial.TrialStatus = Column(None, IntEnum(), table=None, nullable=False, default=ColumnDefault(<TrialStatus.CANDIDATE: 0>))¶

status_quo_name: Optional[str] = Column(None, String(length=100), table=None)¶

stop_metadata: Optional[Dict[str, Any]] = Column(None, JSONEncodedText(), table=None)¶

time_completed: Optional[datetime.datetime] = Column(None, IntTimestamp(), table=None)¶

time_created: datetime.datetime = Column(None, IntTimestamp(), table=None, nullable=False)¶

time_run_started: Optional[datetime.datetime] = Column(None, IntTimestamp(), table=None)¶

time_staged: Optional[datetime.datetime] = Column(None, IntTimestamp(), table=None)¶

trial_type: Optional[str] = Column(None, String(length=100), table=None)¶

ttl_seconds: Optional[int] = Column(None, Integer(), table=None)¶