ax.storage¶

ax.storage.json_store.decoder module¶

ax.storage.json_store.decoder.ax_class_from_json_dict(_class: type, object_json: dict[str, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_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, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_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, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → Experiment[source]¶

Load Ax Experiment from JSON.

ax.storage.json_store.decoder.generation_node_from_json(generation_node_json: dict[str, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → GenerationNode[source]¶

Load GenerationNode object from JSON.

ax.storage.json_store.decoder.generation_step_from_json(generation_step_json: dict[str, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → GenerationStep[source]¶

Load generation step from JSON.

ax.storage.json_store.decoder.generation_strategy_from_json(generation_strategy_json: dict[str, ~typing.Any], experiment: ~ax.core.experiment.Experiment | None = None, decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → GenerationStrategy[source]¶

Load generation strategy from JSON.

ax.storage.json_store.decoder.generator_run_from_json(object_json: dict[str, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → GeneratorRun[source]¶

Load Ax GeneratorRun from JSON.

ax.storage.json_store.decoder.get_input_transform_json_components(input_transforms_json: list[dict[str, ~typing.Any]] | dict[str, ~typing.Any] | None, decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → tuple[list[dict[str, Any]] | None, dict[str, Any] | None][source]¶

ax.storage.json_store.decoder.get_outcome_transform_json_components(outcome_transforms_json: list[dict[str, ~typing.Any]] | None, decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → tuple[list[dict[str, Any]] | None, dict[str, Any] | None][source]¶

ax.storage.json_store.decoder.model_spec_from_json(model_spec_json: dict[str, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → ModelSpec[source]¶

Load ModelSpec from JSON.

ax.storage.json_store.decoder.multi_type_experiment_from_json(object_json: dict[str, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → MultiTypeExperiment[source]¶

Load AE MultiTypeExperiment from JSON.

ax.storage.json_store.decoder.object_from_json(object_json: ~typing.Any, decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → Any[source]¶

Recursively load objects from a JSON-serializable dictionary.

ax.storage.json_store.decoder.objective_from_json(object_json: dict[str, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → Objective[source]¶

Load an Objective from JSON in a backwards compatible way.

If both minimize and lower_is_better are specified but have conflicting values, this will overwrite lower_is_better=minimize to resolve the conflict.

# TODO: Do we need to do this for scalarized objective as well?

ax.storage.json_store.decoder.parameter_constraints_from_json(parameter_constraint_json: list[dict[str, ~typing.Any]], parameters: list[~ax.core.parameter.Parameter], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → list[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, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → 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.surrogate_from_list_surrogate_json(list_surrogate_json: dict[str, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → Surrogate[source]¶

ax.storage.json_store.decoder.trials_from_json(experiment: ~ax.core.experiment.Experiment, trials_json: dict[str, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → dict[int, BaseTrial][source]¶

Load Ax Trials from JSON.

ax.storage.json_store.decoder.unpack_transition_criteria_from_json(class_: type, transition_criteria_json: dict[str, ~typing.Any], decoder_registry: dict[str, type[~ax.utils.common.serialization.T] | ~collections.abc.Callable[[...], ~ax.utils.common.serialization.T]] = {'AbandonedArm': <class 'ax.core.batch_trial.AbandonedArm'>, 'AggregatedBenchmarkResult': <class 'ax.benchmark.benchmark_result.AggregatedBenchmarkResult'>, 'AndEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>, 'Arm': <class 'ax.core.arm.Arm'>, 'AutoTransitionAfterGen': <class 'ax.modelbridge.transition_criterion.AutoTransitionAfterGen'>, 'AuxiliaryExperiment': <class 'ax.core.auxiliary.AuxiliaryExperiment'>, 'AuxiliaryExperimentCheck': <class 'ax.modelbridge.transition_criterion.AuxiliaryExperimentCheck'>, 'AuxiliaryExperimentPurpose': <enum 'AuxiliaryExperimentPurpose'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, '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'>, 'ChainedInputTransform': <class 'botorch.models.transforms.input.ChainedInputTransform'>, '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'>, 'GammaPrior': <class 'gpytorch.priors.torch_priors.GammaPrior'>, 'GenerationNode': <class 'ax.modelbridge.generation_node.GenerationNode'>, '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'>, 'ImprovementGlobalStoppingStrategy': <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>, 'InputConstructorPurpose': <enum 'InputConstructorPurpose'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'IsSingleObjective': <class 'ax.modelbridge.transition_criterion.IsSingleObjective'>, 'Keys': <enum 'Keys'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'LifecycleStage': <enum 'LifecycleStage'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'LogNormalPrior': <class 'gpytorch.priors.torch_priors.LogNormalPrior'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, 'MaxGenerationParallelism': <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>, 'MaxTrials': <class 'ax.modelbridge.transition_criterion.MaxTrials'>, 'Metric': <class 'ax.core.metric.Metric'>, 'MinTrials': <class 'ax.modelbridge.transition_criterion.MinTrials'>, 'MinimumPreferenceOccurances': <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>, 'MinimumTrialsInStatus': <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>, 'ModelConfig': <class 'ax.models.torch.botorch_modular.utils.ModelConfig'>, 'ModelRegistryBase': <enum 'ModelRegistryBase'>, 'ModelSpec': <class 'ax.modelbridge.model_spec.ModelSpec'>, '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'>, 'NodeInputConstructors': <enum 'NodeInputConstructors'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, 'Normalize': <class 'botorch.models.transforms.input.Normalize'>, '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'>, 'OrEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>, 'OrderConstraint': <class 'ax.core.parameter_constraint.OrderConstraint'>, 'OutcomeConstraint': <class 'ax.core.outcome_constraint.OutcomeConstraint'>, 'ParameterConstraint': <class 'ax.core.parameter_constraint.ParameterConstraint'>, 'ParameterConstraintType': <enum 'ParameterConstraintType'>, 'ParameterDistribution': <class 'ax.core.parameter_distribution.ParameterDistribution'>, 'ParameterType': <enum 'ParameterType'>, 'Path': <function pathlib_from_json>, 'PercentileEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>, 'PosixPath': <function pathlib_from_json>, 'PurePath': <function pathlib_from_json>, 'PurePosixPath': <function pathlib_from_json>, 'PureWindowsPath': <function pathlib_from_json>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, 'ReductionCriterion': <enum 'ReductionCriterion'>, 'RiskMeasure': <class 'ax.core.risk_measures.RiskMeasure'>, 'RobustSearchSpace': <class 'ax.core.search_space.RobustSearchSpace'>, 'Round': <class 'botorch.models.transforms.input.Round'>, 'ScalarizedObjective': <class 'ax.core.objective.ScalarizedObjective'>, 'SchedulerOptions': <class 'ax.service.utils.scheduler_options.SchedulerOptions'>, 'SearchSpace': <class 'ax.core.search_space.SearchSpace'>, 'SingleDiagnosticBestModelSelector': <class 'ax.modelbridge.best_model_selector.SingleDiagnosticBestModelSelector'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SobolQMCNormalSampler': <class 'botorch.sampling.normal.SobolQMCNormalSampler'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.benchmark_metric.BenchmarkMetric'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.surrogate.SurrogateSpec'>, 'SyntheticRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'ThresholdEarlyStoppingStrategy': <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>, 'Trial': <class 'ax.core.trial.Trial'>, 'TrialStatus': <enum 'TrialStatus'>, 'TrialType': <enum 'TrialType'>, 'WindowsPath': <function pathlib_from_json>, 'WinsorizationConfig': <class 'ax.models.winsorization_config.WinsorizationConfig'>}, class_decoder_registry: dict[str, ~collections.abc.Callable[[dict[str, ~typing.Any]], ~typing.Any]] = {'Type[AcquisitionFunction]': <function class_from_json>, 'Type[Acquisition]': <function class_from_json>, 'Type[InputTransform]': <function input_transform_type_from_json>, 'Type[Kernel]': <function class_from_json>, 'Type[Likelihood]': <function class_from_json>, 'Type[MarginalLogLikelihood]': <function class_from_json>, 'Type[Model]': <function class_from_json>, 'Type[OutcomeTransform]': <function outcome_transform_type_from_json>, 'Type[Transform]': <function transform_type_from_json>, 'Type[torch.nn.Module]': <function class_from_json>, '_DefaultType': <function default_from_json>}) → TransitionCriterion | None[source]¶

Load Ax transition criteria that depend on Trials from JSON.

Since TrialBasedCriterion contain lists of TrialStatus, the json for these criterion needs to be carefully unpacked and re-processed via object_from_json in order to maintain correct typing. We pass in class_ in order to correctly handle all classes which inherit from TrialBasedCriterion (ex: MaxTrials).

ax.storage.json_store.decoders module¶

ax.storage.json_store.decoders.batch_trial_from_json(experiment: core.experiment.Experiment, index: int, trial_type: str | None, status: TrialStatus, time_created: datetime, time_completed: datetime | None, time_staged: datetime | None, time_run_started: datetime | None, abandoned_reason: str | None, run_metadata: dict[str, Any] | None, generator_run_structs: list[GeneratorRunStruct], runner: Runner | None, abandoned_arms_metadata: dict[str, AbandonedArm], num_arms_created: int, status_quo: Arm | None, status_quo_weight_override: float, optimize_for_power: bool | None, failed_reason: str | None = None, ttl_seconds: int | None = None, generation_step_index: int | None = None, properties: dict[str, Any] | None = None, stop_metadata: dict[str, Any] | None = None, lifecycle_stage: LifecycleStage | None = 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.botorch_component_from_json(botorch_class: type[T], json: dict[str, Any]) → T[source]¶

Load any instance of torch.nn.Module or descendants registered in CLASS_DECODER_REGISTRY from state dict.

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.default_from_json(json: dict[str, Any]) → _DefaultType[source]¶

ax.storage.json_store.decoders.input_transform_type_from_json(object_json: dict[str, Any]) → type[InputTransform][source]¶

ax.storage.json_store.decoders.outcome_transform_type_from_json(object_json: dict[str, Any]) → type[OutcomeTransform][source]¶

ax.storage.json_store.decoders.pathlib_from_json(pathsegments: str | Iterable[str]) → Path[source]¶

ax.storage.json_store.decoders.tensor_from_json(json: dict[str, Any]) → Tensor[source]¶

ax.storage.json_store.decoders.tensor_or_size_from_json(json: dict[str, Any]) → Tensor | Size[source]¶

ax.storage.json_store.decoders.transform_type_from_json(object_json: dict[str, Any]) → type[Transform][source]¶

Load the transform type from JSON.

ax.storage.json_store.decoders.trial_from_json(experiment: core.experiment.Experiment, index: int, trial_type: str | None, status: TrialStatus, time_created: datetime, time_completed: datetime | None, time_staged: datetime | None, time_run_started: datetime | None, abandoned_reason: str | None, run_metadata: dict[str, Any] | None, generator_run: GeneratorRun, runner: Runner | None, num_arms_created: int, failed_reason: str | None = None, ttl_seconds: int | None = None, generation_step_index: int | None = None, properties: dict[str, Any] | None = None, stop_metadata: dict[str, Any] | None = 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.