ax.storage¶

ax.storage.json_store.decoder module¶

ax.storage.json_store.decoder.ax_class_from_json_dict(_class: ~typing.Type, object_json: ~typing.Dict[str, ~typing.Any], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → 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: ~typing.Dict[str, ~typing.Any], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → Dict[int, OrderedDict[int, Data]][source]¶

Load Ax Data from JSON.

ax.storage.json_store.decoder.experiment_from_json(object_json: ~typing.Dict[str, ~typing.Any], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → Experiment[source]¶

Load Ax Experiment from JSON.

ax.storage.json_store.decoder.generation_step_from_json(generation_step_json: ~typing.Dict[str, ~typing.Any], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → GenerationStep[source]¶

Load generation step from JSON.

ax.storage.json_store.decoder.generation_strategy_from_json(generation_strategy_json: ~typing.Dict[str, ~typing.Any], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}, experiment: ~typing.Optional[~ax.core.experiment.Experiment] = None) → GenerationStrategy[source]¶

Load generation strategy from JSON.

ax.storage.json_store.decoder.generator_run_from_json(object_json: ~typing.Dict[str, ~typing.Any], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → GeneratorRun[source]¶

Load Ax GeneratorRun from JSON.

ax.storage.json_store.decoder.get_input_transform_json_components(input_transforms_json: ~typing.Optional[~typing.List[~typing.Dict[str, ~typing.Any]]], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → Tuple[Optional[List[Dict[str, Any]]], Optional[Dict[str, Any]]][source]¶

ax.storage.json_store.decoder.get_outcome_transform_json_components(outcome_transforms_json: ~typing.Optional[~typing.List[~typing.Dict[str, ~typing.Any]]], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → Tuple[Optional[List[Dict[str, Any]]], Optional[Dict[str, Any]]][source]¶

ax.storage.json_store.decoder.multi_type_experiment_from_json(object_json: ~typing.Dict[str, ~typing.Any], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → MultiTypeExperiment[source]¶

Load AE MultiTypeExperiment from JSON.

ax.storage.json_store.decoder.object_from_json(object_json: ~typing.Any, decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → Any[source]¶

Recursively load objects from a JSON-serializable dictionary.

ax.storage.json_store.decoder.parameter_constraints_from_json(parameter_constraint_json: ~typing.List[~typing.Dict[str, ~typing.Any]], parameters: ~typing.List[~ax.core.parameter.Parameter], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → 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: ~typing.Dict[str, ~typing.Any], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → 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: ~typing.Dict[str, ~typing.Any], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → Surrogate[source]¶

ax.storage.json_store.decoder.transition_criteria_from_json(transition_criteria_json: ~typing.List[~typing.Dict[str, ~typing.Any]], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → Optional[List[TransitionCriterion]][source]¶

Load Ax TransitionCriteria from JSON.

This function is necessary due to the loading of TrialStatus in some, but not all, TransitionCriterion.

ax.storage.json_store.decoder.trials_from_json(experiment: ~ax.core.experiment.Experiment, trials_json: ~typing.Dict[str, ~typing.Any], decoder_registry: ~typing.Dict[str, ~typing.Type] = {'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'>, 'AugmentedBraninMetric': <class 'ax.metrics.branin.AugmentedBraninMetric'>, 'AugmentedHartmann6Metric': <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>, 'BatchTrial': <class 'ax.core.batch_trial.BatchTrial'>, 'BenchmarkMethod': <class 'ax.benchmark.benchmark_method.BenchmarkMethod'>, 'BenchmarkProblem': <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>, 'BenchmarkResult': <class 'ax.benchmark.benchmark_result.BenchmarkResult'>, 'BoTorchModel': <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>, 'BotorchTestProblemMetric': <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>, 'BotorchTestProblemRunner': <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>, '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'>, 'DictLookupMetric': <class 'ax.metrics.dict_lookup.DictLookupMetric'>, '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'>, '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'>, 'Interval': <class 'gpytorch.constraints.constraints.Interval'>, 'JenattonMetric': <class 'ax.metrics.jenatton.JenattonMetric'>, 'L2NormMetric': <class 'ax.metrics.l2norm.L2NormMetric'>, 'ListSurrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'MapData': <class 'ax.core.map_data.MapData'>, 'MapKeyInfo': <class 'ax.core.map_data.MapKeyInfo'>, 'MapMetric': <class 'ax.core.map_metric.MapMetric'>, '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'>, 'Models': <enum 'Models'>, 'MultiObjective': <class 'ax.core.objective.MultiObjective'>, 'MultiObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>, 'MultiObjectiveOptimizationConfig': <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>, 'MultiTypeExperiment': <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>, 'NegativeBraninMetric': <class 'ax.metrics.branin.NegativeBraninMetric'>, 'NoisyFunctionMetric': <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>, '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>, 'PyTorchCNNMetric': <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>, 'PyTorchCNNTorchvisionBenchmarkProblem': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>, 'PyTorchCNNTorchvisionRunner': <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>, 'RangeParameter': <class 'ax.core.parameter.RangeParameter'>, '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'>, 'SingleObjectiveBenchmarkProblem': <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>, 'SklearnDataset': <enum 'SklearnDataset'>, 'SklearnMetric': <class 'ax.metrics.sklearn.SklearnMetric'>, 'SklearnModelType': <enum 'SklearnModelType'>, 'SumConstraint': <class 'ax.core.parameter_constraint.SumConstraint'>, 'Surrogate': <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>, 'SurrogateMetric': <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>, 'SurrogateRunner': <class 'ax.runners.synthetic.SyntheticRunner'>, 'SurrogateSpec': <class 'ax.models.torch.botorch_modular.model.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: ~typing.Dict[str, ~typing.Callable[[~typing.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[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>}) → Dict[int, BaseTrial][source]¶

Load Ax Trials from JSON.

ax.storage.json_store.decoders module¶

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

Load Ax BatchTrial from JSON.

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

ax.storage.json_store.decoders.botorch_component_from_json(botorch_class: Any, json: Dict[str, Any]) → Type[Any][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.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: Union[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]) → Union[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: Optional[str], status: TrialStatus, time_created: datetime, time_completed: Optional[datetime], time_staged: Optional[datetime], time_run_started: Optional[datetime], abandoned_reason: Optional[str], run_metadata: Optional[Dict[str, Any]], generator_run: GeneratorRun, runner: Optional[Runner], num_arms_created: int, failed_reason: Optional[str] = None, ttl_seconds: Optional[int] = None, generation_step_index: Optional[int] = None, properties: Optional[Dict[str, Any]] = None, stop_metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Trial[source]¶

Load Ax trial from JSON.

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

ax.storage.json_store.encoder module¶

ax.storage.json_store.encoder.object_to_json(obj: ~typing.Any, encoder_registry: ~typing.Dict[~typing.Type, ~typing.Callable[[~typing.Any], ~typing.Dict[str, ~typing.Any]]] = {<class 'ax.core.arm.Arm'>: <function arm_to_dict>, <class 'ax.early_stopping.strategies.logical.AndEarlyStoppingStrategy'>: <function logical_early_stopping_strategy_to_dict>, <class 'ax.metrics.branin.AugmentedBraninMetric'>: <function metric_to_dict>, <class 'ax.metrics.hartmann6.AugmentedHartmann6Metric'>: <function metric_to_dict>, <class 'ax.core.batch_trial.BatchTrial'>: <function batch_to_dict>, <class 'ax.benchmark.benchmark_problem.BenchmarkProblem'>: <function benchmark_problem_to_dict>, <class 'ax.models.torch.botorch_modular.model.BoTorchModel'>: <function botorch_model_to_dict>, <class 'ax.metrics.botorch_test_problem.BotorchTestProblemMetric'>: <function metric_to_dict>, <class 'ax.runners.botorch_test_problem.BotorchTestProblemRunner'>: <function runner_to_dict>, <class 'ax.metrics.branin.BraninMetric'>: <function metric_to_dict>, <class 'ax.metrics.branin_map.BraninTimestampMapMetric'>: <function metric_to_dict>, <class 'botorch.models.transforms.input.ChainedInputTransform'>: <function botorch_component_to_dict>, <class 'ax.core.parameter.ChoiceParameter'>: <function choice_parameter_to_dict>, <class 'ax.core.data.Data'>: <function data_to_dict>, <class 'ax.metrics.dict_lookup.DictLookupMetric'>: <function metric_to_dict>, <class 'ax.core.experiment.Experiment'>: <function experiment_to_dict>, <class 'ax.metrics.factorial.FactorialMetric'>: <function metric_to_dict>, <class 'ax.core.parameter.FixedParameter'>: <function fixed_parameter_to_dict>, <class 'gpytorch.priors.torch_priors.GammaPrior'>: <function botorch_component_to_dict>, <class 'ax.modelbridge.generation_node.GenerationStep'>: <function generation_step_to_dict>, <class 'ax.modelbridge.generation_strategy.GenerationStrategy'>: <function generation_strategy_to_dict>, <class 'ax.core.generator_run.GeneratorRun'>: <function generator_run_to_dict>, <class 'ax.metrics.hartmann6.Hartmann6Metric'>: <function metric_to_dict>, <class 'ax.global_stopping.strategies.improvement.ImprovementGlobalStoppingStrategy'>: <function improvement_global_stopping_strategy_to_dict>, <class 'gpytorch.constraints.constraints.Interval'>: <function botorch_component_to_dict>, <class 'ax.metrics.jenatton.JenattonMetric'>: <function metric_to_dict>, <class 'ax.metrics.l2norm.L2NormMetric'>: <function metric_to_dict>, <class 'ax.core.map_data.MapData'>: <function map_data_to_dict>, <class 'ax.core.map_data.MapKeyInfo'>: <function map_key_info_to_dict>, <class 'ax.core.map_metric.MapMetric'>: <function metric_to_dict>, <class 'ax.modelbridge.transition_criterion.MaxGenerationParallelism'>: <function transition_criterion_to_dict>, <class 'ax.modelbridge.transition_criterion.MaxTrials'>: <function transition_criterion_to_dict>, <class 'ax.core.metric.Metric'>: <function metric_to_dict>, <class 'ax.modelbridge.transition_criterion.MinTrials'>: <function transition_criterion_to_dict>, <class 'ax.modelbridge.transition_criterion.MinimumTrialsInStatus'>: <function transition_criterion_to_dict>, <class 'ax.modelbridge.transition_criterion.MinimumPreferenceOccurances'>: <function transition_criterion_to_dict>, <class 'ax.core.objective.MultiObjective'>: <function multi_objective_to_dict>, <class 'ax.benchmark.benchmark_problem.MultiObjectiveBenchmarkProblem'>: <function multi_objective_benchmark_problem_to_dict>, <class 'ax.core.optimization_config.MultiObjectiveOptimizationConfig'>: <function multi_objective_optimization_config_to_dict>, <class 'ax.core.multi_type_experiment.MultiTypeExperiment'>: <function multi_type_experiment_to_dict>, <class 'botorch.models.transforms.input.Normalize'>: <function botorch_component_to_dict>, <class 'ax.early_stopping.strategies.percentile.PercentileEarlyStoppingStrategy'>: <function percentile_early_stopping_strategy_to_dict>, <class 'ax.metrics.sklearn.SklearnMetric'>: <function metric_to_dict>, <class 'ax.metrics.chemistry.ChemistryMetric'>: <function metric_to_dict>, <class 'ax.metrics.branin.NegativeBraninMetric'>: <function metric_to_dict>, <class 'ax.metrics.noisy_function.NoisyFunctionMetric'>: <function metric_to_dict>, <class 'ax.core.objective.Objective'>: <function objective_to_dict>, <class 'ax.core.outcome_constraint.ObjectiveThreshold'>: <function outcome_constraint_to_dict>, <class 'ax.core.optimization_config.OptimizationConfig'>: <function optimization_config_to_dict>, <class 'ax.early_stopping.strategies.logical.OrEarlyStoppingStrategy'>: <function logical_early_stopping_strategy_to_dict>, <class 'ax.core.parameter_constraint.OrderConstraint'>: <function order_parameter_constraint_to_dict>, <class 'ax.core.outcome_constraint.OutcomeConstraint'>: <function outcome_constraint_to_dict>, <class 'ax.core.parameter_constraint.ParameterConstraint'>: <function parameter_constraint_to_dict>, <class 'ax.core.parameter_distribution.ParameterDistribution'>: <function parameter_distribution_to_dict>, <class 'pathlib.Path'>: <function pathlib_to_dict>, <class 'pathlib.PurePath'>: <function pathlib_to_dict>, <class 'pathlib.PosixPath'>: <function pathlib_to_dict>, <class 'pathlib.WindowsPath'>: <function pathlib_to_dict>, <class 'pathlib.PurePosixPath'>: <function pathlib_to_dict>, <class 'pathlib.PureWindowsPath'>: <function pathlib_to_dict>, <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionBenchmarkProblem'>: <function pytorch_cnn_torchvision_benchmark_problem_to_dict>, <class 'ax.benchmark.problems.hpo.pytorch_cnn.PyTorchCNNMetric'>: <function metric_to_dict>, <class 'ax.benchmark.problems.hpo.torchvision.PyTorchCNNTorchvisionRunner'>: <function runner_to_dict>, <class 'ax.core.parameter.RangeParameter'>: <function range_parameter_to_dict>, <class 'ax.core.risk_measures.RiskMeasure'>: <function risk_measure_to_dict>, <class 'ax.core.search_space.RobustSearchSpace'>: <function robust_search_space_to_dict>, <class 'botorch.models.transforms.input.Round'>: <function botorch_component_to_dict>, <class 'ax.core.objective.ScalarizedObjective'>: <function scalarized_objective_to_dict>, <class 'ax.core.search_space.SearchSpace'>: <function search_space_to_dict>, <class 'ax.benchmark.benchmark_problem.SingleObjectiveBenchmarkProblem'>: <function single_objective_benchmark_problem_to_dict>, <class 'ax.core.search_space.HierarchicalSearchSpace'>: <function search_space_to_dict>, <class 'ax.core.parameter_constraint.SumConstraint'>: <function sum_parameter_constraint_to_dict>, <class 'ax.models.torch.botorch_modular.surrogate.Surrogate'>: <function surrogate_to_dict>, <class 'ax.benchmark.problems.surrogate.SurrogateMetric'>: <function metric_to_dict>, <class 'ax.benchmark.problems.surrogate.SurrogateRunner'>: <function runner_to_dict>, <class 'ax.runners.synthetic.SyntheticRunner'>: <function runner_to_dict>, <class 'ax.early_stopping.strategies.threshold.ThresholdEarlyStoppingStrategy'>: <function threshold_early_stopping_strategy_to_dict>, <class 'ax.core.trial.Trial'>: <function trial_to_dict>, <class 'ax.core.observation.ObservationFeatures'>: <function observation_features_to_dict>, <class 'ax.models.winsorization_config.WinsorizationConfig'>: <function winsorization_config_to_dict>}, class_encoder_registry: ~typing.Dict[~typing.Type, ~typing.Callable[[~typing.Any], ~typing.Dict[str, ~typing.Any]]] = {<class 'ax.models.torch.botorch_modular.acquisition.Acquisition'>: <function botorch_modular_to_dict>, <class 'botorch.acquisition.acquisition.AcquisitionFunction'>: <function botorch_modular_to_dict>, <class 'gpytorch.likelihoods.likelihood.Likelihood'>: <function botorch_modular_to_dict>, <class 'torch.nn.modules.module.Module'>: <function botorch_modular_to_dict>, <class 'gpytorch.mlls.marginal_log_likelihood.MarginalLogLikelihood'>: <function botorch_modular_to_dict>, <class 'botorch.models.model.Model'>: <function botorch_modular_to_dict>, <class 'ax.modelbridge.transforms.base.Transform'>: <function transform_type_to_dict>}) → Any[source]¶

Convert an Ax object to a JSON-serializable dictionary.

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

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

ax.storage.json_store.encoders module¶

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

Convert Ax arm to a dictionary.

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

Convert Ax batch to a dictionary.

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

Convert Ax benchmark problem to a dictionary.

ax.storage.json_store.encoders.botorch_component_to_dict(input_obj: Any) → Dict[str, Any][source]¶

ax.storage.json_store.encoders.botorch_input_transform_to_init_args(input_transform: InputTransform) → Dict[str, Any][source]¶

Extract the init kwargs from an input transform.

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

Convert Ax model to a dictionary.

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

Convert any class to a dictionary.

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

Convert Ax choice parameter to a dictionary.

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

Convert Ax data to a dictionary.

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

Convert Ax experiment to a dictionary.

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

Convert Ax fixed parameter to a dictionary.

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

Converts Ax generation step to a dictionary.

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

Converts Ax generation strategy to a dictionary.

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

Convert Ax generator run to a dictionary.

ax.storage.json_store.encoders.improvement_global_stopping_strategy_to_dict(gss: ImprovementGlobalStoppingStrategy) → Dict[str, Any][source]¶

Convert ImprovementGlobalStoppingStrategy to a dictionary.

ax.storage.json_store.encoders.logical_early_stopping_strategy_to_dict(strategy: LogicalEarlyStoppingStrategy) → Dict[str, Any][source]¶

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

Convert Ax map data to a dictionary.

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

Convert Ax map data metadata to a dictionary.

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

Convert Ax metric to a dictionary.

ax.storage.json_store.encoders.multi_objective_benchmark_problem_to_dict(moo_benchmark_problem: MultiObjectiveBenchmarkProblem) → Dict[str, Any][source]¶

Convert Ax multi-objective benchmark problem to a dictionary.

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

Convert Ax optimization config to a dictionary.

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

Convert Ax objective to a dictionary.

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

Convert AE multitype experiment to a dictionary.

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

Convert Ax objective to a dictionary.

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

Converts Ax observation features to a dictionary

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

Convert Ax optimization config to a dictionary.

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

Convert Ax order parameter constraint to a dictionary.

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

Convert Ax outcome constraint to a dictionary.