pulumi-google-native-kotlin/com.pulumi.googlenative.ml.v1.kotlin.enums

Package-level declarations

Types

enum GoogleCloudMlV1__AcceleratorConfigType : Enum<GoogleCloudMlV1__AcceleratorConfigType> , ConvertibleToJava<GoogleCloudMlV1__AcceleratorConfigType>

The type of accelerator to use.

GoogleCloudMlV1__HyperparameterSpecAlgorithm

enum GoogleCloudMlV1__HyperparameterSpecAlgorithm : Enum<GoogleCloudMlV1__HyperparameterSpecAlgorithm> , ConvertibleToJava<GoogleCloudMlV1__HyperparameterSpecAlgorithm>

Optional. The search algorithm specified for the hyperparameter tuning job. Uses the default AI Platform hyperparameter tuning algorithm if unspecified.

GoogleCloudMlV1__HyperparameterSpecGoal

enum GoogleCloudMlV1__HyperparameterSpecGoal : Enum<GoogleCloudMlV1__HyperparameterSpecGoal> , ConvertibleToJava<GoogleCloudMlV1__HyperparameterSpecGoal>

Required. The type of goal to use for tuning. Available types are MAXIMIZE and MINIMIZE. Defaults to MAXIMIZE.

GoogleCloudMlV1__MetricSpecName

enum GoogleCloudMlV1__MetricSpecName : Enum<GoogleCloudMlV1__MetricSpecName> , ConvertibleToJava<GoogleCloudMlV1__MetricSpecName>

metric name.

GoogleCloudMlV1__ParameterSpecScaleType

enum GoogleCloudMlV1__ParameterSpecScaleType : Enum<GoogleCloudMlV1__ParameterSpecScaleType> , ConvertibleToJava<GoogleCloudMlV1__ParameterSpecScaleType>

Optional. How the parameter should be scaled to the hypercube. Leave unset for categorical parameters. Some kind of scaling is strongly recommended for real or integral parameters (e.g., UNIT_LINEAR_SCALE).

GoogleCloudMlV1__ParameterSpecType

enum GoogleCloudMlV1__ParameterSpecType : Enum<GoogleCloudMlV1__ParameterSpecType> , ConvertibleToJava<GoogleCloudMlV1__ParameterSpecType>

Required. The type of the parameter.

GoogleCloudMlV1__PredictionInputDataFormat

enum GoogleCloudMlV1__PredictionInputDataFormat : Enum<GoogleCloudMlV1__PredictionInputDataFormat> , ConvertibleToJava<GoogleCloudMlV1__PredictionInputDataFormat>

Required. The format of the input data files.

GoogleCloudMlV1__PredictionInputOutputDataFormat

enum GoogleCloudMlV1__PredictionInputOutputDataFormat : Enum<GoogleCloudMlV1__PredictionInputOutputDataFormat> , ConvertibleToJava<GoogleCloudMlV1__PredictionInputOutputDataFormat>

Optional. Format of the output data files, defaults to JSON.

GoogleCloudMlV1__StudyConfigAlgorithm

enum GoogleCloudMlV1__StudyConfigAlgorithm : Enum<GoogleCloudMlV1__StudyConfigAlgorithm> , ConvertibleToJava<GoogleCloudMlV1__StudyConfigAlgorithm>

The search algorithm specified for the study.

GoogleCloudMlV1__TrainingInputScaleTier

enum GoogleCloudMlV1__TrainingInputScaleTier : Enum<GoogleCloudMlV1__TrainingInputScaleTier> , ConvertibleToJava<GoogleCloudMlV1__TrainingInputScaleTier>

Required. Specifies the machine types, the number of replicas for workers and parameter servers.

GoogleCloudMlV1_StudyConfig_MetricSpecGoal

enum GoogleCloudMlV1_StudyConfig_MetricSpecGoal : Enum<GoogleCloudMlV1_StudyConfig_MetricSpecGoal> , ConvertibleToJava<GoogleCloudMlV1_StudyConfig_MetricSpecGoal>

Required. The optimization goal of the metric.

GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType

enum GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType : Enum<GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType> , ConvertibleToJava<GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType>

How the parameter should be scaled. Leave unset for categorical parameters.

GoogleCloudMlV1_StudyConfig_ParameterSpecType

enum GoogleCloudMlV1_StudyConfig_ParameterSpecType : Enum<GoogleCloudMlV1_StudyConfig_ParameterSpecType> , ConvertibleToJava<GoogleCloudMlV1_StudyConfig_ParameterSpecType>

Required. The type of the parameter.

GoogleIamV1__AuditLogConfigLogType

enum GoogleIamV1__AuditLogConfigLogType : Enum<GoogleIamV1__AuditLogConfigLogType> , ConvertibleToJava<GoogleIamV1__AuditLogConfigLogType>

The log type that this config enables.

TrialState

enum TrialState : Enum<TrialState> , ConvertibleToJava<TrialState>

The detailed state of a trial.

VersionFramework

enum VersionFramework : Enum<VersionFramework> , ConvertibleToJava<VersionFramework>

Optional. The machine learning framework AI Platform uses to train this version of the model. Valid values are TENSORFLOW, SCIKIT_LEARN, XGBOOST. If you do not specify a framework, AI Platform will analyze files in the deployment_uri to determine a framework. If you choose SCIKIT_LEARN or XGBOOST, you must also set the runtime version of the model to 1.4 or greater. Do not specify a framework if you're deploying a /ai-platform/prediction/docs/custom-prediction-routines or if you're using a /ai-platform/prediction/docs/use-custom-container.