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

Package-level declarations

Types

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data class GetJobIamPolicyResult(val auditConfigs: List<GoogleIamV1__AuditConfigResponse>, val bindings: List<GoogleIamV1__BindingResponse>, val etag: String, val version: Int)
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data class GetJobResult(val createTime: String, val endTime: String, val errorMessage: String, val etag: String, val jobId: String, val jobPosition: String, val labels: Map<String, String>, val predictionInput: GoogleCloudMlV1__PredictionInputResponse, val predictionOutput: GoogleCloudMlV1__PredictionOutputResponse, val startTime: String, val state: String, val trainingInput: GoogleCloudMlV1__TrainingInputResponse, val trainingOutput: GoogleCloudMlV1__TrainingOutputResponse)
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data class GetModelIamPolicyResult(val auditConfigs: List<GoogleIamV1__AuditConfigResponse>, val bindings: List<GoogleIamV1__BindingResponse>, val etag: String, val version: Int)
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data class GetModelResult(val defaultVersion: GoogleCloudMlV1__VersionResponse, val description: String, val etag: String, val labels: Map<String, String>, val name: String, val onlinePredictionConsoleLogging: Boolean, val onlinePredictionLogging: Boolean, val regions: List<String>)
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data class GetStudyResult(val createTime: String, val inactiveReason: String, val name: String, val state: String, val studyConfig: GoogleCloudMlV1__StudyConfigResponse)
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data class GetTrialResult(val clientId: String, val endTime: String, val finalMeasurement: GoogleCloudMlV1__MeasurementResponse, val infeasibleReason: String, val measurements: List<GoogleCloudMlV1__MeasurementResponse>, val name: String, val parameters: List<GoogleCloudMlV1_Trial_ParameterResponse>, val startTime: String, val state: String, val trialInfeasible: Boolean)
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data class GetVersionResult(val acceleratorConfig: GoogleCloudMlV1__AcceleratorConfigResponse, val autoScaling: GoogleCloudMlV1__AutoScalingResponse, val container: GoogleCloudMlV1__ContainerSpecResponse, val createTime: String, val deploymentUri: String, val description: String, val errorMessage: String, val etag: String, val explanationConfig: GoogleCloudMlV1__ExplanationConfigResponse, val framework: String, val isDefault: Boolean, val labels: Map<String, String>, val lastMigrationModelId: String, val lastMigrationTime: String, val lastUseTime: String, val machineType: String, val manualScaling: GoogleCloudMlV1__ManualScalingResponse, val name: String, val packageUris: List<String>, val predictionClass: String, val pythonVersion: String, val requestLoggingConfig: GoogleCloudMlV1__RequestLoggingConfigResponse, val routes: GoogleCloudMlV1__RouteMapResponse, val runtimeVersion: String, val serviceAccount: String, val state: String)
data class GoogleCloudMlV1__AcceleratorConfigResponse(val count: String, val type: String)

Represents a hardware accelerator request config. Note that the AcceleratorConfig can be used in both Jobs and Versions. Learn more about /ml-engine/docs/using-gpus and /ml-engine/docs/machine-types-online-prediction#gpus.

data class GoogleCloudMlV1__AutomatedStoppingConfigResponse(val decayCurveStoppingConfig: GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponse, val medianAutomatedStoppingConfig: GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponse)

Configuration for Automated Early Stopping of Trials. If no implementation_config is set, automated early stopping will not be run.

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data class GoogleCloudMlV1__AutoScalingResponse(val maxNodes: Int, val metrics: List<GoogleCloudMlV1__MetricSpecResponse>, val minNodes: Int)

Options for automatically scaling a model.

data class GoogleCloudMlV1__BuiltInAlgorithmOutputResponse(val framework: String, val modelPath: String, val pythonVersion: String, val runtimeVersion: String)

Represents output related to a built-in algorithm Job.

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data class GoogleCloudMlV1__ContainerPortResponse(val containerPort: Int)

Represents a network port in a single container. This message is a subset of the Kubernetes ContainerPort v1 core specification.

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data class GoogleCloudMlV1__ContainerSpecResponse(val args: List<String>, val command: List<String>, val env: List<GoogleCloudMlV1__EnvVarResponse>, val image: String, val ports: List<GoogleCloudMlV1__ContainerPortResponse>)

Specification of a custom container for serving predictions. This message is a subset of the Kubernetes Container v1 core specification.

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data class GoogleCloudMlV1__DiskConfigResponse(val bootDiskSizeGb: Int, val bootDiskType: String)

Represents the config of disk options.

data class GoogleCloudMlV1__EncryptionConfigResponse(val kmsKeyName: String)

Represents a custom encryption key configuration that can be applied to a resource.

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data class GoogleCloudMlV1__EnvVarResponse(val name: String, val value: String)

Represents an environment variable to be made available in a container. This message is a subset of the Kubernetes EnvVar v1 core specification.

data class GoogleCloudMlV1__ExplanationConfigResponse(val integratedGradientsAttribution: GoogleCloudMlV1__IntegratedGradientsAttributionResponse, val sampledShapleyAttribution: GoogleCloudMlV1__SampledShapleyAttributionResponse, val xraiAttribution: GoogleCloudMlV1__XraiAttributionResponse)

Message holding configuration options for explaining model predictions. There are three feature attribution methods supported for TensorFlow models: integrated gradients, sampled Shapley, and XRAI. /ai-platform/prediction/docs/ai-explanations/overview

data class GoogleCloudMlV1__HyperparameterOutputResponse(val allMetrics: List<GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponse>, val builtInAlgorithmOutput: GoogleCloudMlV1__BuiltInAlgorithmOutputResponse, val endTime: String, val finalMetric: GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponse, val hyperparameters: Map<String, String>, val isTrialStoppedEarly: Boolean, val startTime: String, val state: String, val trialId: String, val webAccessUris: Map<String, String>)

Represents the result of a single hyperparameter tuning trial from a training job. The TrainingOutput object that is returned on successful completion of a training job with hyperparameter tuning includes a list of HyperparameterOutput objects, one for each successful trial.

data class GoogleCloudMlV1__HyperparameterSpecResponse(val algorithm: String, val enableTrialEarlyStopping: Boolean, val goal: String, val hyperparameterMetricTag: String, val maxFailedTrials: Int, val maxParallelTrials: Int, val maxTrials: Int, val params: List<GoogleCloudMlV1__ParameterSpecResponse>, val resumePreviousJobId: String)

Represents a set of hyperparameters to optimize.

data class GoogleCloudMlV1__IntegratedGradientsAttributionResponse(val numIntegralSteps: Int)

Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

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data class GoogleCloudMlV1__ManualScalingResponse(val nodes: Int)

Options for manually scaling a model.

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data class GoogleCloudMlV1__MeasurementResponse(val elapsedTime: String, val metrics: List<GoogleCloudMlV1_Measurement_MetricResponse>, val stepCount: String)

A message representing a measurement.

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data class GoogleCloudMlV1__MetricSpecResponse(val name: String, val target: Int)

MetricSpec contains the specifications to use to calculate the desired nodes count when autoscaling is enabled.

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data class GoogleCloudMlV1__ParameterSpecResponse(val categoricalValues: List<String>, val discreteValues: List<Double>, val maxValue: Double, val minValue: Double, val parameterName: String, val scaleType: String, val type: String)

Represents a single hyperparameter to optimize.

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data class GoogleCloudMlV1__PredictionInputResponse(val batchSize: String, val dataFormat: String, val inputPaths: List<String>, val maxWorkerCount: String, val modelName: String, val outputDataFormat: String, val outputPath: String, val region: String, val runtimeVersion: String, val signatureName: String, val uri: String, val versionName: String)

Represents input parameters for a prediction job.

data class GoogleCloudMlV1__PredictionOutputResponse(val errorCount: String, val nodeHours: Double, val outputPath: String, val predictionCount: String)

Represents results of a prediction job.

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data class GoogleCloudMlV1__ReplicaConfigResponse(val acceleratorConfig: GoogleCloudMlV1__AcceleratorConfigResponse, val containerArgs: List<String>, val containerCommand: List<String>, val diskConfig: GoogleCloudMlV1__DiskConfigResponse, val imageUri: String, val tpuTfVersion: String)

Represents the configuration for a replica in a cluster.

data class GoogleCloudMlV1__RequestLoggingConfigResponse(val bigqueryTableName: String, val samplingPercentage: Double)

Configuration for logging request-response pairs to a BigQuery table. Online prediction requests to a model version and the responses to these requests are converted to raw strings and saved to the specified BigQuery table. Logging is constrained by /bigquery/quotas. If your project exceeds BigQuery quotas or limits, AI Platform Prediction does not log request-response pairs, but it continues to serve predictions. If you are using /ml-engine/docs/continuous-evaluation/, you do not need to specify this configuration manually. Setting up continuous evaluation automatically enables logging of request-response pairs.

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data class GoogleCloudMlV1__RouteMapResponse(val health: String, val predict: String)

Specifies HTTP paths served by a custom container. AI Platform Prediction sends requests to these paths on the container; the custom container must run an HTTP server that responds to these requests with appropriate responses. Read /ai-platform/prediction/docs/custom-container-requirements for details on how to create your container image to meet these requirements.

data class GoogleCloudMlV1__SampledShapleyAttributionResponse(val numPaths: Int)

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

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data class GoogleCloudMlV1__SchedulingResponse(val maxRunningTime: String, val maxWaitTime: String, val priority: Int)

All parameters related to scheduling of training jobs.

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data class GoogleCloudMlV1__StudyConfigResponse(val algorithm: String, val automatedStoppingConfig: GoogleCloudMlV1__AutomatedStoppingConfigResponse, val metrics: List<GoogleCloudMlV1_StudyConfig_MetricSpecResponse>, val parameters: List<GoogleCloudMlV1_StudyConfig_ParameterSpecResponse>)

Represents configuration of a study.

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data class GoogleCloudMlV1__TrainingInputResponse(val args: List<String>, val enableWebAccess: Boolean, val encryptionConfig: GoogleCloudMlV1__EncryptionConfigResponse, val evaluatorConfig: GoogleCloudMlV1__ReplicaConfigResponse, val evaluatorCount: String, val evaluatorType: String, val hyperparameters: GoogleCloudMlV1__HyperparameterSpecResponse, val jobDir: String, val masterConfig: GoogleCloudMlV1__ReplicaConfigResponse, val masterType: String, val network: String, val packageUris: List<String>, val parameterServerConfig: GoogleCloudMlV1__ReplicaConfigResponse, val parameterServerCount: String, val parameterServerType: String, val pythonModule: String, val pythonVersion: String, val region: String, val runtimeVersion: String, val scaleTier: String, val scheduling: GoogleCloudMlV1__SchedulingResponse, val serviceAccount: String, val useChiefInTfConfig: Boolean, val workerConfig: GoogleCloudMlV1__ReplicaConfigResponse, val workerCount: String, val workerType: String)

Represents input parameters for a training job. When using the gcloud command to submit your training job, you can specify the input parameters as command-line arguments and/or in a YAML configuration file referenced from the --config command-line argument. For details, see the guide to /ai-platform/training/docs/training-jobs.

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data class GoogleCloudMlV1__TrainingOutputResponse(val builtInAlgorithmOutput: GoogleCloudMlV1__BuiltInAlgorithmOutputResponse, val completedTrialCount: String, val consumedMLUnits: Double, val hyperparameterMetricTag: String, val isBuiltInAlgorithmJob: Boolean, val isHyperparameterTuningJob: Boolean, val trials: List<GoogleCloudMlV1__HyperparameterOutputResponse>, val webAccessUris: Map<String, String>)

Represents results of a training job. Output only.

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data class GoogleCloudMlV1__VersionResponse(val acceleratorConfig: GoogleCloudMlV1__AcceleratorConfigResponse, val autoScaling: GoogleCloudMlV1__AutoScalingResponse, val container: GoogleCloudMlV1__ContainerSpecResponse, val createTime: String, val deploymentUri: String, val description: String, val errorMessage: String, val etag: String, val explanationConfig: GoogleCloudMlV1__ExplanationConfigResponse, val framework: String, val isDefault: Boolean, val labels: Map<String, String>, val lastMigrationModelId: String, val lastMigrationTime: String, val lastUseTime: String, val machineType: String, val manualScaling: GoogleCloudMlV1__ManualScalingResponse, val name: String, val packageUris: List<String>, val predictionClass: String, val pythonVersion: String, val requestLoggingConfig: GoogleCloudMlV1__RequestLoggingConfigResponse, val routes: GoogleCloudMlV1__RouteMapResponse, val runtimeVersion: String, val serviceAccount: String, val state: String)

Represents a version of the model. Each version is a trained model deployed in the cloud, ready to handle prediction requests. A model can have multiple versions. You can get information about all of the versions of a given model by calling projects.models.versions.list.

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data class GoogleCloudMlV1__XraiAttributionResponse(val numIntegralSteps: Int)

Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.

data class GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponse(val useElapsedTime: Boolean)

The median automated stopping rule stops a pending trial if the trial's best objective_value is strictly below the median 'performance' of all completed trials reported up to the trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the trial in each measurement.

data class GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponse(val objectiveValue: Double, val trainingStep: String)

An observed value of a metric.

data class GoogleCloudMlV1_Measurement_MetricResponse(val metric: String, val value: Double)

A message representing a metric in the measurement.

data class GoogleCloudMlV1_StudyConfig_MetricSpecResponse(val goal: String, val metric: String)

Represents a metric to optimize.

data class GoogleCloudMlV1_StudyConfig_ParameterSpecResponse(val categoricalValueSpec: GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponse, val childParameterSpecs: List<GoogleCloudMlV1_StudyConfig_ParameterSpecResponse>, val discreteValueSpec: GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponse, val doubleValueSpec: GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponse, val integerValueSpec: GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponse, val parameter: String, val parentCategoricalValues: GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponse, val parentDiscreteValues: GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponse, val parentIntValues: GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponse, val scaleType: String, val type: String)

Represents a single parameter to optimize.

data class GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponse(val values: List<String>)

Represents the spec to match categorical values from parent parameter.

data class GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponse(val values: List<Double>)

Represents the spec to match discrete values from parent parameter.

data class GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponse(val values: List<String>)

Represents the spec to match integer values from parent parameter.

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data class GoogleCloudMlV1_Trial_ParameterResponse(val floatValue: Double, val intValue: String, val parameter: String, val stringValue: String)

A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.

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data class GoogleIamV1__AuditConfigResponse(val auditLogConfigs: List<GoogleIamV1__AuditLogConfigResponse>, val service: String)

Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both allServices and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { "audit_configs": [ { "service": "allServices", "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": "user:jose@example.com" }, { "log_type": "DATA_WRITE" }, { "log_type": "ADMIN_READ" } ] }, { "service": "sampleservice.googleapis.com", "audit_log_configs": [ { "log_type": "DATA_READ" }, { "log_type": "DATA_WRITE", "exempted_members": "user:aliya@example.com" } ] } ] } For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts jose@example.com from DATA_READ logging, and aliya@example.com from DATA_WRITE logging.

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data class GoogleIamV1__AuditLogConfigResponse(val exemptedMembers: List<String>, val logType: String)

Provides the configuration for logging a type of permissions. Example: { "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": "user:jose@example.com" }, { "log_type": "DATA_WRITE" } ] } This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting jose@example.com from DATA_READ logging.

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data class GoogleIamV1__BindingResponse(val condition: GoogleType__ExprResponse, val members: List<String>, val role: String)

Associates members, or principals, with a role.

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data class GoogleType__ExprResponse(val description: String, val expression: String, val location: String, val title: String)

Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.