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Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

google-native.aiplatform/v1.getDataLabelingJob

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Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

    Gets a DataLabelingJob.

    Using getDataLabelingJob

    Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.

    function getDataLabelingJob(args: GetDataLabelingJobArgs, opts?: InvokeOptions): Promise<GetDataLabelingJobResult>
function getDataLabelingJobOutput(args: GetDataLabelingJobOutputArgs, opts?: InvokeOptions): Output<GetDataLabelingJobResult>
    def get_data_labeling_job(data_labeling_job_id: Optional[str] = None,
                          location: Optional[str] = None,
                          project: Optional[str] = None,
                          opts: Optional[InvokeOptions] = None) -> GetDataLabelingJobResult
def get_data_labeling_job_output(data_labeling_job_id: Optional[pulumi.Input[str]] = None,
                          location: Optional[pulumi.Input[str]] = None,
                          project: Optional[pulumi.Input[str]] = None,
                          opts: Optional[InvokeOptions] = None) -> Output[GetDataLabelingJobResult]
    func LookupDataLabelingJob(ctx *Context, args *LookupDataLabelingJobArgs, opts ...InvokeOption) (*LookupDataLabelingJobResult, error)
func LookupDataLabelingJobOutput(ctx *Context, args *LookupDataLabelingJobOutputArgs, opts ...InvokeOption) LookupDataLabelingJobResultOutput

    > Note: This function is named LookupDataLabelingJob in the Go SDK.

    public static class GetDataLabelingJob 
{
    public static Task<GetDataLabelingJobResult> InvokeAsync(GetDataLabelingJobArgs args, InvokeOptions? opts = null)
    public static Output<GetDataLabelingJobResult> Invoke(GetDataLabelingJobInvokeArgs args, InvokeOptions? opts = null)
}
    public static CompletableFuture<GetDataLabelingJobResult> getDataLabelingJob(GetDataLabelingJobArgs args, InvokeOptions options)
public static Output<GetDataLabelingJobResult> getDataLabelingJob(GetDataLabelingJobArgs args, InvokeOptions options)

    fn::invoke:
  function: google-native:aiplatform/v1:getDataLabelingJob
  arguments:
    # arguments dictionary

    The following arguments are supported:

    getDataLabelingJob Result

    The following output properties are available:

    ActiveLearningConfig Pulumi.GoogleNative.Aiplatform.V1.Outputs.GoogleCloudAiplatformV1ActiveLearningConfigResponse
    Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
    AnnotationLabels Dictionary<string, string>
    Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
    CreateTime string
    Timestamp when this DataLabelingJob was created.
    CurrentSpend Pulumi.GoogleNative.Aiplatform.V1.Outputs.GoogleTypeMoneyResponse
    Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.
    Datasets List<string>
    Dataset resource names. Right now we only support labeling from a single Dataset. Format: projects/{project}/locations/{location}/datasets/{dataset}
    DisplayName string
    The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.
    EncryptionSpec Pulumi.GoogleNative.Aiplatform.V1.Outputs.GoogleCloudAiplatformV1EncryptionSpecResponse
    Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.
    Error Pulumi.GoogleNative.Aiplatform.V1.Outputs.GoogleRpcStatusResponse
    DataLabelingJob errors. It is only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
    Inputs object
    Input config parameters for the DataLabelingJob.
    InputsSchemaUri string
    Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.
    InstructionUri string
    The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.
    LabelerCount int
    Number of labelers to work on each DataItem.
    LabelingProgress int
    Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.
    Labels Dictionary<string, string>
    The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title.
    Name string
    Resource name of the DataLabelingJob.
    SpecialistPools List<string>
    The SpecialistPools' resource names associated with this job.
    State string
    The detailed state of the job.
    UpdateTime string
    Timestamp when this DataLabelingJob was updated most recently.
    ActiveLearningConfig GoogleCloudAiplatformV1ActiveLearningConfigResponse
    Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
    AnnotationLabels map[string]string
    Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
    CreateTime string
    Timestamp when this DataLabelingJob was created.
    CurrentSpend GoogleTypeMoneyResponse
    Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.
    Datasets []string
    Dataset resource names. Right now we only support labeling from a single Dataset. Format: projects/{project}/locations/{location}/datasets/{dataset}
    DisplayName string
    The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.
    EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse
    Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.
    Error GoogleRpcStatusResponse
    DataLabelingJob errors. It is only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
    Inputs interface{}
    Input config parameters for the DataLabelingJob.
    InputsSchemaUri string
    Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.
    InstructionUri string
    The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.
    LabelerCount int
    Number of labelers to work on each DataItem.
    LabelingProgress int
    Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.
    Labels map[string]string
    The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title.
    Name string
    Resource name of the DataLabelingJob.
    SpecialistPools []string
    The SpecialistPools' resource names associated with this job.
    State string
    The detailed state of the job.
    UpdateTime string
    Timestamp when this DataLabelingJob was updated most recently.
    activeLearningConfig GoogleCloudAiplatformV1ActiveLearningConfigResponse
    Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
    annotationLabels Map<String,String>
    Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
    createTime String
    Timestamp when this DataLabelingJob was created.
    currentSpend GoogleTypeMoneyResponse
    Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.
    datasets List<String>
    Dataset resource names. Right now we only support labeling from a single Dataset. Format: projects/{project}/locations/{location}/datasets/{dataset}
    displayName String
    The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.
    encryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse
    Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.
    error GoogleRpcStatusResponse
    DataLabelingJob errors. It is only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
    inputs Object
    Input config parameters for the DataLabelingJob.
    inputsSchemaUri String
    Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.
    instructionUri String
    The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.
    labelerCount Integer
    Number of labelers to work on each DataItem.
    labelingProgress Integer
    Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.
    labels Map<String,String>
    The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title.
    name String
    Resource name of the DataLabelingJob.
    specialistPools List<String>
    The SpecialistPools' resource names associated with this job.
    state String
    The detailed state of the job.
    updateTime String
    Timestamp when this DataLabelingJob was updated most recently.
    activeLearningConfig GoogleCloudAiplatformV1ActiveLearningConfigResponse
    Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
    annotationLabels {[key: string]: string}
    Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
    createTime string
    Timestamp when this DataLabelingJob was created.
    currentSpend GoogleTypeMoneyResponse
    Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.
    datasets string[]
    Dataset resource names. Right now we only support labeling from a single Dataset. Format: projects/{project}/locations/{location}/datasets/{dataset}
    displayName string
    The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.
    encryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse
    Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.
    error GoogleRpcStatusResponse
    DataLabelingJob errors. It is only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
    inputs any
    Input config parameters for the DataLabelingJob.
    inputsSchemaUri string
    Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.
    instructionUri string
    The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.
    labelerCount number
    Number of labelers to work on each DataItem.
    labelingProgress number
    Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.
    labels {[key: string]: string}
    The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title.
    name string
    Resource name of the DataLabelingJob.
    specialistPools string[]
    The SpecialistPools' resource names associated with this job.
    state string
    The detailed state of the job.
    updateTime string
    Timestamp when this DataLabelingJob was updated most recently.
    active_learning_config GoogleCloudAiplatformV1ActiveLearningConfigResponse
    Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
    annotation_labels Mapping[str, str]
    Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
    create_time str
    Timestamp when this DataLabelingJob was created.
    current_spend GoogleTypeMoneyResponse
    Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.
    datasets Sequence[str]
    Dataset resource names. Right now we only support labeling from a single Dataset. Format: projects/{project}/locations/{location}/datasets/{dataset}
    display_name str
    The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.
    encryption_spec GoogleCloudAiplatformV1EncryptionSpecResponse
    Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.
    error GoogleRpcStatusResponse
    DataLabelingJob errors. It is only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
    inputs Any
    Input config parameters for the DataLabelingJob.
    inputs_schema_uri str
    Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.
    instruction_uri str
    The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.
    labeler_count int
    Number of labelers to work on each DataItem.
    labeling_progress int
    Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.
    labels Mapping[str, str]
    The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title.
    name str
    Resource name of the DataLabelingJob.
    specialist_pools Sequence[str]
    The SpecialistPools' resource names associated with this job.
    state str
    The detailed state of the job.
    update_time str
    Timestamp when this DataLabelingJob was updated most recently.
    activeLearningConfig Property Map
    Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
    annotationLabels Map<String>
    Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
    createTime String
    Timestamp when this DataLabelingJob was created.
    currentSpend Property Map
    Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.
    datasets List<String>
    Dataset resource names. Right now we only support labeling from a single Dataset. Format: projects/{project}/locations/{location}/datasets/{dataset}
    displayName String
    The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.
    encryptionSpec Property Map
    Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.
    error Property Map
    DataLabelingJob errors. It is only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
    inputs Any
    Input config parameters for the DataLabelingJob.
    inputsSchemaUri String
    Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.
    instructionUri String
    The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.
    labelerCount Number
    Number of labelers to work on each DataItem.
    labelingProgress Number
    Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.
    labels Map<String>
    The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title.
    name String
    Resource name of the DataLabelingJob.
    specialistPools List<String>
    The SpecialistPools' resource names associated with this job.
    state String
    The detailed state of the job.
    updateTime String
    Timestamp when this DataLabelingJob was updated most recently.

    Supporting Types

    GoogleCloudAiplatformV1ActiveLearningConfigResponse

    MaxDataItemCount string
    Max number of human labeled DataItems.
    MaxDataItemPercentage int
    Max percent of total DataItems for human labeling.
    SampleConfig Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1SampleConfigResponse
    Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
    TrainingConfig Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1TrainingConfigResponse
    CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
    MaxDataItemCount string
    Max number of human labeled DataItems.
    MaxDataItemPercentage int
    Max percent of total DataItems for human labeling.
    SampleConfig GoogleCloudAiplatformV1SampleConfigResponse
    Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
    TrainingConfig GoogleCloudAiplatformV1TrainingConfigResponse
    CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
    maxDataItemCount String
    Max number of human labeled DataItems.
    maxDataItemPercentage Integer
    Max percent of total DataItems for human labeling.
    sampleConfig GoogleCloudAiplatformV1SampleConfigResponse
    Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
    trainingConfig GoogleCloudAiplatformV1TrainingConfigResponse
    CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
    maxDataItemCount string
    Max number of human labeled DataItems.
    maxDataItemPercentage number
    Max percent of total DataItems for human labeling.
    sampleConfig GoogleCloudAiplatformV1SampleConfigResponse
    Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
    trainingConfig GoogleCloudAiplatformV1TrainingConfigResponse
    CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
    max_data_item_count str
    Max number of human labeled DataItems.
    max_data_item_percentage int
    Max percent of total DataItems for human labeling.
    sample_config GoogleCloudAiplatformV1SampleConfigResponse
    Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
    training_config GoogleCloudAiplatformV1TrainingConfigResponse
    CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
    maxDataItemCount String
    Max number of human labeled DataItems.
    maxDataItemPercentage Number
    Max percent of total DataItems for human labeling.
    sampleConfig Property Map
    Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
    trainingConfig Property Map
    CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

    GoogleCloudAiplatformV1EncryptionSpecResponse

    KmsKeyName string
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    KmsKeyName string
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    kmsKeyName String
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    kmsKeyName string
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    kms_key_name str
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
    kmsKeyName String
    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

    GoogleCloudAiplatformV1SampleConfigResponse

    FollowingBatchSamplePercentage int
    The percentage of data needed to be labeled in each following batch (except the first batch).
    InitialBatchSamplePercentage int
    The percentage of data needed to be labeled in the first batch.
    SampleStrategy string
    Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
    FollowingBatchSamplePercentage int
    The percentage of data needed to be labeled in each following batch (except the first batch).
    InitialBatchSamplePercentage int
    The percentage of data needed to be labeled in the first batch.
    SampleStrategy string
    Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
    followingBatchSamplePercentage Integer
    The percentage of data needed to be labeled in each following batch (except the first batch).
    initialBatchSamplePercentage Integer
    The percentage of data needed to be labeled in the first batch.
    sampleStrategy String
    Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
    followingBatchSamplePercentage number
    The percentage of data needed to be labeled in each following batch (except the first batch).
    initialBatchSamplePercentage number
    The percentage of data needed to be labeled in the first batch.
    sampleStrategy string
    Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
    following_batch_sample_percentage int
    The percentage of data needed to be labeled in each following batch (except the first batch).
    initial_batch_sample_percentage int
    The percentage of data needed to be labeled in the first batch.
    sample_strategy str
    Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
    followingBatchSamplePercentage Number
    The percentage of data needed to be labeled in each following batch (except the first batch).
    initialBatchSamplePercentage Number
    The percentage of data needed to be labeled in the first batch.
    sampleStrategy String
    Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.

    GoogleCloudAiplatformV1TrainingConfigResponse

    TimeoutTrainingMilliHours string
    The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.
    TimeoutTrainingMilliHours string
    The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.
    timeoutTrainingMilliHours String
    The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.
    timeoutTrainingMilliHours string
    The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.
    timeout_training_milli_hours str
    The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.
    timeoutTrainingMilliHours String
    The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.

    GoogleRpcStatusResponse

    Code int
    The status code, which should be an enum value of google.rpc.Code.
    Details List<ImmutableDictionary<string, string>>
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    Message string
    A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
    Code int
    The status code, which should be an enum value of google.rpc.Code.
    Details []map[string]string
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    Message string
    A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
    code Integer
    The status code, which should be an enum value of google.rpc.Code.
    details List<Map<String,String>>
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    message String
    A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
    code number
    The status code, which should be an enum value of google.rpc.Code.
    details {[key: string]: string}[]
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    message string
    A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
    code int
    The status code, which should be an enum value of google.rpc.Code.
    details Sequence[Mapping[str, str]]
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    message str
    A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
    code Number
    The status code, which should be an enum value of google.rpc.Code.
    details List<Map<String>>
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    message String
    A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

    GoogleTypeMoneyResponse

    CurrencyCode string
    The three-letter currency code defined in ISO 4217.
    Nanos int
    Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If units is positive, nanos must be positive or zero. If units is zero, nanos can be positive, zero, or negative. If units is negative, nanos must be negative or zero. For example $-1.75 is represented as units=-1 and nanos=-750,000,000.
    Units string
    The whole units of the amount. For example if currencyCode is "USD", then 1 unit is one US dollar.
    CurrencyCode string
    The three-letter currency code defined in ISO 4217.
    Nanos int
    Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If units is positive, nanos must be positive or zero. If units is zero, nanos can be positive, zero, or negative. If units is negative, nanos must be negative or zero. For example $-1.75 is represented as units=-1 and nanos=-750,000,000.
    Units string
    The whole units of the amount. For example if currencyCode is "USD", then 1 unit is one US dollar.
    currencyCode String
    The three-letter currency code defined in ISO 4217.
    nanos Integer
    Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If units is positive, nanos must be positive or zero. If units is zero, nanos can be positive, zero, or negative. If units is negative, nanos must be negative or zero. For example $-1.75 is represented as units=-1 and nanos=-750,000,000.
    units String
    The whole units of the amount. For example if currencyCode is "USD", then 1 unit is one US dollar.
    currencyCode string
    The three-letter currency code defined in ISO 4217.
    nanos number
    Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If units is positive, nanos must be positive or zero. If units is zero, nanos can be positive, zero, or negative. If units is negative, nanos must be negative or zero. For example $-1.75 is represented as units=-1 and nanos=-750,000,000.
    units string
    The whole units of the amount. For example if currencyCode is "USD", then 1 unit is one US dollar.
    currency_code str
    The three-letter currency code defined in ISO 4217.
    nanos int
    Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If units is positive, nanos must be positive or zero. If units is zero, nanos can be positive, zero, or negative. If units is negative, nanos must be negative or zero. For example $-1.75 is represented as units=-1 and nanos=-750,000,000.
    units str
    The whole units of the amount. For example if currencyCode is "USD", then 1 unit is one US dollar.
    currencyCode String
    The three-letter currency code defined in ISO 4217.
    nanos Number
    Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If units is positive, nanos must be positive or zero. If units is zero, nanos can be positive, zero, or negative. If units is negative, nanos must be negative or zero. For example $-1.75 is represented as units=-1 and nanos=-750,000,000.
    units String
    The whole units of the amount. For example if currencyCode is "USD", then 1 unit is one US dollar.

    Package Details

    Repository
    Google Cloud Native pulumi/pulumi-google-native
    License
    Apache-2.0
    google-native logo

    Google Cloud Native is in preview. Google Cloud Classic is fully supported.

    Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
    pulumi/pulumi-google-native