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
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
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)
// Output-based functions aren't available in Java yet
fn::invoke:
function: google-native:aiplatform/v1:getDataLabelingJob
arguments:
# arguments dictionary
The following arguments are supported:
- Data
Labeling stringJob Id - Location string
- Project string
- Data
Labeling stringJob Id - Location string
- Project string
- data
Labeling StringJob Id - location String
- project String
- data
Labeling stringJob Id - location string
- project string
- data_
labeling_ strjob_ id - location str
- project str
- data
Labeling StringJob Id - location String
- project String
getDataLabelingJob Result
The following output properties are available:
- Active
Learning Pulumi.Config Google Native. Aiplatform. V1. Outputs. Google Cloud Aiplatform V1Active Learning Config Response - 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 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.
- Create
Time string - Timestamp when this DataLabelingJob was created.
- Current
Spend Pulumi.Google Native. Aiplatform. V1. Outputs. Google Type Money Response - 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}
- Display
Name 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.
- Encryption
Spec Pulumi.Google Native. Aiplatform. V1. Outputs. Google Cloud Aiplatform V1Encryption Spec Response - 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.
Google Native. Aiplatform. V1. Outputs. Google Rpc Status Response - DataLabelingJob errors. It is only populated when job's state is
JOB_STATE_FAILED
orJOB_STATE_CANCELLED
. - Inputs object
- Input config parameters for the DataLabelingJob.
- Inputs
Schema stringUri - 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 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.
- 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 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.
- Specialist
Pools List<string> - The SpecialistPools' resource names associated with this job.
- State string
- The detailed state of the job.
- Update
Time string - Timestamp when this DataLabelingJob was updated most recently.
- Active
Learning GoogleConfig Cloud Aiplatform V1Active Learning Config Response - 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 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.
- Create
Time string - Timestamp when this DataLabelingJob was created.
- Current
Spend GoogleType Money Response - 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}
- Display
Name 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.
- Encryption
Spec GoogleCloud Aiplatform V1Encryption Spec Response - 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
Google
Rpc Status Response - DataLabelingJob errors. It is only populated when job's state is
JOB_STATE_FAILED
orJOB_STATE_CANCELLED
. - Inputs interface{}
- Input config parameters for the DataLabelingJob.
- Inputs
Schema stringUri - 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 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.
- 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 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.
- Specialist
Pools []string - The SpecialistPools' resource names associated with this job.
- State string
- The detailed state of the job.
- Update
Time string - Timestamp when this DataLabelingJob was updated most recently.
- active
Learning GoogleConfig Cloud Aiplatform V1Active Learning Config Response - 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 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.
- create
Time String - Timestamp when this DataLabelingJob was created.
- current
Spend GoogleType Money Response - 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}
- display
Name 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.
- encryption
Spec GoogleCloud Aiplatform V1Encryption Spec Response - 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
Google
Rpc Status Response - DataLabelingJob errors. It is only populated when job's state is
JOB_STATE_FAILED
orJOB_STATE_CANCELLED
. - inputs Object
- Input config parameters for the DataLabelingJob.
- inputs
Schema StringUri - 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 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.
- labeler
Count Integer - Number of labelers to work on each DataItem.
- labeling
Progress 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.
- specialist
Pools List<String> - The SpecialistPools' resource names associated with this job.
- state String
- The detailed state of the job.
- update
Time String - Timestamp when this DataLabelingJob was updated most recently.
- active
Learning GoogleConfig Cloud Aiplatform V1Active Learning Config Response - 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 {[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.
- create
Time string - Timestamp when this DataLabelingJob was created.
- current
Spend GoogleType Money Response - 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}
- display
Name 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.
- encryption
Spec GoogleCloud Aiplatform V1Encryption Spec Response - 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
Google
Rpc Status Response - DataLabelingJob errors. It is only populated when job's state is
JOB_STATE_FAILED
orJOB_STATE_CANCELLED
. - inputs any
- Input config parameters for the DataLabelingJob.
- inputs
Schema stringUri - 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 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.
- labeler
Count number - Number of labelers to work on each DataItem.
- labeling
Progress 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.
- specialist
Pools string[] - The SpecialistPools' resource names associated with this job.
- state string
- The detailed state of the job.
- update
Time string - Timestamp when this DataLabelingJob was updated most recently.
- active_
learning_ Googleconfig Cloud Aiplatform V1Active Learning Config Response - 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 GoogleType Money Response - 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 GoogleCloud Aiplatform V1Encryption Spec Response - 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
Google
Rpc Status Response - DataLabelingJob errors. It is only populated when job's state is
JOB_STATE_FAILED
orJOB_STATE_CANCELLED
. - inputs Any
- Input config parameters for the DataLabelingJob.
- inputs_
schema_ struri - 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.
- active
Learning Property MapConfig - 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 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.
- create
Time String - Timestamp when this DataLabelingJob was created.
- current
Spend 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}
- display
Name 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.
- encryption
Spec 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
orJOB_STATE_CANCELLED
. - inputs Any
- Input config parameters for the DataLabelingJob.
- inputs
Schema StringUri - 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 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.
- labeler
Count Number - Number of labelers to work on each DataItem.
- labeling
Progress 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.
- specialist
Pools List<String> - The SpecialistPools' resource names associated with this job.
- state String
- The detailed state of the job.
- update
Time String - Timestamp when this DataLabelingJob was updated most recently.
Supporting Types
GoogleCloudAiplatformV1ActiveLearningConfigResponse
- Max
Data stringItem Count - Max number of human labeled DataItems.
- Max
Data intItem Percentage - Max percent of total DataItems for human labeling.
- Sample
Config Pulumi.Google Native. Aiplatform. V1. Inputs. Google Cloud Aiplatform V1Sample Config Response - 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 Pulumi.Google Native. Aiplatform. V1. Inputs. Google Cloud Aiplatform V1Training Config Response - 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 stringItem Count - Max number of human labeled DataItems.
- Max
Data intItem Percentage - Max percent of total DataItems for human labeling.
- Sample
Config GoogleCloud Aiplatform V1Sample Config Response - 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 GoogleCloud Aiplatform V1Training Config Response - 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 StringItem Count - Max number of human labeled DataItems.
- max
Data IntegerItem Percentage - Max percent of total DataItems for human labeling.
- sample
Config GoogleCloud Aiplatform V1Sample Config Response - 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 GoogleCloud Aiplatform V1Training Config Response - 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 stringItem Count - Max number of human labeled DataItems.
- max
Data numberItem Percentage - Max percent of total DataItems for human labeling.
- sample
Config GoogleCloud Aiplatform V1Sample Config Response - 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 GoogleCloud Aiplatform V1Training Config Response - 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_ stritem_ count - Max number of human labeled DataItems.
- max_
data_ intitem_ percentage - Max percent of total DataItems for human labeling.
- sample_
config GoogleCloud Aiplatform V1Sample Config Response - 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 GoogleCloud Aiplatform V1Training Config Response - 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 StringItem Count - Max number of human labeled DataItems.
- max
Data NumberItem Percentage - Max percent of total DataItems for human labeling.
- sample
Config 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.
- training
Config 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
- Kms
Key stringName - 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 stringName - 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 StringName - 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 stringName - 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_ strname - 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 StringName - 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
- Following
Batch intSample Percentage - The percentage of data needed to be labeled in each following batch (except the first batch).
- Initial
Batch intSample Percentage - The percentage of data needed to be labeled in the first batch.
- Sample
Strategy string - Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
- Following
Batch intSample Percentage - The percentage of data needed to be labeled in each following batch (except the first batch).
- Initial
Batch intSample Percentage - The percentage of data needed to be labeled in the first batch.
- Sample
Strategy string - Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
- following
Batch IntegerSample Percentage - The percentage of data needed to be labeled in each following batch (except the first batch).
- initial
Batch IntegerSample Percentage - The percentage of data needed to be labeled in the first batch.
- sample
Strategy String - Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
- following
Batch numberSample Percentage - The percentage of data needed to be labeled in each following batch (except the first batch).
- initial
Batch numberSample Percentage - The percentage of data needed to be labeled in the first batch.
- sample
Strategy string - Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
- following_
batch_ intsample_ percentage - The percentage of data needed to be labeled in each following batch (except the first batch).
- initial_
batch_ intsample_ percentage - 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.
- following
Batch NumberSample Percentage - The percentage of data needed to be labeled in each following batch (except the first batch).
- initial
Batch NumberSample Percentage - The percentage of data needed to be labeled in the first batch.
- sample
Strategy String - Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
GoogleCloudAiplatformV1TrainingConfigResponse
- Timeout
Training stringMilli Hours - 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 stringMilli Hours - 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 StringMilli Hours - 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 stringMilli Hours - 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_ strmilli_ hours - 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 StringMilli Hours - 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<Immutable
Dictionary<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
- Currency
Code 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. Ifunits
is zero,nanos
can be positive, zero, or negative. Ifunits
is negative,nanos
must be negative or zero. For example $-1.75 is represented asunits
=-1 andnanos
=-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 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. Ifunits
is zero,nanos
can be positive, zero, or negative. Ifunits
is negative,nanos
must be negative or zero. For example $-1.75 is represented asunits
=-1 andnanos
=-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 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. Ifunits
is zero,nanos
can be positive, zero, or negative. Ifunits
is negative,nanos
must be negative or zero. For example $-1.75 is represented asunits
=-1 andnanos
=-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 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. Ifunits
is zero,nanos
can be positive, zero, or negative. Ifunits
is negative,nanos
must be negative or zero. For example $-1.75 is represented asunits
=-1 andnanos
=-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. Ifunits
is zero,nanos
can be positive, zero, or negative. Ifunits
is negative,nanos
must be negative or zero. For example $-1.75 is represented asunits
=-1 andnanos
=-750,000,000. - units str
- The whole units of the amount. For example if
currencyCode
is"USD"
, then 1 unit is one US dollar.
- currency
Code 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. Ifunits
is zero,nanos
can be positive, zero, or negative. Ifunits
is negative,nanos
must be negative or zero. For example $-1.75 is represented asunits
=-1 andnanos
=-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 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