Google Cloud Ai Platform V1 Client - Class DataLabelingJob (1.31.0)

Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class DataLabelingJob.

DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:

Generated from protobuf message google.cloud.aiplatform.v1.DataLabelingJob

Namespace

Google \ Cloud \ AIPlatform \ V1

Methods

__construct

Constructor.

Parameters
Name
Description
data
array

Optional. Data for populating the Message object.

↳ name
string

Output only. Resource name of the DataLabelingJob.

↳ display_name
string

Required. 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.

↳ datasets
array

Required. Dataset resource names. Right now we only support labeling from a single Dataset. Format: projects/{project}/locations/{location}/datasets/{dataset}

↳ annotation_labels
array| Google\Protobuf\Internal\MapField

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.

↳ labeler_count
int

Required. Number of labelers to work on each DataItem.

↳ instruction_uri
string

Required. 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.

↳ inputs_schema_uri
string

Required. 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.

↳ inputs
Google\Protobuf\Value

Required. Input config parameters for the DataLabelingJob.

↳ state
int

Output only. The detailed state of the job.

↳ labeling_progress
int

Output only. Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.

↳ current_spend
Google\Type\Money

Output only. Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.

↳ create_time
Google\Protobuf\Timestamp

Output only. Timestamp when this DataLabelingJob was created.

↳ update_time
Google\Protobuf\Timestamp

Output only. Timestamp when this DataLabelingJob was updated most recently.

↳ error
Google\Rpc\Status

Output only. DataLabelingJob errors. It is only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED .

↳ labels
array| Google\Protobuf\Internal\MapField

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.

↳ specialist_pools
array

The SpecialistPools' resource names associated with this job.

↳ encryption_spec
EncryptionSpec

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.

↳ active_learning_config
ActiveLearningConfig

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.

getName

Output only. Resource name of the DataLabelingJob.

Returns
Type
Description
string

setName

Output only. Resource name of the DataLabelingJob.

Parameter
Name
Description
var
string
Returns
Type
Description
$this

getDisplayName

Required. 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.

Returns
Type
Description
string

setDisplayName

Required. 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.

Parameter
Name
Description
var
string
Returns
Type
Description
$this

getDatasets

Required. Dataset resource names. Right now we only support labeling from a single Dataset. Format: projects/{project}/locations/{location}/datasets/{dataset}

Returns
Type
Description

setDatasets

Required. Dataset resource names. Right now we only support labeling from a single Dataset. Format: projects/{project}/locations/{location}/datasets/{dataset}

Parameter
Name
Description
var
string[]
Returns
Type
Description
$this

getAnnotationLabels

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.

Returns
Type
Description

setAnnotationLabels

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.

Parameter
Name
Description
Returns
Type
Description
$this

getLabelerCount

Required. Number of labelers to work on each DataItem.

Returns
Type
Description
int

setLabelerCount

Required. Number of labelers to work on each DataItem.

Parameter
Name
Description
var
int
Returns
Type
Description
$this

getInstructionUri

Required. 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.

Returns
Type
Description
string

setInstructionUri

Required. 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.

Parameter
Name
Description
var
string
Returns
Type
Description
$this

getInputsSchemaUri

Required. 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.

Returns
Type
Description
string

setInputsSchemaUri

Required. 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.

Parameter
Name
Description
var
string
Returns
Type
Description
$this

getInputs

Required. Input config parameters for the DataLabelingJob.

Returns
Type
Description

hasInputs

clearInputs

setInputs

Required. Input config parameters for the DataLabelingJob.

Parameter
Name
Description
Returns
Type
Description
$this

getState

Output only. The detailed state of the job.

Returns
Type
Description
int

setState

Output only. The detailed state of the job.

Parameter
Name
Description
var
int
Returns
Type
Description
$this

getLabelingProgress

Output only. Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.

Returns
Type
Description
int

setLabelingProgress

Output only. Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.

Parameter
Name
Description
var
int
Returns
Type
Description
$this

getCurrentSpend

Output only. Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.

Returns
Type
Description

hasCurrentSpend

clearCurrentSpend

setCurrentSpend

Output only. Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.

Parameter
Name
Description
Returns
Type
Description
$this

getCreateTime

Output only. Timestamp when this DataLabelingJob was created.

Returns
Type
Description

hasCreateTime

clearCreateTime

setCreateTime

Output only. Timestamp when this DataLabelingJob was created.

Parameter
Name
Description
Returns
Type
Description
$this

getUpdateTime

Output only. Timestamp when this DataLabelingJob was updated most recently.

Returns
Type
Description

hasUpdateTime

clearUpdateTime

setUpdateTime

Output only. Timestamp when this DataLabelingJob was updated most recently.

Parameter
Name
Description
Returns
Type
Description
$this

getError

Output only. DataLabelingJob errors. It is only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED .

Returns
Type
Description

hasError

clearError

setError

Output only. DataLabelingJob errors. It is only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED .

Parameter
Name
Description
Returns
Type
Description
$this

getLabels

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.
Returns
Type
Description

setLabels

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.
Parameter
Name
Description
Returns
Type
Description
$this

getSpecialistPools

The SpecialistPools' resource names associated with this job.

Returns
Type
Description

setSpecialistPools

The SpecialistPools' resource names associated with this job.

Parameter
Name
Description
var
string[]
Returns
Type
Description
$this

getEncryptionSpec

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.

Returns
Type
Description

hasEncryptionSpec

clearEncryptionSpec

setEncryptionSpec

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.

Parameter
Name
Description
Returns
Type
Description
$this

getActiveLearningConfig

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.

Returns
Type
Description

hasActiveLearningConfig

clearActiveLearningConfig

setActiveLearningConfig

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.

Parameter
Name
Description
Returns
Type
Description
$this
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