- 1.73.0 (latest)
- 1.72.0
- 1.71.1
- 1.70.0
- 1.69.0
- 1.68.0
- 1.67.1
- 1.66.0
- 1.65.0
- 1.63.0
- 1.62.0
- 1.60.0
- 1.59.0
- 1.58.0
- 1.57.0
- 1.56.0
- 1.55.0
- 1.54.1
- 1.53.0
- 1.52.0
- 1.51.0
- 1.50.0
- 1.49.0
- 1.48.0
- 1.47.0
- 1.46.0
- 1.45.0
- 1.44.0
- 1.43.0
- 1.39.0
- 1.38.1
- 1.37.0
- 1.36.4
- 1.35.0
- 1.34.0
- 1.33.1
- 1.32.0
- 1.31.1
- 1.30.1
- 1.29.0
- 1.28.1
- 1.27.1
- 1.26.1
- 1.25.0
- 1.24.1
- 1.23.0
- 1.22.1
- 1.21.0
- 1.20.0
- 1.19.1
- 1.18.3
- 1.17.1
- 1.16.1
- 1.15.1
- 1.14.0
- 1.13.1
- 1.12.1
- 1.11.0
- 1.10.0
- 1.9.0
- 1.8.1
- 1.7.1
- 1.6.2
- 1.5.0
- 1.4.3
- 1.3.0
- 1.2.0
- 1.1.1
- 1.0.1
- 0.9.0
- 0.8.0
- 0.7.1
- 0.6.0
- 0.5.1
- 0.4.0
- 0.3.1
DataLabelingJob
(
mapping
=
None
,
*
,
ignore_unknown_fields
=
False
,
**
kwargs
)
DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:
Attributes
| Name | Description |
| name | str
Output only. Resource name of the DataLabelingJob. |
| display_name | str
Required. The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can be consist of any UTF-8 characters. Display name of a DataLabelingJob. |
| datasets | Sequence[str]
Required. Dataset resource names. Right now we only support labeling from a single Dataset. Format: projects/{project}/locations/{location}/datasets/{dataset}
|
| 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. |
| labeler_count | int
Required. Number of labelers to work on each DataItem. |
| instruction_uri | str
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 | str
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.struct_pb2.Value
Required. Input config parameters for the DataLabelingJob. |
| state | google.cloud.aiplatform_v1.types.JobState
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_pb2.Money
Output only. Estimated cost(in US dollars) that the DataLabelingJob has incurred to date. |
| create_time | google.protobuf.timestamp_pb2.Timestamp
Output only. Timestamp when this DataLabelingJob was created. |
| update_time | google.protobuf.timestamp_pb2.Timestamp
Output only. Timestamp when this DataLabelingJob was updated most recently. |
| error | google.rpc.status_pb2.Status
Output only. DataLabelingJob errors. It is only populated when job's state is JOB_STATE_FAILED
or JOB_STATE_CANCELLED
. |
| 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. |
| specialist_pools | Sequence[str]
The SpecialistPools' resource names associated with this job. |
| encryption_spec | google.cloud.aiplatform_v1.types.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 | google.cloud.aiplatform_v1.types.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. |
Inheritance
builtins.object > proto.message.Message > DataLabelingJobClasses
AnnotationLabelsEntry
AnnotationLabelsEntry
(
mapping
=
None
,
*
,
ignore_unknown_fields
=
False
,
**
kwargs
)
The abstract base class for a message.
| Name | Description |
| kwargs | dict
Keys and values corresponding to the fields of the message. |
| mapping | Union[dict,
A dictionary or message to be used to determine the values for this message. |
| ignore_unknown_fields | Optional(bool)
If True, do not raise errors for unknown fields. Only applied if |
LabelsEntry
LabelsEntry
(
mapping
=
None
,
*
,
ignore_unknown_fields
=
False
,
**
kwargs
)
The abstract base class for a message.
| Name | Description |
| kwargs | dict
Keys and values corresponding to the fields of the message. |
| mapping | Union[dict,
A dictionary or message to be used to determine the values for this message. |
| ignore_unknown_fields | Optional(bool)
If True, do not raise errors for unknown fields. Only applied if |
