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PipelineJob(mapping=None, *, ignore_unknown_fields=False, **kwargs)
An instance of a machine learning PipelineJob.
Attributes
Name | Description |
name |
str
Output only. The resource name of the PipelineJob. |
display_name |
str
The display name of the Pipeline. The name can be up to 128 characters long and can be consist of any UTF-8 characters. |
create_time |
google.protobuf.timestamp_pb2.Timestamp
Output only. Pipeline creation time. |
start_time |
google.protobuf.timestamp_pb2.Timestamp
Output only. Pipeline start time. |
end_time |
google.protobuf.timestamp_pb2.Timestamp
Output only. Pipeline end time. |
update_time |
google.protobuf.timestamp_pb2.Timestamp
Output only. Timestamp when this PipelineJob was most recently updated. |
pipeline_spec |
google.protobuf.struct_pb2.Struct
Required. The spec of the pipeline. |
state |
google.cloud.aiplatform_v1.types.PipelineState
Output only. The detailed state of the job. |
job_detail |
google.cloud.aiplatform_v1.types.PipelineJobDetail
Output only. The details of pipeline run. Not available in the list view. |
error |
google.rpc.status_pb2.Status
Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED. |
labels |
Sequence[google.cloud.aiplatform_v1.types.PipelineJob.LabelsEntry]
The labels with user-defined metadata to organize PipelineJob. 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. |
runtime_config |
google.cloud.aiplatform_v1.types.PipelineJob.RuntimeConfig
Runtime config of the pipeline. |
encryption_spec |
google.cloud.aiplatform_v1.types.EncryptionSpec
Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key. |
service_account |
str
The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the ``iam.serviceAccounts.actAs`` permission on this service account. |
network |
str
The full name of the Compute Engine `network `__ to which the Pipeline Job's workload should be peered. For example, ``projects/12345/global/networks/myVPC``. `Format `__ is of the form ``projects/{project}/global/networks/{network}``. Where {project} is a project number, as in ``12345``, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the GCP resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network. |
Inheritance
builtins.object > proto.message.Message > PipelineJobClasses
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, `.Message`]
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 |
RuntimeConfig
RuntimeConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)
The runtime config of a PipelineJob.