Class PipelineJob (1.8.1)

  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 > PipelineJob

Classes

LabelsEntry

  LabelsEntry 
 ( 
 mapping 
 = 
 None 
 , 
 * 
 , 
 ignore_unknown_fields 
 = 
 False 
 , 
 ** 
 kwargs 
 )

The abstract base class for a message.

Parameters

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 `mapping` is a mapping type or there are keyword parameters.

RuntimeConfig

  RuntimeConfig 
 ( 
 mapping 
 = 
 None 
 , 
 * 
 , 
 ignore_unknown_fields 
 = 
 False 
 , 
 ** 
 kwargs 
 )

The runtime config of a PipelineJob.