Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::PipelineJob (v0.33.0)

Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::PipelineJob.

An instance of a machine learning PipelineJob.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#create_time

def create_time() -> ::Google::Protobuf::Timestamp
Returns

#display_name

def display_name() -> ::String
Returns
  • (::String) — The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.

#display_name=

def display_name=(value) -> ::String
Parameter
  • value (::String) — The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
Returns
  • (::String) — The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.

#encryption_spec

def encryption_spec() -> ::Google::Cloud::AIPlatform::V1::EncryptionSpec
Returns

#encryption_spec=

def encryption_spec=(value) -> ::Google::Cloud::AIPlatform::V1::EncryptionSpec
Parameter
Returns

#end_time

def end_time() -> ::Google::Protobuf::Timestamp
Returns

#error

def error() -> ::Google::Rpc::Status
Returns
  • (::Google::Rpc::Status) — Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.

#job_detail

def job_detail() -> ::Google::Cloud::AIPlatform::V1::PipelineJobDetail
Returns

#labels

def labels() -> ::Google::Protobuf::Map{::String => ::String}
Returns
  • (::Google::Protobuf::Map{::String => ::String}) —

    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.

    Note there is some reserved label key for Vertex AI Pipelines.

    • vertex-ai-pipelines-run-billing-id, user set value will get overrided.

#labels=

def labels=(value) -> ::Google::Protobuf::Map{::String => ::String}
Parameter
  • value (::Google::Protobuf::Map{::String => ::String}) —

    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.

    Note there is some reserved label key for Vertex AI Pipelines.

    • vertex-ai-pipelines-run-billing-id, user set value will get overrided.
Returns
  • (::Google::Protobuf::Map{::String => ::String}) —

    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.

    Note there is some reserved label key for Vertex AI Pipelines.

    • vertex-ai-pipelines-run-billing-id, user set value will get overrided.

#name

def name() -> ::String
Returns
  • (::String) — Output only. The resource name of the PipelineJob.

#network

def network() -> ::String
Returns
  • (::String) — 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 Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.

#network=

def network=(value) -> ::String
Parameter
  • value (::String) — 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 Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.

Returns
  • (::String) — 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 Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.

#pipeline_spec

def pipeline_spec() -> ::Google::Protobuf::Struct
Returns

#pipeline_spec=

def pipeline_spec=(value) -> ::Google::Protobuf::Struct
Parameter
Returns

#reserved_ip_ranges

def reserved_ip_ranges() -> ::Array<::String>
Returns
  • (::Array<::String>) — A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload.

    If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network.

    Example: ['vertex-ai-ip-range'].

#reserved_ip_ranges=

def reserved_ip_ranges=(value) -> ::Array<::String>
Parameter
  • value (::Array<::String>) — A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload.

    If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network.

    Example: ['vertex-ai-ip-range'].

Returns
  • (::Array<::String>) — A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload.

    If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network.

    Example: ['vertex-ai-ip-range'].

#runtime_config

def runtime_config() -> ::Google::Cloud::AIPlatform::V1::PipelineJob::RuntimeConfig
Returns

#runtime_config=

def runtime_config=(value) -> ::Google::Cloud::AIPlatform::V1::PipelineJob::RuntimeConfig
Parameter
Returns

#schedule_name

def schedule_name() -> ::String
Returns
  • (::String) — Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.

#service_account

def service_account() -> ::String
Returns
  • (::String) — 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.

#service_account=

def service_account=(value) -> ::String
Parameter
  • value (::String) — 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.

Returns
  • (::String) — 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.

#start_time

def start_time() -> ::Google::Protobuf::Timestamp
Returns

#state

def state() -> ::Google::Cloud::AIPlatform::V1::PipelineState
Returns

#template_metadata

def template_metadata() -> ::Google::Cloud::AIPlatform::V1::PipelineTemplateMetadata
Returns

#template_uri

def template_uri() -> ::String
Returns
  • (::String) — A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.

#template_uri=

def template_uri=(value) -> ::String
Parameter
  • value (::String) — A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
Returns
  • (::String) — A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.

#update_time

def update_time() -> ::Google::Protobuf::Timestamp
Returns