PipelineJobArgs class

The set of arguments for PipelineJob. The set of arguments for PipelineJob.

Constructors

PipelineJobArgs({Input<String>? displayName, Input<GoogleCloudAiplatformV1EncryptionSpec>? encryptionSpec, Input<Map<String, String>>? labels, Input<String>? location, Input<String>? network, Input<String>? pipelineJobId, Input<Map<String, String>>? pipelineSpec, Input<String>? project, Input<List<String>>? reservedIpRanges, Input<GoogleCloudAiplatformV1PipelineJobRuntimeConfig>? runtimeConfig, Input<String>? serviceAccount, Input<String>? templateUri})
Creates a new PipelineJobArgs. displayName The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters. 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. labels 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. location Optional. network 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. pipelineJobId The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are /a-z-/. pipelineSpec The spec of the pipeline. project Optional. reservedIpRanges 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'. runtimeConfig Runtime config of the pipeline. serviceAccount 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. templateUri 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.
const
PipelineJobArgs.fromMap(Map<String, dynamic> map)
factory

Properties

displayName → Input<String>?
The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
final
encryptionSpec → Input<GoogleCloudAiplatformV1EncryptionSpec>?
Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
final
hashCode → int
The hash code for this object.
no setterinherited
labels → Input<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.
final
location → Input<String>?
final
network → Input<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.
final
pipelineJobId → Input<String>?
The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are /a-z-/.
final
pipelineSpec → Input<Map<String, String>>?
The spec of the pipeline.
final
project → Input<String>?
final
reservedIpRanges → Input<List<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'.
final
runtimeConfig → Input<GoogleCloudAiplatformV1PipelineJobRuntimeConfig>?
Runtime config of the pipeline.
final
runtimeType → Type
A representation of the runtime type of the object.
no setterinherited
serviceAccount → Input<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.
final
templateUri → Input<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.
final

Methods

noSuchMethod(Invocation invocation) → dynamic
Invoked when a nonexistent method or property is accessed.
inherited
toMap() → Map<String, dynamic>
toString() → String
A string representation of this object.
inherited

Operators

operator ==(Object other) → bool
The equality operator.
inherited