TrainingPipeline class

Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run. Auto-naming is currently not supported for this resource.

Constructors

TrainingPipeline(String name, {TrainingPipelineArgs? args, CustomResourceOptions? options})

Creates a new TrainingPipeline. name The Pulumi resource name. args Arguments used to configure this TrainingPipeline. The set of arguments for TrainingPipeline. options Resource options controlling this resource's behavior.

Properties

childResources → Set<Resource>

final, inherited

completionSources ↔ Map<String, IOutputCompletionSource>

late, final, inherited

createTime ↔ Output<String>

Time when the TrainingPipeline was created.

late, final

displayName ↔ Output<String>

The user-defined name of this TrainingPipeline.

late, final

encryptionSpec ↔ Output<GoogleCloudAiplatformV1EncryptionSpecResponse>

Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately.

late, final

endTime ↔ Output<String>

Time when the TrainingPipeline entered any of the following states: PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED, PIPELINE_STATE_CANCELLED.

late, final

error ↔ Output<GoogleRpcStatusResponse>

Only populated when the pipeline's state is PIPELINE_STATE_FAILED or PIPELINE_STATE_CANCELLED.

late, final

hashCode → int

The hash code for this object.

no setter, inherited

id ↔ Output<String>

getter/setter pair, inherited

inputDataConfig ↔ Output<GoogleCloudAiplatformV1InputDataConfigResponse>

Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration.

late, final

isCustom → bool

Returns whether this resource is provider-managed.

no setter, inherited

isProtected → bool

Returns whether this resource is protected from deletion.

no setter, inherited

isRemote → bool

Whether this resource is registered as remote.

no setter, inherited

isResourceReference → bool

Whether this instance represents a resource value returned over RPC.

final, inherited

labels ↔ Output<Map<String, String>>

The labels with user-defined metadata to organize TrainingPipelines. 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.

late, final

location ↔ Output<String>

late, final

modelId ↔ Output<String>

Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are [a-z0-9_-]. The first character cannot be a number or hyphen.

late, final

modelToUpload ↔ Output<GoogleCloudAiplatformV1ModelResponse>

Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's training_task_definition should make clear whether this Model description should be populated, and if there are any special requirements regarding how it should be filled. If nothing is mentioned in the training_task_definition, then it should be assumed that this field should not be filled and the training task either uploads the Model without a need of this information, or that training task does not support uploading a Model as part of the pipeline. When the Pipeline's state becomes PIPELINE_STATE_SUCCEEDED and the trained Model had been uploaded into Vertex AI, then the model_to_upload's resource name is populated. The Model is always uploaded into the Project and Location in which this pipeline is.

late, final

name ↔ Output<String>

Resource name of the TrainingPipeline.

late, final

parentModel ↔ Output<String>

Optional. When specify this field, the model_to_upload will not be uploaded as a new model, instead, it will become a new version of this parent_model.

late, final

project ↔ Output<String>

late, final

resourceTransforms → List<ResourceTransform>

Inherited/explicit async transforms.

no setter, inherited

runtimeType → Type

A representation of the runtime type of the object.

no setter, inherited

startTime ↔ Output<String>

Time when the TrainingPipeline for the first time entered the PIPELINE_STATE_RUNNING state.

late, final

state ↔ Output<String>

The detailed state of the pipeline.

late, final

trainingTaskDefinition ↔ Output<String>

A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud-aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

late, final

trainingTaskInputs ↔ Output

The training task's parameter(s), as specified in the training_task_definition's inputs.

late, final

trainingTaskMetadata ↔ Output

The metadata information as specified in the training_task_definition's metadata. This metadata is an auxiliary runtime and final information about the training task. While the pipeline is running this information is populated only at a best effort basis. Only present if the pipeline's training_task_definition contains metadata object.

late, final

transformations → List<ResourceTransformation>

Inherited/explicit legacy transformations.

no setter, inherited

updateTime ↔ Output<String>

Time when the TrainingPipeline was most recently updated.

late, final

urn ↔ Output<String>

late, final, inherited

Methods

failId(Object error) → void

Completes this resource ID with an error when registration fails.

inherited

failOutputs(Object error) → void

Completes all output properties with error.

inherited

failUrn(Object error) → void

Completes this resource URN with an error when registration fails.

inherited

getProvider(String moduleMember) → ProviderResource?

Returns provider for moduleMember's package, if configured.

inherited

getResourceName() → String

Returns this resource's logical name.

inherited

getResourceType() → String

Returns this resource's Pulumi type token.

inherited

noSuchMethod(Invocation invocation) → dynamic

Invoked when a nonexistent method or property is accessed.

inherited

registerOutput<T>(String propertyName, {Object? decoder(Object?)?, bool isSecret = false}) → Output<T>

Registers a dynamic output property for this resource.

inherited

resolveId(String? value, {required bool isKnown}) → void

Resolves the provider-assigned ID for this resource.

inherited

resolveOutputs(Struct outputs) → void

Resolves all output properties from a monitor response payload.

inherited

resolveUrn(String value) → void

Resolves this resource's URN once assigned by the engine.

inherited

serializeProperties(Map<String, dynamic> properties) → Future<Struct>

Serializes resource properties for RPC transmission.

inherited

toString() → String

A string representation of this object.

inherited

Operators

operator ==(Object other) → bool

The equality operator.

inherited