- 0.54.0 (latest)
- 0.53.0
- 0.52.0
- 0.51.0
- 0.50.0
- 0.49.0
- 0.48.0
- 0.47.0
- 0.46.0
- 0.45.0
- 0.44.0
- 0.43.0
- 0.42.0
- 0.41.0
- 0.40.0
- 0.39.0
- 0.38.0
- 0.37.0
- 0.36.0
- 0.35.0
- 0.34.0
- 0.33.0
- 0.32.0
- 0.31.0
- 0.30.0
- 0.29.0
- 0.28.0
- 0.27.0
- 0.26.0
- 0.25.0
- 0.24.0
- 0.23.0
- 0.22.0
- 0.21.0
- 0.20.0
- 0.19.0
- 0.18.0
- 0.17.0
- 0.16.0
- 0.15.0
- 0.14.0
- 0.13.0
- 0.12.0
- 0.11.0
- 0.10.0
- 0.9.1
- 0.8.0
- 0.7.0
- 0.6.0
- 0.5.0
- 0.4.0
- 0.3.0
- 0.2.0
- 0.1.0
Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::Model.
A trained machine learning Model.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#artifact_uri
def artifact_uri() -> ::String
Returns
- (::String) — Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models or Large Models.
#artifact_uri=
def artifact_uri=(value) -> ::String
Parameter
- value (::String) — Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models or Large Models.
Returns
- (::String) — Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models or Large Models.
#container_spec
def container_spec() -> ::Google::Cloud::AIPlatform::V1::ModelContainerSpec
Returns
- (::Google::Cloud::AIPlatform::V1::ModelContainerSpec) — Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models or Large Models.
#container_spec=
def container_spec=(value) -> ::Google::Cloud::AIPlatform::V1::ModelContainerSpec
Parameter
- value (::Google::Cloud::AIPlatform::V1::ModelContainerSpec) — Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models or Large Models.
Returns
- (::Google::Cloud::AIPlatform::V1::ModelContainerSpec) — Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models or Large Models.
#create_time
def create_time() -> ::Google::Protobuf::Timestamp
Returns
- (::Google::Protobuf::Timestamp) — Output only. Timestamp when this Model was uploaded into Vertex AI.
#deployed_models
def deployed_models() -> ::Array<::Google::Cloud::AIPlatform::V1::DeployedModelRef>
Returns
- (::Array<::Google::Cloud::AIPlatform::V1::DeployedModelRef>) — Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
#description
def description() -> ::String
Returns
- (::String) — The description of the Model.
#description=
def description=(value) -> ::String
Parameter
- value (::String) — The description of the Model.
Returns
- (::String) — The description of the Model.
#display_name
def display_name() -> ::String
Returns
- (::String) — Required. The display name of the Model. 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) — Required. The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters.
Returns
- (::String) — Required. The display name of the Model. 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