Class Google::Cloud::AIPlatform::V1::Model (v0.1.0)

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.

#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.
Returns
  • (::String) — Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models.

#container_spec

def container_spec() -> ::Google::Cloud::AIPlatform::V1::ModelContainerSpec
Returns

#container_spec=

def container_spec=(value) -> ::Google::Cloud::AIPlatform::V1::ModelContainerSpec
Parameter
Returns

#create_time

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

#deployed_models

def deployed_models() -> ::Array<::Google::Cloud::AIPlatform::V1::DeployedModelRef>
Returns

#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 be 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 be 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 be 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

#etag

def etag() -> ::String
Returns
  • (::String) — Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

#etag=

def etag=(value) -> ::String
Parameter
  • value (::String) — Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
Returns
  • (::String) — Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

#explanation_spec

def explanation_spec() -> ::Google::Cloud::AIPlatform::V1::ExplanationSpec
Returns

#explanation_spec=

def explanation_spec=(value) -> ::Google::Cloud::AIPlatform::V1::ExplanationSpec
Parameter
Returns

#labels

def labels() -> ::Google::Protobuf::Map{::String => ::String}
Returns
  • (::Google::Protobuf::Map{::String => ::String}) — The labels with user-defined metadata to organize your Models.

    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.

#labels=

def labels=(value) -> ::Google::Protobuf::Map{::String => ::String}
Parameter
  • value (::Google::Protobuf::Map{::String => ::String}) — The labels with user-defined metadata to organize your Models.

    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.

Returns
  • (::Google::Protobuf::Map{::String => ::String}) — The labels with user-defined metadata to organize your Models.

    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.

#metadata

def metadata() -> ::Google::Protobuf::Value
Returns
  • (::Google::Protobuf::Value) — Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.

#metadata=

def metadata=(value) -> ::Google::Protobuf::Value
Parameter
  • value (::Google::Protobuf::Value) — Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
Returns
  • (::Google::Protobuf::Value) — Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.

#metadata_schema_uri

def metadata_schema_uri() -> ::String
Returns
  • (::String) — Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 Schema Object. AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. 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.

#metadata_schema_uri=

def metadata_schema_uri=(value) -> ::String
Parameter
  • value (::String) — Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 Schema Object. AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. 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.
Returns
  • (::String) — Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 Schema Object. AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. 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.

#name

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

#name=

def name=(value) -> ::String
Parameter
  • value (::String) — The resource name of the Model.
Returns
  • (::String) — The resource name of the Model.

#predict_schemata

def predict_schemata() -> ::Google::Cloud::AIPlatform::V1::PredictSchemata
Returns

#predict_schemata=

def predict_schemata=(value) -> ::Google::Cloud::AIPlatform::V1::PredictSchemata
Parameter
Returns

#supported_deployment_resources_types

def supported_deployment_resources_types() -> ::Array<::Google::Cloud::AIPlatform::V1::Model::DeploymentResourcesType>
Returns

#supported_export_formats

def supported_export_formats() -> ::Array<::Google::Cloud::AIPlatform::V1::Model::ExportFormat>
Returns

#supported_input_storage_formats

def supported_input_storage_formats() -> ::Array<::String>
Returns

#supported_output_storage_formats

def supported_output_storage_formats() -> ::Array<::String>
Returns

#training_pipeline

def training_pipeline() -> ::String
Returns
  • (::String) — Output only. The resource name of the TrainingPipeline that uploaded this Model, if any.

#update_time

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