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Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::TuningJob (v1.30.0)

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

Represents a TuningJob that runs with Google owned models.

Inherits

Object

Extended By

Google::Protobuf::MessageExts::ClassMethods

Includes

Google::Protobuf::MessageExts

Methods

#base_model

def base_model() -> ::String

Returns

(::String) — The base model that is being tuned. See Supported models.

Note: The following fields are mutually exclusive: base_model, pre_tuned_model. If a field in that set is populated, all other fields in the set will automatically be cleared.

#base_model=

def base_model=(value) -> ::String

Parameter

value (::String) — The base model that is being tuned. See Supported models.

Note: The following fields are mutually exclusive: base_model, pre_tuned_model. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns

(::String) — The base model that is being tuned. See Supported models.

Note: The following fields are mutually exclusive: base_model, pre_tuned_model. If a field in that set is populated, all other fields in the set will automatically be cleared.

#create_time

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

Returns

(::Google::Protobuf::Timestamp) — Output only. Time when the TuningJob was created.

#description

def description() -> ::String

Returns

(::String) — Optional. The description of the TuningJob.

#description=

def description=(value) -> ::String

Parameter

value (::String) — Optional. The description of the TuningJob.

Returns

(::String) — Optional. The description of the TuningJob.

#encryption_spec

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

Returns

(::Google::Cloud::AIPlatform::V1::EncryptionSpec) — Customer-managed encryption key options for a TuningJob. If this is set, then all resources created by the TuningJob will be encrypted with the provided encryption key.

#encryption_spec=

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

Parameter

value (::Google::Cloud::AIPlatform::V1::EncryptionSpec) — Customer-managed encryption key options for a TuningJob. If this is set, then all resources created by the TuningJob will be encrypted with the provided encryption key.

Returns

(::Google::Cloud::AIPlatform::V1::EncryptionSpec) — Customer-managed encryption key options for a TuningJob. If this is set, then all resources created by the TuningJob will be encrypted with the provided encryption key.

#end_time

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

Returns

(::Google::Protobuf::Timestamp) — Output only. Time when the TuningJob entered any of the following JobStates: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED, JOB_STATE_EXPIRED.

#error

def error() -> ::Google::Rpc::Status

Returns

(::Google::Rpc::Status) — Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

#experiment

def experiment() -> ::String

Returns

(::String) — Output only. The Experiment associated with this TuningJob.

#labels

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

Returns

(::Google::Protobuf::Map{::String => ::String}) — Optional. The labels with user-defined metadata to organize TuningJob and generated resources such as Model and Endpoint.

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}) — Optional. The labels with user-defined metadata to organize TuningJob and generated resources such as Model and Endpoint.

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}) — Optional. The labels with user-defined metadata to organize TuningJob and generated resources such as Model and Endpoint.

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.

#name

def name() -> ::String

Returns

(::String) — Output only. Identifier. Resource name of a TuningJob. Format: projects/{project}/locations/{location}/tuningJobs/{tuning_job}

#pre_tuned_model

def pre_tuned_model() -> ::Google::Cloud::AIPlatform::V1::PreTunedModel

Returns

(::Google::Cloud::AIPlatform::V1::PreTunedModel) — The pre-tuned model for continuous tuning.

Note: The following fields are mutually exclusive: pre_tuned_model, base_model. If a field in that set is populated, all other fields in the set will automatically be cleared.

#pre_tuned_model=

def pre_tuned_model=(value) -> ::Google::Cloud::AIPlatform::V1::PreTunedModel

Parameter

value (::Google::Cloud::AIPlatform::V1::PreTunedModel) — The pre-tuned model for continuous tuning.

Note: The following fields are mutually exclusive: pre_tuned_model, base_model. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns

(::Google::Cloud::AIPlatform::V1::PreTunedModel) — The pre-tuned model for continuous tuning.

Note: The following fields are mutually exclusive: pre_tuned_model, base_model. If a field in that set is populated, all other fields in the set will automatically be cleared.

#service_account

def service_account() -> ::String

Returns

(::String) — The service account that the tuningJob workload runs as. If not specified, the Vertex AI Secure Fine-Tuned Service Agent in the project will be used. See https://cloud.google.com/iam/docs/service-agents#vertex-ai-secure-fine-tuning-service-agent

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 tuningJob workload runs as. If not specified, the Vertex AI Secure Fine-Tuned Service Agent in the project will be used. See https://cloud.google.com/iam/docs/service-agents#vertex-ai-secure-fine-tuning-service-agent

Users starting the pipeline must have the iam.serviceAccounts.actAs permission on this service account.

Returns

(::String) — The service account that the tuningJob workload runs as. If not specified, the Vertex AI Secure Fine-Tuned Service Agent in the project will be used. See https://cloud.google.com/iam/docs/service-agents#vertex-ai-secure-fine-tuning-service-agent

Users starting the pipeline must have the iam.serviceAccounts.actAs permission on this service account.

#start_time

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

Returns

(::Google::Protobuf::Timestamp) — Output only. Time when the TuningJob for the first time entered the JOB_STATE_RUNNING state.

#state

def state() -> ::Google::Cloud::AIPlatform::V1::JobState

Returns

(::Google::Cloud::AIPlatform::V1::JobState) — Output only. The detailed state of the job.

#supervised_tuning_spec

def supervised_tuning_spec() -> ::Google::Cloud::AIPlatform::V1::SupervisedTuningSpec

Returns

(::Google::Cloud::AIPlatform::V1::SupervisedTuningSpec) — Tuning Spec for Supervised Fine Tuning.

#supervised_tuning_spec=

def supervised_tuning_spec=(value) -> ::Google::Cloud::AIPlatform::V1::SupervisedTuningSpec

Parameter

value (::Google::Cloud::AIPlatform::V1::SupervisedTuningSpec) — Tuning Spec for Supervised Fine Tuning.

Returns

(::Google::Cloud::AIPlatform::V1::SupervisedTuningSpec) — Tuning Spec for Supervised Fine Tuning.

#tuned_model

def tuned_model() -> ::Google::Cloud::AIPlatform::V1::TunedModel

Returns

(::Google::Cloud::AIPlatform::V1::TunedModel) — Output only. The tuned model resources associated with this TuningJob.

#tuned_model_display_name

def tuned_model_display_name() -> ::String

Returns

(::String) — Optional. The display name of the TunedModel. The name can be up to 128 characters long and can consist of any UTF-8 characters. For continuous tuning, tuned_model_display_name will by default use the same display name as the pre-tuned model. If a new display name is provided, the tuning job will create a new model instead of a new version.

#tuned_model_display_name=

def tuned_model_display_name=(value) -> ::String

Parameter

value (::String) — Optional. The display name of the TunedModel. The name can be up to 128 characters long and can consist of any UTF-8 characters. For continuous tuning, tuned_model_display_name will by default use the same display name as the pre-tuned model. If a new display name is provided, the tuning job will create a new model instead of a new version.

Returns

(::String) — Optional. The display name of the TunedModel. The name can be up to 128 characters long and can consist of any UTF-8 characters. For continuous tuning, tuned_model_display_name will by default use the same display name as the pre-tuned model. If a new display name is provided, the tuning job will create a new model instead of a new version.

#tuning_data_stats

def tuning_data_stats() -> ::Google::Cloud::AIPlatform::V1::TuningDataStats

Returns

(::Google::Cloud::AIPlatform::V1::TuningDataStats) — Output only. The tuning data statistics associated with this TuningJob.

#update_time

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

Returns

(::Google::Protobuf::Timestamp) — Output only. Time when the TuningJob was most recently updated.