Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1TuningJob

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1/classes.rb,
lib/google/apis/aiplatform_v1/representations.rb,
lib/google/apis/aiplatform_v1/representations.rb

Overview

Represents a TuningJob that runs with Google owned models.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1TuningJob

Returns a new instance of GoogleCloudAiplatformV1TuningJob.



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49980

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#base_model ⇒ String

The base model that is being tuned. See Supported models. Corresponds to the JSON property baseModel

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49859

def base_model
  @base_model
end

#create_time ⇒ String

Output only. Time when the TuningJob was created. Corresponds to the JSON property createTime

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49864

def create_time
  @create_time
end

#description ⇒ String

Optional. The description of the TuningJob. Corresponds to the JSON property description

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49869

def description
  @description
end

#encryption_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1EncryptionSpec

Represents a customer-managed encryption key specification that can be applied to a Vertex AI resource. Corresponds to the JSON property encryptionSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49875

def encryption_spec
  @encryption_spec
end

#end_time ⇒ String

Output only. Time when the TuningJob entered any of the following JobStates: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED, JOB_STATE_EXPIRED. Corresponds to the JSON property endTime

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49882

def end_time
  @end_time
end

#error ⇒ Google::Apis::AiplatformV1::GoogleRpcStatus

The Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC. Each Status message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the API Design Guide. Corresponds to the JSON property error

Returns:



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49892

def error
  @error
end

#evaluate_dataset_runs ⇒ Array<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1EvaluateDatasetRun>

Output only. Evaluation runs for the Tuning Job. Corresponds to the JSON property evaluateDatasetRuns

Returns:



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49897

def evaluate_dataset_runs
  @evaluate_dataset_runs
end

#experiment ⇒ String

Output only. The Experiment associated with this TuningJob. Corresponds to the JSON property experiment

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49902

def experiment
  @experiment
end

#labels ⇒ Hash<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. Corresponds to the JSON property labels

Returns:

  • (Hash<String,String>) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49912

def labels
  @labels
end

#name ⇒ String

Output only. Identifier. Resource name of a TuningJob. Format: projects/ project/locations/location/tuningJobs/tuning_job` Corresponds to the JSON propertyname`

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49918

def name
  @name
end

#pre_tuned_model ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1PreTunedModel

A pre-tuned model for continuous tuning. Corresponds to the JSON property preTunedModel

Returns:



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49923

def pre_tuned_model
  @pre_tuned_model
end

#preference_optimization_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1PreferenceOptimizationSpec

Tuning Spec for Preference Optimization. Corresponds to the JSON property preferenceOptimizationSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49928

def preference_optimization_spec
  @preference_optimization_spec
end

#service_account ⇒ 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. Corresponds to the JSON property serviceAccount

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49937

def 
  @service_account
end

#start_time ⇒ String

Output only. Time when the TuningJob for the first time entered the JOB_STATE_RUNNING state. Corresponds to the JSON property startTime

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49943

def start_time
  @start_time
end

#state ⇒ String

Output only. The detailed state of the job. Corresponds to the JSON property state

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49948

def state
  @state
end

#supervised_tuning_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SupervisedTuningSpec

Tuning Spec for Supervised Tuning for first party models. Corresponds to the JSON property supervisedTuningSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49953

def supervised_tuning_spec
  @supervised_tuning_spec
end

#tuned_model ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1TunedModel

The Model Registry Model and Online Prediction Endpoint associated with this TuningJob. Corresponds to the JSON property tunedModel

Returns:



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49959

def tuned_model
  @tuned_model
end

#tuned_model_display_name ⇒ 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. Corresponds to the JSON property tunedModelDisplayName

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49968

def tuned_model_display_name
  @tuned_model_display_name
end

#tuning_data_stats ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1TuningDataStats

The tuning data statistic values for TuningJob. Corresponds to the JSON property tuningDataStats

Returns:



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49973

def tuning_data_stats
  @tuning_data_stats
end

#update_time ⇒ String

Output only. Time when the TuningJob was most recently updated. Corresponds to the JSON property updateTime

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49978

def update_time
  @update_time
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 49985

def update!(**args)
  @base_model = args[:base_model] if args.key?(:base_model)
  @create_time = args[:create_time] if args.key?(:create_time)
  @description = args[:description] if args.key?(:description)
  @encryption_spec = args[:encryption_spec] if args.key?(:encryption_spec)
  @end_time = args[:end_time] if args.key?(:end_time)
  @error = args[:error] if args.key?(:error)
  @evaluate_dataset_runs = args[:evaluate_dataset_runs] if args.key?(:evaluate_dataset_runs)
  @experiment = args[:experiment] if args.key?(:experiment)
  @labels = args[:labels] if args.key?(:labels)
  @name = args[:name] if args.key?(:name)
  @pre_tuned_model = args[:pre_tuned_model] if args.key?(:pre_tuned_model)
  @preference_optimization_spec = args[:preference_optimization_spec] if args.key?(:preference_optimization_spec)
  @service_account = args[:service_account] if args.key?(:service_account)
  @start_time = args[:start_time] if args.key?(:start_time)
  @state = args[:state] if args.key?(:state)
  @supervised_tuning_spec = args[:supervised_tuning_spec] if args.key?(:supervised_tuning_spec)
  @tuned_model = args[:tuned_model] if args.key?(:tuned_model)
  @tuned_model_display_name = args[:tuned_model_display_name] if args.key?(:tuned_model_display_name)
  @tuning_data_stats = args[:tuning_data_stats] if args.key?(:tuning_data_stats)
  @update_time = args[:update_time] if args.key?(:update_time)
end