Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1TuningJob

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1beta1/classes.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb

Overview

Represents a TuningJob that runs with Google owned models.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1TuningJob

Returns a new instance of GoogleCloudAiplatformV1beta1TuningJob.



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61649

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_v1beta1/classes.rb', line 61457

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_v1beta1/classes.rb', line 61462

def create_time
  @create_time
end

#custom_base_model ⇒ String

Optional. The user-provided path to custom model weights. Set this field to tune a custom model. The path must be a Cloud Storage directory that contains the model weights in .safetensors format along with associated model metadata files. If this field is set, the base_model field must still be set to indicate which base model the custom model is derived from. This feature is only available for open source models. Corresponds to the JSON property customBaseModel

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61472

def custom_base_model
  @custom_base_model
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_v1beta1/classes.rb', line 61477

def description
  @description
end

#distillation_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1DistillationSpec

Tuning Spec for Distillation. Corresponds to the JSON property distillationSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61482

def distillation_spec
  @distillation_spec
end

#encryption_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1EncryptionSpec

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_v1beta1/classes.rb', line 61488

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_v1beta1/classes.rb', line 61495

def end_time
  @end_time
end

#error ⇒ Google::Apis::AiplatformV1beta1::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_v1beta1/classes.rb', line 61505

def error
  @error
end

#evaluate_dataset_runs ⇒ Array<Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1EvaluateDatasetRun>

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

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61510

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_v1beta1/classes.rb', line 61515

def experiment
  @experiment
end

#full_fine_tuning_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1FullFineTuningSpec

Tuning Spec for Full Fine Tuning. Corresponds to the JSON property fullFineTuningSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61520

def full_fine_tuning_spec
  @full_fine_tuning_spec
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_v1beta1/classes.rb', line 61530

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_v1beta1/classes.rb', line 61536

def name
  @name
end

#output_uri ⇒ String

Optional. Cloud Storage path to the directory where tuning job outputs are written to. This field is only available and required for open source models. Corresponds to the JSON property outputUri

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61542

def output_uri
  @output_uri
end

#partner_model_tuning_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1PartnerModelTuningSpec

Tuning spec for Partner models. Corresponds to the JSON property partnerModelTuningSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61547

def partner_model_tuning_spec
  @partner_model_tuning_spec
end

#pipeline_job ⇒ String

Output only. The resource name of the PipelineJob associated with the TuningJob. Format: projects/project/locations/location/pipelineJobs/ pipeline_job`. Corresponds to the JSON propertypipelineJob`

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61554

def pipeline_job
  @pipeline_job
end

#pre_tuned_model ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1PreTunedModel

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

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61559

def pre_tuned_model
  @pre_tuned_model
end

#preference_optimization_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1PreferenceOptimizationSpec

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

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61564

def preference_optimization_spec
  @preference_optimization_spec
end

#satisfies_pzi ⇒ Boolean Also known as: satisfies_pzi?

Output only. Reserved for future use. Corresponds to the JSON property satisfiesPzi

Returns:

  • (Boolean) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61569

def satisfies_pzi
  @satisfies_pzi
end

#satisfies_pzs ⇒ Boolean Also known as: satisfies_pzs?

Output only. Reserved for future use. Corresponds to the JSON property satisfiesPzs

Returns:

  • (Boolean) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61575

def satisfies_pzs
  @satisfies_pzs
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_v1beta1/classes.rb', line 61585

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_v1beta1/classes.rb', line 61591

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_v1beta1/classes.rb', line 61596

def state
  @state
end

#supervised_tuning_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SupervisedTuningSpec

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_v1beta1/classes.rb', line 61601

def supervised_tuning_spec
  @supervised_tuning_spec
end

#tuned_model ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1TunedModel

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_v1beta1/classes.rb', line 61607

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_v1beta1/classes.rb', line 61616

def tuned_model_display_name
  @tuned_model_display_name
end

#tuning_data_stats ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1TuningDataStats

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

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61621

def tuning_data_stats
  @tuning_data_stats
end

#tuning_job_metadata ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1TuningJobMetadata

Tuning job metadata. Corresponds to the JSON property tuningJobMetadata

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61626

def tuning_job_metadata
  @tuning_job_metadata
end

#tuning_job_state ⇒ String

Output only. The detail state of the tuning job (while the overall JobState is running). Corresponds to the JSON property tuningJobState

Returns:

  • (String) 


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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61632

def tuning_job_state
  @tuning_job_state
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_v1beta1/classes.rb', line 61637

def update_time
  @update_time
end

#veo_lora_tuning_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1VeoLoraTuningSpec

Tuning Spec for Veo LoRA Model Tuning. Corresponds to the JSON property veoLoraTuningSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61642

def veo_lora_tuning_spec
  @veo_lora_tuning_spec
end

#veo_tuning_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1VeoTuningSpec

Tuning Spec for Veo Model Tuning. Corresponds to the JSON property veoTuningSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61647

def veo_tuning_spec
  @veo_tuning_spec
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 61654

def update!(**args)
  @base_model = args[:base_model] if args.key?(:base_model)
  @create_time = args[:create_time] if args.key?(:create_time)
  @custom_base_model = args[:custom_base_model] if args.key?(:custom_base_model)
  @description = args[:description] if args.key?(:description)
  @distillation_spec = args[:distillation_spec] if args.key?(:distillation_spec)
  @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)
  @full_fine_tuning_spec = args[:full_fine_tuning_spec] if args.key?(:full_fine_tuning_spec)
  @labels = args[:labels] if args.key?(:labels)
  @name = args[:name] if args.key?(:name)
  @output_uri = args[:output_uri] if args.key?(:output_uri)
  @partner_model_tuning_spec = args[:partner_model_tuning_spec] if args.key?(:partner_model_tuning_spec)
  @pipeline_job = args[:pipeline_job] if args.key?(:pipeline_job)
  @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)
  @satisfies_pzi = args[:satisfies_pzi] if args.key?(:satisfies_pzi)
  @satisfies_pzs = args[:satisfies_pzs] if args.key?(:satisfies_pzs)
  @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)
  @tuning_job_metadata = args[:tuning_job_metadata] if args.key?(:tuning_job_metadata)
  @tuning_job_state = args[:tuning_job_state] if args.key?(:tuning_job_state)
  @update_time = args[:update_time] if args.key?(:update_time)
  @veo_lora_tuning_spec = args[:veo_lora_tuning_spec] if args.key?(:veo_lora_tuning_spec)
  @veo_tuning_spec = args[:veo_tuning_spec] if args.key?(:veo_tuning_spec)
end