Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1StudySpec

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 specification of a Study.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1StudySpec

Returns a new instance of GoogleCloudAiplatformV1StudySpec.



30322
30323
30324
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 30322

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

Instance Attribute Details

#algorithm ⇒ String

The search algorithm specified for the Study. Corresponds to the JSON property algorithm

Returns:

  • (String) 


30261
30262
30263
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 30261

def algorithm
  @algorithm
end

#convex_automated_stopping_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpec

Configuration for ConvexAutomatedStoppingSpec. When there are enough completed trials (configured by min_measurement_count), for pending trials with enough measurements and steps, the policy first computes an overestimate of the objective value at max_num_steps according to the slope of the incomplete objective value curve. No prediction can be made if the curve is completely flat. If the overestimation is worse than the best objective value of the completed trials, this pending trial will be early-stopped, but a last measurement will be added to the pending trial with max_num_steps and predicted objective value from the autoregression model. Corresponds to the JSON property convexAutomatedStoppingSpec

Returns:



30274
30275
30276
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 30274

def convex_automated_stopping_spec
  @convex_automated_stopping_spec
end

#decay_curve_stopping_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpec

The decay curve automated stopping rule builds a Gaussian Process Regressor to predict the final objective value of a Trial based on the already completed Trials and the intermediate measurements of the current Trial. Early stopping is requested for the current Trial if there is very low probability to exceed the optimal value found so far. Corresponds to the JSON property decayCurveStoppingSpec

Returns:



30283
30284
30285
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 30283

def decay_curve_stopping_spec
  @decay_curve_stopping_spec
end

#measurement_selection_type ⇒ String

Describe which measurement selection type will be used Corresponds to the JSON property measurementSelectionType

Returns:

  • (String) 


30288
30289
30290
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 30288

def measurement_selection_type
  @measurement_selection_type
end

#median_automated_stopping_spec ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpec

The median automated stopping rule stops a pending Trial if the Trial's best objective_value is strictly below the median 'performance' of all completed Trials reported up to the Trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the Trial in each measurement. Corresponds to the JSON property medianAutomatedStoppingSpec

Returns:



30297
30298
30299
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 30297

def median_automated_stopping_spec
  @median_automated_stopping_spec
end

#metrics ⇒ Array<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1StudySpecMetricSpec>

Required. Metric specs for the Study. Corresponds to the JSON property metrics

Returns:



30302
30303
30304
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 30302

def metrics
  @metrics
end

#observation_noise ⇒ String

The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline. Corresponds to the JSON property observationNoise

Returns:

  • (String) 


30309
30310
30311
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 30309

def observation_noise
  @observation_noise
end

#parameters ⇒ Array<Google::Apis::AiplatformV1::GoogleCloudAiplatformV1StudySpecParameterSpec>

Required. The set of parameters to tune. Corresponds to the JSON property parameters

Returns:



30314
30315
30316
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 30314

def parameters
  @parameters
end

#study_stopping_config ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1StudySpecStudyStoppingConfig

The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection. Corresponds to the JSON property studyStoppingConfig

Returns:



30320
30321
30322
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 30320

def study_stopping_config
  @study_stopping_config
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



30327
30328
30329
30330
30331
30332
30333
30334
30335
30336
30337
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 30327

def update!(**args)
  @algorithm = args[:algorithm] if args.key?(:algorithm)
  @convex_automated_stopping_spec = args[:convex_automated_stopping_spec] if args.key?(:convex_automated_stopping_spec)
  @decay_curve_stopping_spec = args[:decay_curve_stopping_spec] if args.key?(:decay_curve_stopping_spec)
  @measurement_selection_type = args[:measurement_selection_type] if args.key?(:measurement_selection_type)
  @median_automated_stopping_spec = args[:median_automated_stopping_spec] if args.key?(:median_automated_stopping_spec)
  @metrics = args[:metrics] if args.key?(:metrics)
  @observation_noise = args[:observation_noise] if args.key?(:observation_noise)
  @parameters = args[:parameters] if args.key?(:parameters)
  @study_stopping_config = args[:study_stopping_config] if args.key?(:study_stopping_config)
end