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.



29297
29298
29299
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29297

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) 


29236
29237
29238
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29236

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:



29249
29250
29251
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29249

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:



29258
29259
29260
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29258

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) 


29263
29264
29265
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29263

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:



29272
29273
29274
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29272

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:



29277
29278
29279
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29277

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) 


29284
29285
29286
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29284

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:



29289
29290
29291
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29289

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:



29295
29296
29297
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29295

def study_stopping_config
  @study_stopping_config
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



29302
29303
29304
29305
29306
29307
29308
29309
29310
29311
29312
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 29302

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