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.



35471
35472
35473
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 35471

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) 


35410
35411
35412
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 35410

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:



35423
35424
35425
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 35423

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:



35432
35433
35434
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 35432

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) 


35437
35438
35439
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 35437

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:



35446
35447
35448
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 35446

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:



35451
35452
35453
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 35451

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) 


35458
35459
35460
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 35458

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:



35463
35464
35465
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 35463

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:



35469
35470
35471
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 35469

def study_stopping_config
  @study_stopping_config
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



35476
35477
35478
35479
35480
35481
35482
35483
35484
35485
35486
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 35476

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