Class: EasyML::Core::Tuner

Inherits:
Object
  • Object
show all
Includes:
GlueGun::DSL
Defined in:
lib/easy_ml/core/tuner.rb,
lib/easy_ml/core/tuner/adapters.rb,
lib/easy_ml/core/tuner/adapters/base_adapter.rb,
lib/easy_ml/core/tuner/adapters/xgboost_adapter.rb

Defined Under Namespace

Modules: Adapters

Instance Attribute Summary collapse

Instance Method Summary collapse

Instance Attribute Details

#results ⇒ Object

Returns the value of attribute results.



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# File 'lib/easy_ml/core/tuner.rb', line 18

def results
  @results
end

#study ⇒ Object

Returns the value of attribute study.



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# File 'lib/easy_ml/core/tuner.rb', line 18

def study
  @study
end

Instance Method Details

#loggers(_study, trial) ⇒ Object 



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# File 'lib/easy_ml/core/tuner.rb', line 38

def loggers(_study, trial)
  return unless trial.state.name == "FAIL"

  raise "Trial failed: Stopping optimization."
end

#pick_adapter ⇒ Object 



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# File 'lib/easy_ml/core/tuner.rb', line 79

def pick_adapter
  case model
  when EasyML::Core::Models::XGBoost, EasyML::Models::XGBoost
    Adapters::XGBoostAdapter
  end
end

#set_defaults! ⇒ Object

Raises:

  • (ArgumentError) 


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# File 'lib/easy_ml/core/tuner.rb', line 94

def set_defaults!
  unless task.present?
    self.task = model.task
    raise ArgumentError, "EasyML::Core::Tuner requires task (regression or classification)" unless task.present?
  end
  raise ArgumentError, "Objectives required for EasyML::Core::Tuner" unless objective.present?

  self.metrics = EasyML::Core::Model.new(task: task).allowed_metrics if metrics.nil? || metrics.empty?
end

#tune ⇒ Object 



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# File 'lib/easy_ml/core/tuner.rb', line 44

def tune
  set_defaults!

  @study = Optuna::Study.new
  @results = []
  model.task = task
  x_true, y_true = model.dataset.test(split_ys: true)
  tune_started_at = EST.now
  adapter = pick_adapter.new(model: model, config: config, tune_started_at: tune_started_at, y_true: y_true,
                             x_true: x_true)
  adapter.configure_callbacks

  @study.optimize(n_trials: n_trials, callbacks: [method(:loggers)]) do |trial|
    run_metrics = tune_once(trial, x_true, y_true, adapter)

    result = if model.evaluator.present?
               if model.evaluator_metric.present?
                 run_metrics[model.evaluator_metric]
               else
                 run_metrics[:custom]
               end
             else
               run_metrics[objective.to_sym]
             end
    @results.push(result)
    result
  rescue StandardError => e
    puts "Optuna failed with: #{e.message}"
  end

  raise "Optuna study failed" unless @study.respond_to?(:best_trial)

  @study.best_trial.params
end

#tune_once(trial, x_true, y_true, adapter) ⇒ Object 



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# File 'lib/easy_ml/core/tuner.rb', line 86

def tune_once(trial, x_true, y_true, adapter)
  adapter.run_trial(trial) do |model|
    y_pred = model.predict(y_true)
    model.metrics = metrics
    model.evaluate(y_pred: y_pred, y_true: y_true, x_true: x_true)
  end
end