Class: Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec

Inherits:
Object
  • Object
show all
Extended by:
Protobuf::MessageExts::ClassMethods
Includes:
Protobuf::MessageExts
Defined in:
proto_docs/google/cloud/aiplatform/v1/nas_job.rb

Overview

The spec of multi-trial Neural Architecture Search (NAS).

Defined Under Namespace

Modules: MultiTrialAlgorithm Classes: MetricSpec, SearchTrialSpec, TrainTrialSpec

Instance Attribute Summary collapse

Instance Attribute Details

#metric ⇒ ::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::MetricSpec

Returns Metric specs for the NAS job. Validation for this field is done at multi_trial_algorithm_spec field.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/nas_job.rb', line 156

class MultiTrialAlgorithmSpec
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Represents a metric to optimize.
  # @!attribute [rw] metric_id
  #   @return [::String]
  #     Required. The ID of the metric. Must not contain whitespaces.
  # @!attribute [rw] goal
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::MetricSpec::GoalType]
  #     Required. The optimization goal of the metric.
  class MetricSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # The available types of optimization goals.
    module GoalType
      # Goal Type will default to maximize.
      GOAL_TYPE_UNSPECIFIED = 0

      # Maximize the goal metric.
      MAXIMIZE = 1

      # Minimize the goal metric.
      MINIMIZE = 2
    end
  end

  # Represent spec for search trials.
  # @!attribute [rw] search_trial_job_spec
  #   @return [::Google::Cloud::AIPlatform::V1::CustomJobSpec]
  #     Required. The spec of a search trial job. The same spec applies to
  #     all search trials.
  # @!attribute [rw] max_trial_count
  #   @return [::Integer]
  #     Required. The maximum number of Neural Architecture Search (NAS) trials
  #     to run.
  # @!attribute [rw] max_parallel_trial_count
  #   @return [::Integer]
  #     Required. The maximum number of trials to run in parallel.
  # @!attribute [rw] max_failed_trial_count
  #   @return [::Integer]
  #     The number of failed trials that need to be seen before failing
  #     the NasJob.
  #
  #     If set to 0, Vertex AI decides how many trials must fail
  #     before the whole job fails.
  class SearchTrialSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Represent spec for train trials.
  # @!attribute [rw] train_trial_job_spec
  #   @return [::Google::Cloud::AIPlatform::V1::CustomJobSpec]
  #     Required. The spec of a train trial job. The same spec applies to
  #     all train trials.
  # @!attribute [rw] max_parallel_trial_count
  #   @return [::Integer]
  #     Required. The maximum number of trials to run in parallel.
  # @!attribute [rw] frequency
  #   @return [::Integer]
  #     Required. Frequency of search trials to start train stage. Top N
  #     [TrainTrialSpec.max_parallel_trial_count]
  #     search trials will be trained for every M
  #     [TrainTrialSpec.frequency] trials searched.
  class TrainTrialSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # The available types of multi-trial algorithms.
  module MultiTrialAlgorithm
    # Defaults to `REINFORCEMENT_LEARNING`.
    MULTI_TRIAL_ALGORITHM_UNSPECIFIED = 0

    # The Reinforcement Learning Algorithm for Multi-trial Neural
    # Architecture Search (NAS).
    REINFORCEMENT_LEARNING = 1

    # The Grid Search Algorithm for Multi-trial Neural
    # Architecture Search (NAS).
    GRID_SEARCH = 2
  end
end

#multi_trial_algorithm ⇒ ::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::MultiTrialAlgorithm

Returns The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to REINFORCEMENT_LEARNING.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/nas_job.rb', line 156

class MultiTrialAlgorithmSpec
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Represents a metric to optimize.
  # @!attribute [rw] metric_id
  #   @return [::String]
  #     Required. The ID of the metric. Must not contain whitespaces.
  # @!attribute [rw] goal
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::MetricSpec::GoalType]
  #     Required. The optimization goal of the metric.
  class MetricSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # The available types of optimization goals.
    module GoalType
      # Goal Type will default to maximize.
      GOAL_TYPE_UNSPECIFIED = 0

      # Maximize the goal metric.
      MAXIMIZE = 1

      # Minimize the goal metric.
      MINIMIZE = 2
    end
  end

  # Represent spec for search trials.
  # @!attribute [rw] search_trial_job_spec
  #   @return [::Google::Cloud::AIPlatform::V1::CustomJobSpec]
  #     Required. The spec of a search trial job. The same spec applies to
  #     all search trials.
  # @!attribute [rw] max_trial_count
  #   @return [::Integer]
  #     Required. The maximum number of Neural Architecture Search (NAS) trials
  #     to run.
  # @!attribute [rw] max_parallel_trial_count
  #   @return [::Integer]
  #     Required. The maximum number of trials to run in parallel.
  # @!attribute [rw] max_failed_trial_count
  #   @return [::Integer]
  #     The number of failed trials that need to be seen before failing
  #     the NasJob.
  #
  #     If set to 0, Vertex AI decides how many trials must fail
  #     before the whole job fails.
  class SearchTrialSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Represent spec for train trials.
  # @!attribute [rw] train_trial_job_spec
  #   @return [::Google::Cloud::AIPlatform::V1::CustomJobSpec]
  #     Required. The spec of a train trial job. The same spec applies to
  #     all train trials.
  # @!attribute [rw] max_parallel_trial_count
  #   @return [::Integer]
  #     Required. The maximum number of trials to run in parallel.
  # @!attribute [rw] frequency
  #   @return [::Integer]
  #     Required. Frequency of search trials to start train stage. Top N
  #     [TrainTrialSpec.max_parallel_trial_count]
  #     search trials will be trained for every M
  #     [TrainTrialSpec.frequency] trials searched.
  class TrainTrialSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # The available types of multi-trial algorithms.
  module MultiTrialAlgorithm
    # Defaults to `REINFORCEMENT_LEARNING`.
    MULTI_TRIAL_ALGORITHM_UNSPECIFIED = 0

    # The Reinforcement Learning Algorithm for Multi-trial Neural
    # Architecture Search (NAS).
    REINFORCEMENT_LEARNING = 1

    # The Grid Search Algorithm for Multi-trial Neural
    # Architecture Search (NAS).
    GRID_SEARCH = 2
  end
end

#search_trial_spec ⇒ ::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::SearchTrialSpec

Returns Required. Spec for search trials.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/nas_job.rb', line 156

class MultiTrialAlgorithmSpec
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Represents a metric to optimize.
  # @!attribute [rw] metric_id
  #   @return [::String]
  #     Required. The ID of the metric. Must not contain whitespaces.
  # @!attribute [rw] goal
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::MetricSpec::GoalType]
  #     Required. The optimization goal of the metric.
  class MetricSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # The available types of optimization goals.
    module GoalType
      # Goal Type will default to maximize.
      GOAL_TYPE_UNSPECIFIED = 0

      # Maximize the goal metric.
      MAXIMIZE = 1

      # Minimize the goal metric.
      MINIMIZE = 2
    end
  end

  # Represent spec for search trials.
  # @!attribute [rw] search_trial_job_spec
  #   @return [::Google::Cloud::AIPlatform::V1::CustomJobSpec]
  #     Required. The spec of a search trial job. The same spec applies to
  #     all search trials.
  # @!attribute [rw] max_trial_count
  #   @return [::Integer]
  #     Required. The maximum number of Neural Architecture Search (NAS) trials
  #     to run.
  # @!attribute [rw] max_parallel_trial_count
  #   @return [::Integer]
  #     Required. The maximum number of trials to run in parallel.
  # @!attribute [rw] max_failed_trial_count
  #   @return [::Integer]
  #     The number of failed trials that need to be seen before failing
  #     the NasJob.
  #
  #     If set to 0, Vertex AI decides how many trials must fail
  #     before the whole job fails.
  class SearchTrialSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Represent spec for train trials.
  # @!attribute [rw] train_trial_job_spec
  #   @return [::Google::Cloud::AIPlatform::V1::CustomJobSpec]
  #     Required. The spec of a train trial job. The same spec applies to
  #     all train trials.
  # @!attribute [rw] max_parallel_trial_count
  #   @return [::Integer]
  #     Required. The maximum number of trials to run in parallel.
  # @!attribute [rw] frequency
  #   @return [::Integer]
  #     Required. Frequency of search trials to start train stage. Top N
  #     [TrainTrialSpec.max_parallel_trial_count]
  #     search trials will be trained for every M
  #     [TrainTrialSpec.frequency] trials searched.
  class TrainTrialSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # The available types of multi-trial algorithms.
  module MultiTrialAlgorithm
    # Defaults to `REINFORCEMENT_LEARNING`.
    MULTI_TRIAL_ALGORITHM_UNSPECIFIED = 0

    # The Reinforcement Learning Algorithm for Multi-trial Neural
    # Architecture Search (NAS).
    REINFORCEMENT_LEARNING = 1

    # The Grid Search Algorithm for Multi-trial Neural
    # Architecture Search (NAS).
    GRID_SEARCH = 2
  end
end

#train_trial_spec ⇒ ::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::TrainTrialSpec

Returns Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/nas_job.rb', line 156

class MultiTrialAlgorithmSpec
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Represents a metric to optimize.
  # @!attribute [rw] metric_id
  #   @return [::String]
  #     Required. The ID of the metric. Must not contain whitespaces.
  # @!attribute [rw] goal
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::MetricSpec::GoalType]
  #     Required. The optimization goal of the metric.
  class MetricSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # The available types of optimization goals.
    module GoalType
      # Goal Type will default to maximize.
      GOAL_TYPE_UNSPECIFIED = 0

      # Maximize the goal metric.
      MAXIMIZE = 1

      # Minimize the goal metric.
      MINIMIZE = 2
    end
  end

  # Represent spec for search trials.
  # @!attribute [rw] search_trial_job_spec
  #   @return [::Google::Cloud::AIPlatform::V1::CustomJobSpec]
  #     Required. The spec of a search trial job. The same spec applies to
  #     all search trials.
  # @!attribute [rw] max_trial_count
  #   @return [::Integer]
  #     Required. The maximum number of Neural Architecture Search (NAS) trials
  #     to run.
  # @!attribute [rw] max_parallel_trial_count
  #   @return [::Integer]
  #     Required. The maximum number of trials to run in parallel.
  # @!attribute [rw] max_failed_trial_count
  #   @return [::Integer]
  #     The number of failed trials that need to be seen before failing
  #     the NasJob.
  #
  #     If set to 0, Vertex AI decides how many trials must fail
  #     before the whole job fails.
  class SearchTrialSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Represent spec for train trials.
  # @!attribute [rw] train_trial_job_spec
  #   @return [::Google::Cloud::AIPlatform::V1::CustomJobSpec]
  #     Required. The spec of a train trial job. The same spec applies to
  #     all train trials.
  # @!attribute [rw] max_parallel_trial_count
  #   @return [::Integer]
  #     Required. The maximum number of trials to run in parallel.
  # @!attribute [rw] frequency
  #   @return [::Integer]
  #     Required. Frequency of search trials to start train stage. Top N
  #     [TrainTrialSpec.max_parallel_trial_count]
  #     search trials will be trained for every M
  #     [TrainTrialSpec.frequency] trials searched.
  class TrainTrialSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # The available types of multi-trial algorithms.
  module MultiTrialAlgorithm
    # Defaults to `REINFORCEMENT_LEARNING`.
    MULTI_TRIAL_ALGORITHM_UNSPECIFIED = 0

    # The Reinforcement Learning Algorithm for Multi-trial Neural
    # Architecture Search (NAS).
    REINFORCEMENT_LEARNING = 1

    # The Grid Search Algorithm for Multi-trial Neural
    # Architecture Search (NAS).
    GRID_SEARCH = 2
  end
end