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

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

Represents the spec of a NasJob.

Defined Under Namespace

Classes: MultiTrialAlgorithmSpec

Instance Attribute Summary collapse

Instance Attribute Details

#multi_trial_algorithm_spec ⇒ ::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec

Returns The spec of multi-trial algorithms.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/nas_job.rb', line 135

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

  # The spec of multi-trial Neural Architecture Search (NAS).
  # @!attribute [rw] multi_trial_algorithm
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::MultiTrialAlgorithm]
  #     The multi-trial Neural Architecture Search (NAS) algorithm
  #     type. Defaults to `REINFORCEMENT_LEARNING`.
  # @!attribute [rw] metric
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::MetricSpec]
  #     Metric specs for the NAS job.
  #     Validation for this field is done at `multi_trial_algorithm_spec` field.
  # @!attribute [rw] search_trial_spec
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::SearchTrialSpec]
  #     Required. Spec for search trials.
  # @!attribute [rw] train_trial_spec
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::TrainTrialSpec]
  #     Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count]
  #     search trials will be trained for every M
  #     [TrainTrialSpec.frequency] trials searched.
  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
end

#resume_nas_job_id ⇒ ::String

Returns The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.

Returns:

  • (::String) —

    The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.



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# File 'proto_docs/google/cloud/aiplatform/v1/nas_job.rb', line 135

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

  # The spec of multi-trial Neural Architecture Search (NAS).
  # @!attribute [rw] multi_trial_algorithm
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::MultiTrialAlgorithm]
  #     The multi-trial Neural Architecture Search (NAS) algorithm
  #     type. Defaults to `REINFORCEMENT_LEARNING`.
  # @!attribute [rw] metric
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::MetricSpec]
  #     Metric specs for the NAS job.
  #     Validation for this field is done at `multi_trial_algorithm_spec` field.
  # @!attribute [rw] search_trial_spec
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::SearchTrialSpec]
  #     Required. Spec for search trials.
  # @!attribute [rw] train_trial_spec
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::TrainTrialSpec]
  #     Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count]
  #     search trials will be trained for every M
  #     [TrainTrialSpec.frequency] trials searched.
  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
end

#search_space_spec ⇒ ::String

Returns It defines the search space for Neural Architecture Search (NAS).

Returns:

  • (::String) —

    It defines the search space for Neural Architecture Search (NAS).



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# File 'proto_docs/google/cloud/aiplatform/v1/nas_job.rb', line 135

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

  # The spec of multi-trial Neural Architecture Search (NAS).
  # @!attribute [rw] multi_trial_algorithm
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::MultiTrialAlgorithm]
  #     The multi-trial Neural Architecture Search (NAS) algorithm
  #     type. Defaults to `REINFORCEMENT_LEARNING`.
  # @!attribute [rw] metric
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::MetricSpec]
  #     Metric specs for the NAS job.
  #     Validation for this field is done at `multi_trial_algorithm_spec` field.
  # @!attribute [rw] search_trial_spec
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::SearchTrialSpec]
  #     Required. Spec for search trials.
  # @!attribute [rw] train_trial_spec
  #   @return [::Google::Cloud::AIPlatform::V1::NasJobSpec::MultiTrialAlgorithmSpec::TrainTrialSpec]
  #     Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count]
  #     search trials will be trained for every M
  #     [TrainTrialSpec.frequency] trials searched.
  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
end