Class: Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec

Inherits:

Object

• Object
• Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec

Extended by:

Protobuf::MessageExts::ClassMethods

Includes:

Protobuf::MessageExts

Defined in:

proto_docs/google/cloud/aiplatform/v1/study.rb

Overview

Represents a single parameter to optimize.

Defined Under Namespace

Modules: ScaleType Classes: CategoricalValueSpec, ConditionalParameterSpec, DiscreteValueSpec, DoubleValueSpec, IntegerValueSpec

Instance Attribute Summary

• #categorical_value_spec ⇒ ::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::CategoricalValueSpec

  The value spec for a 'CATEGORICAL' parameter.

• #conditional_parameter_specs ⇒ ::Array<::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec>

  A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition.

• #discrete_value_spec ⇒ ::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::DiscreteValueSpec

  The value spec for a 'DISCRETE' parameter.

• #double_value_spec ⇒ ::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::DoubleValueSpec

  The value spec for a 'DOUBLE' parameter.

• #integer_value_spec ⇒ ::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::IntegerValueSpec

  The value spec for an 'INTEGER' parameter.

• #parameter_id ⇒ ::String

  Required.

• #scale_type ⇒ ::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ScaleType

  How the parameter should be scaled.

Instance Attribute Details

#categorical_value_spec ⇒ ::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::CategoricalValueSpec

Returns The value spec for a 'CATEGORICAL' parameter.

Returns:

• (::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::CategoricalValueSpec) —

  The value spec for a 'CATEGORICAL' parameter.

# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 329

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

  # Value specification for a parameter in `DOUBLE` type.
  # @!attribute [rw] min_value
  #   @return [::Float]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Float]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DOUBLE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DoubleValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `INTEGER` type.
  # @!attribute [rw] min_value
  #   @return [::Integer]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Integer]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Integer]
  #     A default value for an `INTEGER` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class IntegerValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `CATEGORICAL` type.
  # @!attribute [rw] values
  #   @return [::Array<::String>]
  #     Required. The list of possible categories.
  # @!attribute [rw] default_value
  #   @return [::String]
  #     A default value for a `CATEGORICAL` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class CategoricalValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `DISCRETE` type.
  # @!attribute [rw] values
  #   @return [::Array<::Float>]
  #     Required. A list of possible values.
  #     The list should be in increasing order and at least 1e-10 apart.
  #     For instance, this parameter might have possible settings of 1.5, 2.5,
  #     and 4.0. This list should not contain more than 1,000 values.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DISCRETE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.  It automatically rounds to the
  #     nearest feasible discrete point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DiscreteValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Represents a parameter spec with condition from its parent parameter.
  # @!attribute [rw] parent_discrete_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::DiscreteValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `DISCRETE` type.
  # @!attribute [rw] parent_int_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::IntValueCondition]
  #     The spec for matching values from a parent parameter of `INTEGER`
  #     type.
  # @!attribute [rw] parent_categorical_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::CategoricalValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `CATEGORICAL` type.
  # @!attribute [rw] parameter_spec
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec]
  #     Required. The spec for a conditional parameter.
  class ConditionalParameterSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Represents the spec to match discrete values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Float>]
    #     Required. Matches values of the parent parameter of 'DISCRETE' type.
    #     All values must exist in `discrete_value_spec` of parent parameter.
    #
    #     The Epsilon of the value matching is 1e-10.
    class DiscreteValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match integer values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Integer>]
    #     Required. Matches values of the parent parameter of 'INTEGER' type.
    #     All values must lie in `integer_value_spec` of parent parameter.
    class IntValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match categorical values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::String>]
    #     Required. Matches values of the parent parameter of 'CATEGORICAL'
    #     type. All values must exist in `categorical_value_spec` of parent
    #     parameter.
    class CategoricalValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end
  end

  # The type of scaling that should be applied to this parameter.
  module ScaleType
    # By default, no scaling is applied.
    SCALE_TYPE_UNSPECIFIED = 0

    # Scales the feasible space to (0, 1) linearly.
    UNIT_LINEAR_SCALE = 1

    # Scales the feasible space logarithmically to (0, 1). The entire
    # feasible space must be strictly positive.
    UNIT_LOG_SCALE = 2

    # Scales the feasible space "reverse" logarithmically to (0, 1). The
    # result is that values close to the top of the feasible space are spread
    # out more than points near the bottom. The entire feasible space must be
    # strictly positive.
    UNIT_REVERSE_LOG_SCALE = 3
  end
end

#conditional_parameter_specs ⇒ ::Array<::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec>

Returns A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition.

If two items in conditional_parameter_specs have the same name, they must have disjoint parent_value_condition.

Returns:

• (::Array<::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec>) —

  A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition.

  If two items in conditional_parameter_specs have the same name, they must have disjoint parent_value_condition.

# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 329

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

  # Value specification for a parameter in `DOUBLE` type.
  # @!attribute [rw] min_value
  #   @return [::Float]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Float]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DOUBLE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DoubleValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `INTEGER` type.
  # @!attribute [rw] min_value
  #   @return [::Integer]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Integer]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Integer]
  #     A default value for an `INTEGER` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class IntegerValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `CATEGORICAL` type.
  # @!attribute [rw] values
  #   @return [::Array<::String>]
  #     Required. The list of possible categories.
  # @!attribute [rw] default_value
  #   @return [::String]
  #     A default value for a `CATEGORICAL` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class CategoricalValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `DISCRETE` type.
  # @!attribute [rw] values
  #   @return [::Array<::Float>]
  #     Required. A list of possible values.
  #     The list should be in increasing order and at least 1e-10 apart.
  #     For instance, this parameter might have possible settings of 1.5, 2.5,
  #     and 4.0. This list should not contain more than 1,000 values.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DISCRETE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.  It automatically rounds to the
  #     nearest feasible discrete point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DiscreteValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Represents a parameter spec with condition from its parent parameter.
  # @!attribute [rw] parent_discrete_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::DiscreteValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `DISCRETE` type.
  # @!attribute [rw] parent_int_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::IntValueCondition]
  #     The spec for matching values from a parent parameter of `INTEGER`
  #     type.
  # @!attribute [rw] parent_categorical_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::CategoricalValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `CATEGORICAL` type.
  # @!attribute [rw] parameter_spec
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec]
  #     Required. The spec for a conditional parameter.
  class ConditionalParameterSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Represents the spec to match discrete values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Float>]
    #     Required. Matches values of the parent parameter of 'DISCRETE' type.
    #     All values must exist in `discrete_value_spec` of parent parameter.
    #
    #     The Epsilon of the value matching is 1e-10.
    class DiscreteValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match integer values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Integer>]
    #     Required. Matches values of the parent parameter of 'INTEGER' type.
    #     All values must lie in `integer_value_spec` of parent parameter.
    class IntValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match categorical values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::String>]
    #     Required. Matches values of the parent parameter of 'CATEGORICAL'
    #     type. All values must exist in `categorical_value_spec` of parent
    #     parameter.
    class CategoricalValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end
  end

  # The type of scaling that should be applied to this parameter.
  module ScaleType
    # By default, no scaling is applied.
    SCALE_TYPE_UNSPECIFIED = 0

    # Scales the feasible space to (0, 1) linearly.
    UNIT_LINEAR_SCALE = 1

    # Scales the feasible space logarithmically to (0, 1). The entire
    # feasible space must be strictly positive.
    UNIT_LOG_SCALE = 2

    # Scales the feasible space "reverse" logarithmically to (0, 1). The
    # result is that values close to the top of the feasible space are spread
    # out more than points near the bottom. The entire feasible space must be
    # strictly positive.
    UNIT_REVERSE_LOG_SCALE = 3
  end
end

#discrete_value_spec ⇒ ::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::DiscreteValueSpec

Returns The value spec for a 'DISCRETE' parameter.

Returns:

• (::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::DiscreteValueSpec) —

  The value spec for a 'DISCRETE' parameter.

# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 329

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

  # Value specification for a parameter in `DOUBLE` type.
  # @!attribute [rw] min_value
  #   @return [::Float]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Float]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DOUBLE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DoubleValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `INTEGER` type.
  # @!attribute [rw] min_value
  #   @return [::Integer]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Integer]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Integer]
  #     A default value for an `INTEGER` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class IntegerValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `CATEGORICAL` type.
  # @!attribute [rw] values
  #   @return [::Array<::String>]
  #     Required. The list of possible categories.
  # @!attribute [rw] default_value
  #   @return [::String]
  #     A default value for a `CATEGORICAL` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class CategoricalValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `DISCRETE` type.
  # @!attribute [rw] values
  #   @return [::Array<::Float>]
  #     Required. A list of possible values.
  #     The list should be in increasing order and at least 1e-10 apart.
  #     For instance, this parameter might have possible settings of 1.5, 2.5,
  #     and 4.0. This list should not contain more than 1,000 values.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DISCRETE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.  It automatically rounds to the
  #     nearest feasible discrete point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DiscreteValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Represents a parameter spec with condition from its parent parameter.
  # @!attribute [rw] parent_discrete_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::DiscreteValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `DISCRETE` type.
  # @!attribute [rw] parent_int_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::IntValueCondition]
  #     The spec for matching values from a parent parameter of `INTEGER`
  #     type.
  # @!attribute [rw] parent_categorical_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::CategoricalValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `CATEGORICAL` type.
  # @!attribute [rw] parameter_spec
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec]
  #     Required. The spec for a conditional parameter.
  class ConditionalParameterSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Represents the spec to match discrete values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Float>]
    #     Required. Matches values of the parent parameter of 'DISCRETE' type.
    #     All values must exist in `discrete_value_spec` of parent parameter.
    #
    #     The Epsilon of the value matching is 1e-10.
    class DiscreteValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match integer values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Integer>]
    #     Required. Matches values of the parent parameter of 'INTEGER' type.
    #     All values must lie in `integer_value_spec` of parent parameter.
    class IntValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match categorical values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::String>]
    #     Required. Matches values of the parent parameter of 'CATEGORICAL'
    #     type. All values must exist in `categorical_value_spec` of parent
    #     parameter.
    class CategoricalValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end
  end

  # The type of scaling that should be applied to this parameter.
  module ScaleType
    # By default, no scaling is applied.
    SCALE_TYPE_UNSPECIFIED = 0

    # Scales the feasible space to (0, 1) linearly.
    UNIT_LINEAR_SCALE = 1

    # Scales the feasible space logarithmically to (0, 1). The entire
    # feasible space must be strictly positive.
    UNIT_LOG_SCALE = 2

    # Scales the feasible space "reverse" logarithmically to (0, 1). The
    # result is that values close to the top of the feasible space are spread
    # out more than points near the bottom. The entire feasible space must be
    # strictly positive.
    UNIT_REVERSE_LOG_SCALE = 3
  end
end

#double_value_spec ⇒ ::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::DoubleValueSpec

Returns The value spec for a 'DOUBLE' parameter.

Returns:

• (::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::DoubleValueSpec) —

  The value spec for a 'DOUBLE' parameter.

# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 329

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

  # Value specification for a parameter in `DOUBLE` type.
  # @!attribute [rw] min_value
  #   @return [::Float]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Float]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DOUBLE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DoubleValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `INTEGER` type.
  # @!attribute [rw] min_value
  #   @return [::Integer]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Integer]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Integer]
  #     A default value for an `INTEGER` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class IntegerValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `CATEGORICAL` type.
  # @!attribute [rw] values
  #   @return [::Array<::String>]
  #     Required. The list of possible categories.
  # @!attribute [rw] default_value
  #   @return [::String]
  #     A default value for a `CATEGORICAL` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class CategoricalValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `DISCRETE` type.
  # @!attribute [rw] values
  #   @return [::Array<::Float>]
  #     Required. A list of possible values.
  #     The list should be in increasing order and at least 1e-10 apart.
  #     For instance, this parameter might have possible settings of 1.5, 2.5,
  #     and 4.0. This list should not contain more than 1,000 values.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DISCRETE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.  It automatically rounds to the
  #     nearest feasible discrete point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DiscreteValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Represents a parameter spec with condition from its parent parameter.
  # @!attribute [rw] parent_discrete_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::DiscreteValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `DISCRETE` type.
  # @!attribute [rw] parent_int_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::IntValueCondition]
  #     The spec for matching values from a parent parameter of `INTEGER`
  #     type.
  # @!attribute [rw] parent_categorical_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::CategoricalValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `CATEGORICAL` type.
  # @!attribute [rw] parameter_spec
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec]
  #     Required. The spec for a conditional parameter.
  class ConditionalParameterSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Represents the spec to match discrete values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Float>]
    #     Required. Matches values of the parent parameter of 'DISCRETE' type.
    #     All values must exist in `discrete_value_spec` of parent parameter.
    #
    #     The Epsilon of the value matching is 1e-10.
    class DiscreteValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match integer values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Integer>]
    #     Required. Matches values of the parent parameter of 'INTEGER' type.
    #     All values must lie in `integer_value_spec` of parent parameter.
    class IntValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match categorical values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::String>]
    #     Required. Matches values of the parent parameter of 'CATEGORICAL'
    #     type. All values must exist in `categorical_value_spec` of parent
    #     parameter.
    class CategoricalValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end
  end

  # The type of scaling that should be applied to this parameter.
  module ScaleType
    # By default, no scaling is applied.
    SCALE_TYPE_UNSPECIFIED = 0

    # Scales the feasible space to (0, 1) linearly.
    UNIT_LINEAR_SCALE = 1

    # Scales the feasible space logarithmically to (0, 1). The entire
    # feasible space must be strictly positive.
    UNIT_LOG_SCALE = 2

    # Scales the feasible space "reverse" logarithmically to (0, 1). The
    # result is that values close to the top of the feasible space are spread
    # out more than points near the bottom. The entire feasible space must be
    # strictly positive.
    UNIT_REVERSE_LOG_SCALE = 3
  end
end

#integer_value_spec ⇒ ::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::IntegerValueSpec

Returns The value spec for an 'INTEGER' parameter.

Returns:

• (::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::IntegerValueSpec) —

  The value spec for an 'INTEGER' parameter.

# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 329

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

  # Value specification for a parameter in `DOUBLE` type.
  # @!attribute [rw] min_value
  #   @return [::Float]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Float]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DOUBLE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DoubleValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `INTEGER` type.
  # @!attribute [rw] min_value
  #   @return [::Integer]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Integer]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Integer]
  #     A default value for an `INTEGER` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class IntegerValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `CATEGORICAL` type.
  # @!attribute [rw] values
  #   @return [::Array<::String>]
  #     Required. The list of possible categories.
  # @!attribute [rw] default_value
  #   @return [::String]
  #     A default value for a `CATEGORICAL` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class CategoricalValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `DISCRETE` type.
  # @!attribute [rw] values
  #   @return [::Array<::Float>]
  #     Required. A list of possible values.
  #     The list should be in increasing order and at least 1e-10 apart.
  #     For instance, this parameter might have possible settings of 1.5, 2.5,
  #     and 4.0. This list should not contain more than 1,000 values.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DISCRETE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.  It automatically rounds to the
  #     nearest feasible discrete point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DiscreteValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Represents a parameter spec with condition from its parent parameter.
  # @!attribute [rw] parent_discrete_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::DiscreteValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `DISCRETE` type.
  # @!attribute [rw] parent_int_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::IntValueCondition]
  #     The spec for matching values from a parent parameter of `INTEGER`
  #     type.
  # @!attribute [rw] parent_categorical_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::CategoricalValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `CATEGORICAL` type.
  # @!attribute [rw] parameter_spec
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec]
  #     Required. The spec for a conditional parameter.
  class ConditionalParameterSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Represents the spec to match discrete values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Float>]
    #     Required. Matches values of the parent parameter of 'DISCRETE' type.
    #     All values must exist in `discrete_value_spec` of parent parameter.
    #
    #     The Epsilon of the value matching is 1e-10.
    class DiscreteValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match integer values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Integer>]
    #     Required. Matches values of the parent parameter of 'INTEGER' type.
    #     All values must lie in `integer_value_spec` of parent parameter.
    class IntValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match categorical values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::String>]
    #     Required. Matches values of the parent parameter of 'CATEGORICAL'
    #     type. All values must exist in `categorical_value_spec` of parent
    #     parameter.
    class CategoricalValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end
  end

  # The type of scaling that should be applied to this parameter.
  module ScaleType
    # By default, no scaling is applied.
    SCALE_TYPE_UNSPECIFIED = 0

    # Scales the feasible space to (0, 1) linearly.
    UNIT_LINEAR_SCALE = 1

    # Scales the feasible space logarithmically to (0, 1). The entire
    # feasible space must be strictly positive.
    UNIT_LOG_SCALE = 2

    # Scales the feasible space "reverse" logarithmically to (0, 1). The
    # result is that values close to the top of the feasible space are spread
    # out more than points near the bottom. The entire feasible space must be
    # strictly positive.
    UNIT_REVERSE_LOG_SCALE = 3
  end
end

#parameter_id ⇒ ::String

Returns Required. The ID of the parameter. Must not contain whitespaces and must be unique amongst all ParameterSpecs.

Returns:

• (::String) —

  Required. The ID of the parameter. Must not contain whitespaces and must be unique amongst all ParameterSpecs.

# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 329

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

  # Value specification for a parameter in `DOUBLE` type.
  # @!attribute [rw] min_value
  #   @return [::Float]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Float]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DOUBLE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DoubleValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `INTEGER` type.
  # @!attribute [rw] min_value
  #   @return [::Integer]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Integer]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Integer]
  #     A default value for an `INTEGER` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class IntegerValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `CATEGORICAL` type.
  # @!attribute [rw] values
  #   @return [::Array<::String>]
  #     Required. The list of possible categories.
  # @!attribute [rw] default_value
  #   @return [::String]
  #     A default value for a `CATEGORICAL` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class CategoricalValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `DISCRETE` type.
  # @!attribute [rw] values
  #   @return [::Array<::Float>]
  #     Required. A list of possible values.
  #     The list should be in increasing order and at least 1e-10 apart.
  #     For instance, this parameter might have possible settings of 1.5, 2.5,
  #     and 4.0. This list should not contain more than 1,000 values.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DISCRETE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.  It automatically rounds to the
  #     nearest feasible discrete point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DiscreteValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Represents a parameter spec with condition from its parent parameter.
  # @!attribute [rw] parent_discrete_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::DiscreteValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `DISCRETE` type.
  # @!attribute [rw] parent_int_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::IntValueCondition]
  #     The spec for matching values from a parent parameter of `INTEGER`
  #     type.
  # @!attribute [rw] parent_categorical_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::CategoricalValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `CATEGORICAL` type.
  # @!attribute [rw] parameter_spec
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec]
  #     Required. The spec for a conditional parameter.
  class ConditionalParameterSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Represents the spec to match discrete values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Float>]
    #     Required. Matches values of the parent parameter of 'DISCRETE' type.
    #     All values must exist in `discrete_value_spec` of parent parameter.
    #
    #     The Epsilon of the value matching is 1e-10.
    class DiscreteValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match integer values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Integer>]
    #     Required. Matches values of the parent parameter of 'INTEGER' type.
    #     All values must lie in `integer_value_spec` of parent parameter.
    class IntValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match categorical values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::String>]
    #     Required. Matches values of the parent parameter of 'CATEGORICAL'
    #     type. All values must exist in `categorical_value_spec` of parent
    #     parameter.
    class CategoricalValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end
  end

  # The type of scaling that should be applied to this parameter.
  module ScaleType
    # By default, no scaling is applied.
    SCALE_TYPE_UNSPECIFIED = 0

    # Scales the feasible space to (0, 1) linearly.
    UNIT_LINEAR_SCALE = 1

    # Scales the feasible space logarithmically to (0, 1). The entire
    # feasible space must be strictly positive.
    UNIT_LOG_SCALE = 2

    # Scales the feasible space "reverse" logarithmically to (0, 1). The
    # result is that values close to the top of the feasible space are spread
    # out more than points near the bottom. The entire feasible space must be
    # strictly positive.
    UNIT_REVERSE_LOG_SCALE = 3
  end
end

#scale_type ⇒ ::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ScaleType

Returns How the parameter should be scaled. Leave unset for CATEGORICAL parameters.

Returns:

• (::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ScaleType) —

  How the parameter should be scaled. Leave unset for CATEGORICAL parameters.

# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 329

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

  # Value specification for a parameter in `DOUBLE` type.
  # @!attribute [rw] min_value
  #   @return [::Float]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Float]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DOUBLE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DoubleValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `INTEGER` type.
  # @!attribute [rw] min_value
  #   @return [::Integer]
  #     Required. Inclusive minimum value of the parameter.
  # @!attribute [rw] max_value
  #   @return [::Integer]
  #     Required. Inclusive maximum value of the parameter.
  # @!attribute [rw] default_value
  #   @return [::Integer]
  #     A default value for an `INTEGER` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class IntegerValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `CATEGORICAL` type.
  # @!attribute [rw] values
  #   @return [::Array<::String>]
  #     Required. The list of possible categories.
  # @!attribute [rw] default_value
  #   @return [::String]
  #     A default value for a `CATEGORICAL` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class CategoricalValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Value specification for a parameter in `DISCRETE` type.
  # @!attribute [rw] values
  #   @return [::Array<::Float>]
  #     Required. A list of possible values.
  #     The list should be in increasing order and at least 1e-10 apart.
  #     For instance, this parameter might have possible settings of 1.5, 2.5,
  #     and 4.0. This list should not contain more than 1,000 values.
  # @!attribute [rw] default_value
  #   @return [::Float]
  #     A default value for a `DISCRETE` parameter that is assumed to be a
  #     relatively good starting point.  Unset value signals that there is no
  #     offered starting point.  It automatically rounds to the
  #     nearest feasible discrete point.
  #
  #     Currently only supported by the Vertex AI Vizier service. Not supported
  #     by HyperparameterTuningJob or TrainingPipeline.
  class DiscreteValueSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Represents a parameter spec with condition from its parent parameter.
  # @!attribute [rw] parent_discrete_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::DiscreteValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `DISCRETE` type.
  # @!attribute [rw] parent_int_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::IntValueCondition]
  #     The spec for matching values from a parent parameter of `INTEGER`
  #     type.
  # @!attribute [rw] parent_categorical_values
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::ConditionalParameterSpec::CategoricalValueCondition]
  #     The spec for matching values from a parent parameter of
  #     `CATEGORICAL` type.
  # @!attribute [rw] parameter_spec
  #   @return [::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec]
  #     Required. The spec for a conditional parameter.
  class ConditionalParameterSpec
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Represents the spec to match discrete values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Float>]
    #     Required. Matches values of the parent parameter of 'DISCRETE' type.
    #     All values must exist in `discrete_value_spec` of parent parameter.
    #
    #     The Epsilon of the value matching is 1e-10.
    class DiscreteValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match integer values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::Integer>]
    #     Required. Matches values of the parent parameter of 'INTEGER' type.
    #     All values must lie in `integer_value_spec` of parent parameter.
    class IntValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # Represents the spec to match categorical values from parent parameter.
    # @!attribute [rw] values
    #   @return [::Array<::String>]
    #     Required. Matches values of the parent parameter of 'CATEGORICAL'
    #     type. All values must exist in `categorical_value_spec` of parent
    #     parameter.
    class CategoricalValueCondition
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end
  end

  # The type of scaling that should be applied to this parameter.
  module ScaleType
    # By default, no scaling is applied.
    SCALE_TYPE_UNSPECIFIED = 0

    # Scales the feasible space to (0, 1) linearly.
    UNIT_LINEAR_SCALE = 1

    # Scales the feasible space logarithmically to (0, 1). The entire
    # feasible space must be strictly positive.
    UNIT_LOG_SCALE = 2

    # Scales the feasible space "reverse" logarithmically to (0, 1). The
    # result is that values close to the top of the feasible space are spread
    # out more than points near the bottom. The entire feasible space must be
    # strictly positive.
    UNIT_REVERSE_LOG_SCALE = 3
  end
end