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 collapse
-
#categorical_value_spec ⇒ ::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::CategoricalValueSpec
The value spec for a 'CATEGORICAL' parameter.
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#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.
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#double_value_spec ⇒ ::Google::Cloud::AIPlatform::V1::StudySpec::ParameterSpec::DoubleValueSpec
The value spec for a 'DOUBLE' parameter.
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#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
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# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 347 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. # # Note: The following fields are mutually exclusive: `parent_discrete_values`, `parent_int_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_int_values`, `parent_discrete_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_categorical_values`, `parent_discrete_values`, `parent_int_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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>
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# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 347 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. # # Note: The following fields are mutually exclusive: `parent_discrete_values`, `parent_int_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_int_values`, `parent_discrete_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_categorical_values`, `parent_discrete_values`, `parent_int_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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
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# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 347 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. # # Note: The following fields are mutually exclusive: `parent_discrete_values`, `parent_int_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_int_values`, `parent_discrete_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_categorical_values`, `parent_discrete_values`, `parent_int_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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
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# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 347 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. # # Note: The following fields are mutually exclusive: `parent_discrete_values`, `parent_int_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_int_values`, `parent_discrete_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_categorical_values`, `parent_discrete_values`, `parent_int_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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
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# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 347 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. # # Note: The following fields are mutually exclusive: `parent_discrete_values`, `parent_int_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_int_values`, `parent_discrete_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_categorical_values`, `parent_discrete_values`, `parent_int_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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
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# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 347 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. # # Note: The following fields are mutually exclusive: `parent_discrete_values`, `parent_int_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_int_values`, `parent_discrete_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_categorical_values`, `parent_discrete_values`, `parent_int_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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
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# File 'proto_docs/google/cloud/aiplatform/v1/study.rb', line 347 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. # # Note: The following fields are mutually exclusive: `parent_discrete_values`, `parent_int_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_int_values`, `parent_discrete_values`, `parent_categorical_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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. # # Note: The following fields are mutually exclusive: `parent_categorical_values`, `parent_discrete_values`, `parent_int_values`. If a field in that set is populated, all other fields in the set will automatically be cleared. # @!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 |