Struct googapis::google::cloud::ml::v1::ParameterSpec[][src]

pub struct ParameterSpec {
    pub parameter_name: String,
    pub type: i32,
    pub min_value: f64,
    pub max_value: f64,
    pub categorical_values: Vec<String>,
    pub discrete_values: Vec<f64>,
    pub scale_type: i32,
}
Expand description

Represents a single hyperparameter to optimize.

Fields

parameter_name: String

Required. The parameter name must be unique amongst all ParameterConfigs in a HyperparameterSpec message. E.g., “learning_rate”.

type: i32

Required. The type of the parameter.

min_value: f64

Required if type is DOUBLE or INTEGER. This field should be unset if type is CATEGORICAL. This value should be integers if type is INTEGER.

max_value: f64

Required if typeis DOUBLE or INTEGER. This field should be unset if type is CATEGORICAL. This value should be integers if type is INTEGER.

categorical_values: Vec<String>

Required if type is CATEGORICAL. The list of possible categories.

discrete_values: Vec<f64>

Required if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. 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.

scale_type: i32

Optional. How the parameter should be scaled to the hypercube. Leave unset for categorical parameters. Some kind of scaling is strongly recommended for real or integral parameters (e.g., UNIT_LINEAR_SCALE).

Implementations

Returns the enum value of type, or the default if the field is set to an invalid enum value.

Sets type to the provided enum value.

Returns the enum value of scale_type, or the default if the field is set to an invalid enum value.

Sets scale_type to the provided enum value.

Trait Implementations

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