Struct GradientDescent 

pub struct GradientDescent {
    pub abs_tol: Tolerances,
    pub dual: bool,
    pub error_norm: Norm,
    pub line_search: LineSearch,
    pub max_steps: usize,
    pub rel_tol: Option<Scalar>,
}

The method of gradient descent.

Fields

abs_tol: Tolerances

Absolute error tolerances.

dual: bool

Lagrangian dual.

error_norm: Norm

Norm type for error evaluation.

line_search: LineSearch

Line search algorithm.

max_steps: usize

Maximum number of steps.

rel_tol: Option<Scalar>

Relative error tolerance.

Trait Implementations

impl Debug for GradientDescent

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for GradientDescent

fn default() -> Self

Returns the “default value” for a type.

impl<F, J, X, E> FirstOrderOptimization<F, J, X> for GradientDescent

where F: Erase<Erased = Scalar> + Tensor, <J as Tensor>::Unit: UnitMul<<X as Tensor>::Unit>, <<J as Tensor>::Unit as UnitMul<<X as Tensor>::Unit>>::Output: UnitSum, <<<J as Tensor>::Unit as UnitMul<<X as Tensor>::Unit>>::Output as UnitSum>::Output: Is<<F as Tensor>::Unit>, J: Erase<Erased = E> + Jacobian + Mul<StepSize<J, X>, Output = X>, for<'a> &'a J: Mul<StepSize<J, X>, Output = X>, X: Erase<Erased = E> + Jacobian + Solution, <X as Tensor>::Unit: UnitDiv<<J as Tensor>::Unit>, E: Tensor, for<'a> &'a Matrix: Mul<&'a X, Output = Vector>,

fn minimize( &self, function: impl FnMut(&X) -> Result<F, String>, jacobian: impl FnMut(&X) -> Result<J, String>, initial_guess: X, equality_constraint: EqualityConstraint, ) -> Result<X, OptimizationError>

impl<F, X, E> ZerothOrderRootFinding<F, X> for GradientDescent

where F: Erase<Erased = E> + Jacobian + Mul<StepSize<F, X>, Output = X>, for<'a> &'a F: Mul<StepSize<F, X>, Output = X>, X: Erase<Erased = E> + Jacobian + Solution, <X as Tensor>::Unit: UnitDiv<<F as Tensor>::Unit>, E: Tensor, for<'a> &'a Matrix: Mul<&'a X, Output = Vector>,

fn root( &self, function: impl FnMut(&X) -> Result<F, String>, initial_guess: X, equality_constraint: EqualityConstraint, ) -> Result<X, OptimizationError>