Struct LinearProgrammingLayer 

pub struct LinearProgrammingLayer {
    pub n_vars: usize,
    pub n_constraints: usize,
}

Linear programming layer: min c^T x s.t. Ax = b, x ≥ 0

Fields

n_vars: usize

n_constraints: usize

Implementations

impl LinearProgrammingLayer

pub fn new(n_vars: usize, n_constraints: usize) -> Self

pub fn solve_simplex( &self, c: &Tensor, A: &Tensor, b: &Tensor, config: &OptimizationConfig, ) -> Result<OptimizationSolution>

Trait Implementations

impl DifferentiableOptimization for LinearProgrammingLayer

fn solve( &self, parameters: &[&Tensor], config: &OptimizationConfig, ) -> Result<OptimizationSolution>

Solve the optimization problem

fn differentiate( &self, solution: &OptimizationSolution, parameters: &[&Tensor], downstream_grad: &Tensor, _config: &OptimizationConfig, ) -> Result<Vec<Tensor>>

Compute derivatives of the solution w.r.t. parameters

fn problem_type(&self) -> OptimizationProblem

Get the type of optimization problem