Function solve_rrule 

pub fn solve_rrule<T, C>(
    ctx: &mut C,
    a: &Tensor<T>,
    b: &Tensor<T>,
    cotangent: &Tensor<T>,
) -> AdResult<SolveGrad<T>>
where
    T: KernelLinalgScalar + Conjugate,
    C: TensorLinalgContextFor<T> + TensorResolveConjContextFor<T>,
    C::Backend: 'static,

Reverse-mode AD rule for linear solve (VJP / pullback).

Given Ax = b and cotangent x̄, computes (Ā, b̄).

Examples

use tenferro_linalg::solve_rrule;
use tenferro_prims::CpuContext;
use tenferro_tensor::{Tensor, MemoryOrder};
use tenferro_device::LogicalMemorySpace;

let col = MemoryOrder::ColumnMajor;
let mem = LogicalMemorySpace::MainMemory;
let mut ctx = CpuContext::new(1);
let a = Tensor::<f64>::eye(3, mem, col).unwrap();
let b = Tensor::<f64>::ones(&[3], mem, col).unwrap();
let cotangent = Tensor::<f64>::ones(&[3], mem, col).unwrap();
let grad = solve_rrule(&mut ctx, &a, &b, &cotangent).unwrap();