Function eigen 

pub fn eigen<T, C>(
    ctx: &mut C,
    tensor: &Tensor<T>,
) -> Result<EigenResult<T, <T as LinalgScalar>::Real>, Error>
where
    T: KernelLinalgScalar,
    C: TensorLinalgContextFor<T>,
    <C as TensorLinalgContextFor<T>>::Backend: 'static,

Compute the eigendecomposition of a batched square matrix.

Input shape: (n, n, *). The lower triangle is treated as canonical input, matching the default UPLO='L' behavior used by PyTorch’s linalg.eigh.

Examples

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

let mut ctx = CpuContext::new(1);
let a = Tensor::<f64>::from_slice(
    &[2.0, 1.0, 1.0, 2.0],
    &[2, 2],
    MemoryOrder::ColumnMajor,
).unwrap();
let result = eigen(&mut ctx, &a).unwrap();
assert_eq!(result.values.dims(), &[2]);