Function einsum_with_subscripts_owned 

pub fn einsum_with_subscripts_owned<Alg, Backend>(
    ctx: &mut BackendContext<Alg, Backend>,
    subscripts: &Subscripts,
    operands: Vec<Tensor<Alg::Scalar>>,
    size_dict: Option<&HashMap<u32, usize>>,
) -> Result<Tensor<Alg::Scalar>>
where
    Alg: Semiring,
    Alg::Scalar: Scalar + Conjugate + HasAlgebra<Algebra = Alg>,
    Backend: EinsumBackend<Alg>,
    BackendContext<Alg, Backend>: TensorTempPoolContext,

Execute einsum with pre-built Subscripts, consuming the input tensors.

This preserves the owned execution path through planning and operand normalization.

Examples

use tenferro_algebra::Standard;
use tenferro_einsum::{einsum_with_subscripts_owned, Subscripts};
use tenferro_prims::{CpuBackend, CpuContext};

let mut ctx = CpuContext::new(1);
let subs = Subscripts::new(&[&[0, 1], &[1, 2]], &[0, 2]);
let out =
    einsum_with_subscripts_owned::<Standard<f64>, CpuBackend>(&mut ctx, &subs, vec![a, b], None)
        .unwrap();