Function autograd::eval

pub fn eval<'a, 'b: 'a, 'c: 'a, V, U, T: Float + 'c + 'b>(
    tensors: &[V], 
    feeds: U
) -> Vec<Option<NdArray<T>>> where
    V: AsRef<Tensor<T>>,
    U: IntoIterator<Item = &'a (&'b Tensor<T>, &'c Array<T, IxDyn>)>, 

Evaluates given symbolic tensors.

Each return value can be None; for example, evaluation of gradient_descent_ops::* would result in None.

NOTE: All the runtime errors are not reported by return values, but by "panic" for convenience.

extern crate ndarray;
extern crate autograd as ag;

let ref a = ag::zeros(&[2]);
let ref b = ag::ones(&[2]);

// eval two tensors at once.
let evaluated = ag::eval(&[a, b], &[]);
assert_eq!(evaluated[0], Some(ndarray::arr1(&[0., 0.]).into_dyn()));
assert_eq!(evaluated[1], Some(ndarray::arr1(&[1., 1.]).into_dyn()));