Trait neuronika::Stack

pub trait Stack<Rhs> {
    type Output;
    fn stack(self, other: Rhs, axis: usize) -> Self::Output;
}

Stacking.

Associated Types

type Output

The type of the stacking’s result. See the differentiability arithmetic for more details.

Required methods

fn stack(self, other: Rhs, axis: usize) -> Self::Output

Stacks variables along the given axis.

Implementors

impl<F1, B1, F2> Stack<Var<F2>> for VarDiff<F1, B1> where
    F1: Data<Dim = B1::Dim> + 'static,
    F2: Data<Dim = F1::Dim> + 'static,
    B1: Gradient + Overwrite + 'static,
    F1::Dim: RemoveAxis,
    B1::Dim: RemoveAxis, 

type Output = VarDiff<Stack<F1, F2>, StackBackwardLeft<B1>>

impl<F1, B1, F2, B2> Stack<VarDiff<F2, B2>> for VarDiff<F1, B1> where
    F1: Data + 'static,
    B1: Gradient + Overwrite + 'static,
    F2: Data<Dim = F1::Dim> + 'static,
    B2: Gradient<Dim = B1::Dim> + Overwrite + 'static,
    F1::Dim: RemoveAxis,
    B1::Dim: RemoveAxis, 

type Output = VarDiff<Stack<F1, F2>, StackBackward<B1, B2>>

impl<F1, F2> Stack<Var<F2>> for Var<F1> where
    F1: Data + 'static,
    F2: Data<Dim = F1::Dim> + 'static,
    F1::Dim: RemoveAxis, 

type Output = Var<Stack<F1, F2>>

impl<F1, F2, B2> Stack<VarDiff<F2, B2>> for Var<F1> where
    F1: Data + 'static,
    F2: Data<Dim = F1::Dim> + 'static,
    B2: Gradient<Dim = F1::Dim> + Overwrite + 'static,
    B2::Dim: RemoveAxis,
    F1::Dim: RemoveAxis, 

type Output = VarDiff<Stack<F1, F2>, StackBackwardRight<B2>>