pub trait Numeric<B>: BasicOps<B>where
    B: Backend,
    Self::Elem: Element,{
Show 29 methods
    // Required methods
    fn add<const D: usize>(
        lhs: Self::Primitive<D>,
        rhs: Self::Primitive<D>
    ) -> Self::Primitive<D>;
    fn add_scalar<const D: usize, E>(
        lhs: Self::Primitive<D>,
        rhs: E
    ) -> Self::Primitive<D>
       where E: ElementConversion;
    fn sub<const D: usize>(
        lhs: Self::Primitive<D>,
        rhs: Self::Primitive<D>
    ) -> Self::Primitive<D>;
    fn sub_scalar<const D: usize, E>(
        lhs: Self::Primitive<D>,
        rhs: E
    ) -> Self::Primitive<D>
       where E: ElementConversion;
    fn div<const D: usize>(
        lhs: Self::Primitive<D>,
        rhs: Self::Primitive<D>
    ) -> Self::Primitive<D>;
    fn div_scalar<const D: usize, E>(
        lhs: Self::Primitive<D>,
        rhs: E
    ) -> Self::Primitive<D>
       where E: ElementConversion;
    fn mul<const D: usize>(
        lhs: Self::Primitive<D>,
        rhs: Self::Primitive<D>
    ) -> Self::Primitive<D>;
    fn mul_scalar<const D: usize, E>(
        lhs: Self::Primitive<D>,
        rhs: E
    ) -> Self::Primitive<D>
       where E: ElementConversion;
    fn neg<const D: usize>(tensor: Self::Primitive<D>) -> Self::Primitive<D>;
    fn zeros<const D: usize>(
        shape: Shape<D>,
        device: &<B as Backend>::Device
    ) -> Self::Primitive<D>;
    fn ones<const D: usize>(
        shape: Shape<D>,
        device: &<B as Backend>::Device
    ) -> Self::Primitive<D>;
    fn sum<const D: usize>(tensor: Self::Primitive<D>) -> Self::Primitive<1>;
    fn sum_dim<const D: usize>(
        tensor: Self::Primitive<D>,
        dim: usize
    ) -> Self::Primitive<D>;
    fn mean<const D: usize>(tensor: Self::Primitive<D>) -> Self::Primitive<1>;
    fn mean_dim<const D: usize>(
        tensor: Self::Primitive<D>,
        dim: usize
    ) -> Self::Primitive<D>;
    fn greater<const D: usize>(
        lhs: Self::Primitive<D>,
        rhs: Self::Primitive<D>
    ) -> Tensor<B, D, Bool>;
    fn greater_elem<const D: usize>(
        lhs: Self::Primitive<D>,
        rhs: Self::Elem
    ) -> Tensor<B, D, Bool>;
    fn greater_equal<const D: usize>(
        lhs: Self::Primitive<D>,
        rhs: Self::Primitive<D>
    ) -> Tensor<B, D, Bool>;
    fn greater_equal_elem<const D: usize>(
        lhs: Self::Primitive<D>,
        rhs: Self::Elem
    ) -> Tensor<B, D, Bool>;
    fn lower<const D: usize>(
        lhs: Self::Primitive<D>,
        rhs: Self::Primitive<D>
    ) -> Tensor<B, D, Bool>;
    fn lower_elem<const D: usize>(
        lhs: Self::Primitive<D>,
        rhs: Self::Elem
    ) -> Tensor<B, D, Bool>;
    fn lower_equal<const D: usize>(
        lhs: Self::Primitive<D>,
        rhs: Self::Primitive<D>
    ) -> Tensor<B, D, Bool>;
    fn lower_equal_elem<const D: usize>(
        lhs: Self::Primitive<D>,
        rhs: Self::Elem
    ) -> Tensor<B, D, Bool>;
    fn mask_scatter<const D: usize>(
        tensor: Self::Primitive<D>,
        mask: Tensor<B, D, Bool>,
        source: Self::Primitive<D>
    ) -> Self::Primitive<D>;
    fn mask_fill<const D: usize>(
        tensor: Self::Primitive<D>,
        mask: Tensor<B, D, Bool>,
        value: Self::Elem
    ) -> Self::Primitive<D>;
    fn index_select<const D: usize>(
        tensor: Self::Primitive<D>,
        indexes: Tensor<B, D, Int>
    ) -> Self::Primitive<D>;
    fn index_select_assign<const D: usize>(
        tensor: Self::Primitive<D>,
        indexes: Tensor<B, D, Int>,
        values: Self::Primitive<D>
    ) -> Self::Primitive<D>;
    fn index_select_dim<const D: usize>(
        tensor: Self::Primitive<D>,
        dim: usize,
        indexes: Tensor<B, 1, Int>
    ) -> Self::Primitive<D>;
    fn index_select_dim_assign<const D1: usize, const D2: usize>(
        tensor: Self::Primitive<D1>,
        dim: usize,
        indexes: Tensor<B, 1, Int>,
        values: Self::Primitive<D2>
    ) -> Self::Primitive<D1>;
}Expand description
Trait that list all operations that can be applied on all numerical tensors.
Warnings
This is an internal trait, use the public API provided by tensor struct.