tensor.reduce_l2

tensor.reduce_l2

   fn reduce_l2(self: @Tensor<T>, axis: usize, keepdims: bool) -> Tensor<T>;

Computes the L2 norm of the input tensor's elements along the provided axes.

Args

• self(@Tensor<T>) - The input tensor.

• axis(usize) - The dimension to reduce.

• keepdims(bool) - If true, retains reduced dimensions with length 1.

Panics

• Panics if axis is not in the range of the input tensor's dimensions.

Returns

A new Tensor<T> instance with the specified axis reduced by summing its elements.

Examples

use core::array::{ArrayTrait, SpanTrait};
use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor};

fn reduce_l2_example() -> Tensor<u32> {

    let mut shape = ArrayTrait::<usize>::new();
    shape.append(2);
    shape.append(2);
    let mut data = ArrayTrait::new();
    data.append(FixedTrait::new_unscaled(1, false));
    data.append(FixedTrait::new_unscaled(2, false));
    data.append(FixedTrait::new_unscaled(3, false));
    data.append(FixedTrait::new_unscaled(5, false));
    let tensor = TensorTrait::<FP8x23>::new(shape.span(), data.span());

    We can call `reduce_l2` function as follows.
    return tensor.reduce_l2(axis: 1, keepdims: true);
}
>>> [[0x11e3779, 0x2ea5ca1]]