#tensor.bitwise_xor
fn bitwise_xor(self: @Tensor<T>, other: @Tensor<T>) -> Tensor<usize>;
Computes the bitwise XOR of two tensors element-wise. The input tensors must have either:
- Exactly the same shape
- The same number of dimensions and the length of each dimension is either a common length or 1.
self
(@Tensor<T>
) - The first tensor to be comparedother
(@Tensor<T>
) - The second tensor to be compared
- Panics if the shapes are not equal or broadcastable
A new Tensor<T>
with the same shape as the broadcasted inputs.
use core::array::{ArrayTrait, SpanTrait};
use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor};
fn xor_example() -> Tensor<usize> {
let tensor_1 = TensorTrait::<u32>::new(
shape: array![3, 3].span(), data: array![0, 1, 2, 3, 4, 5, 6, 7, 8].span(),
);
let tensor_2 = TensorTrait::<u32>::new(
shape: array![3, 3].span(), data: array![0, 1, 2, 0, 4, 5, 0, 6, 2].span(),
);
return tensor_1.bitwise_xor(@tensor_2);
}
>>> [0,0,0,3,0,0,6,1,10]