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tensor.or
#tensor.or
fn or(self: @Tensor<T>, other: @Tensor<T>) -> Tensor<usize>;
Computes the logical OR 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<usize> of booleans (0 or 1) with the same shape as the broadcasted inputs.Case 1: Compare tensors with same shape
use array::{ArrayTrait, SpanTrait};
use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor};
fn or_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, 3, 4, 5, 9, 1, 5].span(),
);
return tensor_1.or(@tensor_2);
}
>>> [0,1,1,1,1,1,1,1,1]
Case 2: Compare tensors with different shapes
use array::{ArrayTrait, SpanTrait};
use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor};
fn or_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![1, 3].span(), data: array![0, 1, 2].span(),
);
return tensor_1.or(@tensor_2);
}
>>> [0,1,1,1,1,1,1,1,1]
Last modified 2mo ago