fn cumsum(self: @Tensor<T>, axis: usize, exclusive: Option<bool>, reverse: Option<bool>) -> Tensor<usize>;
Performs cumulative sum of the input elements along the given axis.
Args
self(@Tensor<T>) - The input tensor.
axis(usize) - The axis along which to compute the cumulative sum.
exclusive(Option<bool>) - By default, it will do the sum inclusively meaning the first element is copied as is.
reverse(Option<bool>) - If true, the cumulative sum is performed in the opposite direction. Defaults to false.
Panics
Panics if axis is not in the range of the input tensor's dimensions.
Returns
A new Tensor<T> instance containing the cumulative sum of the input tensor's elements along the given axis.
Examples
Case 1: cumsum with default parameters
use core::array::{ArrayTrait, SpanTrait};
use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor};
fn cumsum_example() -> Tensor<u32> {
let tensor = TensorTrait::<u32>::new(
shape: array![2, 2, 2].span(), data: array![0, 1, 2, 3, 4, 5, 6, 7].span(),
);
return tensor.cumsum(axis: 2, exclusive: Option::None(()), reverse: Option::None(()));
}
>>> [[[0,1],[2,5]],[[4,9],[6,13]]]
Case 2: cumsum with exclusive = true
use core::array::{ArrayTrait, SpanTrait};
use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor};
fn cumsum_example() -> Tensor<u32> {
let tensor = TensorTrait::<u32>::new(
shape: array![2, 2, 2].span(), data: array![0, 1, 2, 3, 4, 5, 6, 7].span(),
);
return tensor.cumsum(axis: 2, exclusive: Option::Some(true), reverse: Option::None(()));
}
>>> [[[0,0],[0,2]],[[0,4],[0,6]]]
Case 3: cumsum with exclusive = true and reverse = true
use core::array::{ArrayTrait, SpanTrait};
use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor};
fn cumsum_example() -> Tensor<u32> {
let tensor = TensorTrait::<u32>::new(
shape: array![2, 2, 2].span(), data: array![0, 1, 2, 3, 4, 5, 6, 7].span(),
);
return tensor.cumsum(axis: 2, exclusive: Option::Some(true), reverse: Option::Some(true));
}
>>> [[[1,0],[3,0]],[[5,0],[7,0]]]
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