fn split_to_sequence(
       self: @Tensor<T>, axis: usize, keepdims: usize, split: Option<Tensor<usize>>
   ) -> Array<Tensor<T>>;

Split a tensor into a sequence of tensors, along the specified β€˜axis’


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

  • axis(usize) - The axis along which to split on.

  • keepdims (usize) - Keep the split dimension or not. If input β€˜split’ is specified, this attribute is ignored.

  • split (Option<Tensor<usize>>) - Length of each output. It can be either a scalar(tensor of empty shape), or a 1-D tensor. All values must be >= 0.


  • Panics if the 'axis' accepted range is not [-rank, rank-1] where r = rank(input).

  • Panics if the 'split' is not either a scalar (tensor of empty shape), or a 1-D tensor.


One or more outputs forming a sequence of tensors after splitting.


use core::array::{ArrayTrait, SpanTrait};
use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor};
use core::option::OptionTrait;
fn split_to_sequence_example() -> Array<Tensor<u32>> {
    let tensor: Tensor<u32> = TensorTrait::<u32>::new(
        shape: array![2,4].span(), 
        data: array![
            0, 1, 2, 3, 4, 5, 6, 7
    let num_outputs = Option::Some(2);
    // let split = Option::Some(TensorTrait::new(array![1].span(), array![2].span()));
    let split: Option<Tensor<usize>> = Option::Some(TensorTrait::new(array![2].span(), array![2, 2].span()));
    // We can call `split_to_sequence` function as follows.
    return tensor.split_to_sequence(1, 1, split);
>>> [

Last updated