Hey all, newbie here with a newbie question

I’m wondering what’s the easier way to get the first n rows from a multi-dimensional tensor.

For instance, If I have a 3 dimension tensor like this:

t = Nx.tensor([
  [0, 1, 2],
  [3, 4, 5],
  [6, 7, 8]
])

#Nx.Tensor<
  s64[3][3]
  [
    [0, 1, 2],
    [3, 4, 5],
    [6, 7, 8]
  ]
>

How can I get the first 2 rows? I mean [[0, 3, 6], [1, 4, 7]].

A simple solution is to transpose the tensor and then get the first 2 elements, like:

Nx.transpose(t)[0..1]

#Nx.Tensor<
  s64[2][3]
  [
    [0, 3, 6],
    [1, 4, 7]
  ]
>

But I was wondering if there is a more straightforward way to do that?
I’m asking because I have seen that with python (numpy) you can do that with array[0:2].
This is just a curiosity, is not based on any particular needs.

❯ python3
>>> import numpy as np
>>> x1 = [1, 2, 3]
>>> x2 = [4, 5, 6]
>>> x3 = [7, 8, 9]
>>> X = np.column_stack([x1, x2, x3])
>>> X
array([[1, 4, 7],
       [2, 5, 8],
       [3, 6, 9]])
>>> X[0:2]
array([[1, 4, 7],
       [2, 5, 8]])

Thank you all in advance
Cheers