Re:Swift for TensorFlow Shuts Down
by ZephyrBlu on Saturday February 13, 2021 @07:34AM
(#26123255)
I'm not 100% sure what I'm looking at, but that seems to be related to reversing arrays/matrices, not accessing arrays through indexes.
[ Parent
| on HN ]
Re:Swift for TensorFlow Shuts Down
by improbable22 on Saturday February 13, 2021 @07:59AM
(#26123353)
Maybe less readable than I remembered, sorry! But these `CartesianIndex` things are how you index multi-dimensional arrays.
If by indexing you only mean adding offsets to pointers with your bare hands, this is possible but discouraged. Because you'll produce a buggier and less general version of exactly what already exists. In this case, reversing an N-dimensional array, along any M of its axes, with arbitrary offsets -- there are a lot of ways to get that wrong.
What I mean is something like this:
# one dimensional
a = [1, 2, 3]
# prints the number 1 @ index 0
print(a[0])
# multi-dimensional
b = [[1, 2, 3], [4, 5, 6]]
# prints the number 4 @ index (1, 0)
print(b[1][0])
In Julia these indexes would start from 1. It doesn't seem like `CartesianIndex` solves this, since looking at some examples you still have to specify array indexes (Which start from 1): https://docs.julialang.org/en/v1/base/arrays/#Base.Iterators...
Re:Swift for TensorFlow Shuts Down
by improbable22 on Saturday February 13, 2021 @08:59AM
(#26123617)
OK, I thought you were advocating zero based on complicated index calculations for some algorithm, with mod & div, which is what I was trying to say could be abstracted away. The literal syntax `a=[1,2,3]` makes a one-dimensional `Array{Int,1}` whose first element is indeed `a[1]`. (`b` is an array of arrays, while `c = [1 2 3; 4 5 6]` is an honest 2-dimensional array.)