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fix doc for the op sort() and argsort() #15317

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fix doc for the op sort() and argsort() #15317

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4 changes: 2 additions & 2 deletions src/operator/tensor/ordering_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -114,7 +114,7 @@ Examples::
[ 1., 3.]]

// flattens and then sorts
sort(x) = [ 1., 1., 3., 4.]
sort(x, axis=None) = [ 1., 1., 3., 4.]
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This sort makes sense.
But I'm thrown off by the other example. Sorting along the last axis would be 3 then 4 unless it is descending rather than ascending. Does this need to be specified for clarity?

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Hi,
Thanks for your reply!

Do you mean this example?
// sorts along the last axis
sort(x) = [[ 1., 4.], [ 1., 3.]]

Since x = [[ 1, 4],[ 3, 1]], the pairs in the last axis are [1,4] and [3,1]. Sorting only along the last axis in a descend way would be [1,4] and [1,3]. So, in my opinion, it is correct? or maybe I'm wrong?

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I tested it in numpy and it matches fine.

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Sorry that I didn't get your point. What I did wrong in this PR?

If the argument axis=None is not given, this function will sort the array alone the last axis. However, in the second example, we want the array to be flattened and then sorted.

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Everything is fine. I might have needed more examples to see the patterns, but I understand that if you're conversant with NumPy then this all works as expected.


// sorts along the first axis
sort(x, axis=0) = [[ 1., 1.],
Expand Down Expand Up @@ -173,7 +173,7 @@ Examples::
[ 0., 1., 0.]]

// flatten and then sort
argsort(x) = [ 3., 1., 5., 0., 4., 2.]
argsort(x, axis=None) = [ 3., 1., 5., 0., 4., 2.]
)code" ADD_FILELINE)
.set_num_inputs(1)
.set_num_outputs(1)
Expand Down