torch.sort
-
torch.sort(input, dim=-1, descending=False, *, stable=False, out=None) -
Sorts the elements of the
inputtensor along a given dimension in ascending order by value.If
dimis not given, the last dimension of theinputis chosen.If
descendingisTruethen the elements are sorted in descending order by value.If
stableisTruethen the sorting routine becomes stable, preserving the order of equivalent elements.A namedtuple of (values, indices) is returned, where the
valuesare the sorted values andindicesare the indices of the elements in the originalinputtensor.- Parameters
- Keyword Arguments
Example:
>>> x = torch.randn(3, 4) >>> sorted, indices = torch.sort(x) >>> sorted tensor([[-0.2162, 0.0608, 0.6719, 2.3332], [-0.5793, 0.0061, 0.6058, 0.9497], [-0.5071, 0.3343, 0.9553, 1.0960]]) >>> indices tensor([[ 1, 0, 2, 3], [ 3, 1, 0, 2], [ 0, 3, 1, 2]]) >>> sorted, indices = torch.sort(x, 0) >>> sorted tensor([[-0.5071, -0.2162, 0.6719, -0.5793], [ 0.0608, 0.0061, 0.9497, 0.3343], [ 0.6058, 0.9553, 1.0960, 2.3332]]) >>> indices tensor([[ 2, 0, 0, 1], [ 0, 1, 1, 2], [ 1, 2, 2, 0]]) >>> x = torch.tensor([0, 1] * 9) >>> x.sort() torch.return_types.sort( values=tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1]), indices=tensor([ 2, 16, 4, 6, 14, 8, 0, 10, 12, 9, 17, 15, 13, 11, 7, 5, 3, 1])) >>> x.sort(stable=True) torch.return_types.sort( values=tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1]), indices=tensor([ 0, 2, 4, 6, 8, 10, 12, 14, 16, 1, 3, 5, 7, 9, 11, 13, 15, 17]))