torch.sort — PyTorch 2.7 documentation (original) (raw)

torch.sort(input, dim=-1, descending=False, stable=False, *, out=None)¶

Sorts the elements of the input tensor along a given dimension in ascending order by value.

If dim is not given, the last dimension of the input is chosen.

If descending is True then the elements are sorted in descending order by value.

If stable is True then the sorting routine becomes stable, preserving the order of equivalent elements.

A namedtuple of (values, indices) is returned, where the values are the sorted values and indices are the indices of the elements in the originalinput tensor.

Parameters

• input (Tensor) – the input tensor.
• dim (int, optional) – the dimension to sort along
• descending (bool, optional) – controls the sorting order (ascending or descending)
• stable (bool, optional) – makes the sorting routine stable, which guarantees that the order of equivalent elements is preserved.

Keyword Arguments

out (tuple, optional) – the output tuple of (Tensor, LongTensor) that can be optionally given to be used as output buffers

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]))