mindspore.ops.Sort

class mindspore.ops.Sort(axis=- 1, descending=False)[source]

Sorts the elements of the input tensor along the given dimension in the specified order.

Warning

Currently, the data types of Float16 is well supported. Using Float32 might cause loss of accuracy.

Parameters

  • axis (int) – The dimension to sort along. Default: -1.

  • descending (bool) – Controls the sort order. If descending is True then the elements are sorted in descending order by value. Default: False.

Inputs:

  • x (Tensor) - The input tensor of any dimension, with a type of float16 or float32.

Outputs:

  • y1 (Tensor) - A tensor whose values are the sorted values, with the same shape and data type as input.

  • y2 (Tensor) - The indices of the elements in the original input tensor. Data type is int32.

Raises

  • TypeError – If axis is not an int.

  • TypeError – If descending is not a bool.

  • TypeError – If dtype of x is neither float16 nor float32.

  • ValueError – If axis is not in range of [-len(x.shape), len(x.shape)).

Supported Platforms:

Ascend GPU CPU

Examples

>>> x = Tensor(np.array([[8, 2, 1], [5, 9, 3], [4, 6, 7]]), mindspore.float16)
>>> sort = ops.Sort()
>>> output = sort(x)
>>> # The output below is based on the Ascend platform.
>>> print(output)
(Tensor(shape=[3, 3], dtype=Float16, value=
[[ 1.0000e+00,  2.0000e+00,  8.0000e+00],
 [ 3.0000e+00,  5.0000e+00,  9.0000e+00],
 [ 4.0000e+00,  6.0000e+00,  7.0000e+00]]), Tensor(shape=[3, 3], dtype=Int32, value=
[[2, 1, 0],
 [2, 0, 1],
 [0, 1, 2]]))