mindspore.ops.randperm

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mindspore.ops.randperm(n, seed=0, offset=0, dtype=mstype.int64)[source]

Generates random permutation of integers from 0 to n-1.

Returns the tensor with the determined shape inferred by n, the random numbers in it drawn from the data range that a given type can represent.

Warning

  • This is an experimental API that is subject to change or deletion.

  • The Ascend backend does not support the reproducibility of random numbers, so the seed parameter has no effect.

Parameters

  • n (Union[Tensor, int]) – The input n Tensor with shape: () or (1,) and with data type of int64. The value of n must be greater than zero.

  • seed (int, optional) – Random seed. Default: 0 . When seed is -1(only negative value), offset is 0, it's determined by time.

  • offset (int, optional) – Offset to generate random numbers. Priority is higher than random seed. Default: 0 . It must be non-negative.

  • dtype (mindspore.dtype, optional) – The type of output. Its value must be one of the following types: int32, int16, int8, uint8, int64, float64, float32, float16. Default: mstype.int64.

Returns

Tensor. Its shape is specified by the required args n. Its type is specified by dtype. Otherwise is default.

Raises

  • TypeError – If dtype is not allowed.

  • ValueError – If n is a negative or 0 element.

  • ValueError – If seed is a negative element.

  • ValueError – If n is larger than the maximal data of the set dtype.

Supported Platforms:

CPU

Examples

>>> from mindspore import ops
>>> from mindspore import dtype as mstype
>>> n = 4
>>> seed = 0
>>> offset = 0
>>> output = ops.randperm(n, seed, offset, dtype=mstype.int64)
>>> print(output)
[0 2 1 3]