mindspore.mint.randint_like

mindspore.mint.randint_like(input, low=0, high, *, dtype=None) → Tensor[source]

Returns a new tensor filled with integer numbers from the uniform distribution over an interval $[l o w, h i g h)$ based on the given dtype and shape of the input tensor.

Warning

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

Parameters

input (Tensor) – Input Tensor to specify the output shape and its default dtype.
low (int, optional) – the lower bound of the generated random number. Default: 0.
high (int) – the upper bound of the generated random number

Keyword Arguments

dtype (mindspore.dtype, optional) – Designated tensor dtype. If None, the same dtype of input will be applied. Default: None .

Returns

Tensor, with the designated shape and dtype, filled with random numbers from the uniform distribution on the interval $[l o w, h i g h)$ .

Raises

TypeError – If low or high is not integer.

Supported Platforms:: Ascend

Examples

>>> import mindspore as ms
>>> from mindspore import Tensor, mint
>>> a = Tensor([[2, 3, 4], [1, 2, 3]])
>>> low = 0
>>> high = 5
>>> print(mint.randint_like(a, low, high, dtype=ms.int32).shape)
(2, 3)