mindspore.mint.randint

mindspore.mint.randint(low=0, high, size, *, generator=None, dtype=None, device=None) → Tensor

Returns a new tensor filled with integer numbers from the uniform distribution over an interval \([low, high)\) based on the given shape and dtype.

Parameters:

• low (int, optional) – The lower bound of the generated random number. Default: 0.

• high (int) – The upper bound of the generated random number.

• size (Union[tuple(int), list(int)]) – Shape of the new tensor, e.g., \((2, 3)\).

Keyword Arguments:

• generator (mindspore.Generator, optional) – A pseudorandom number generator. Default: None, uses the default pseudorandom number generator.

• dtype (mindspore.dtype, optional) – Designated tensor dtype. If None, mindspore.int64 will be applied. Default: None .

• device (str, optional) – The specified device of the output tensor. Only "Ascend", "npu" and "meta" are supported. If device = None, the value set by mindspore.set_device() will be used. Default: None .

Returns:

Tensor, with the designated shape and dtype, filled with random numbers from the uniform distribution on the interval \([low, high)\).

Raises:

• TypeError – If size is not a tuple.

• TypeError – If low or high is not an integer.

• RuntimeError – If device is "CPU" .

• ValueError – If device is "GPU" .

Supported Platforms:

Ascend

Examples

>>> from mindspore import mint
>>> print(mint.randint(0, 5, (2, 3)).shape)
(2, 3)