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Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

- Incorrect links, empty cells, or wrong formats.

- Chinese characters in English context.

- Minor inconsistencies between the UI and descriptions.

- Low writing fluency that does not affect understanding.

- Incorrect version numbers, including software package names and version numbers on the UI.

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- Incorrect schematic or architecture diagrams.

- Incorrect commands or command parameters.

- Incorrect code.

- Commands inconsistent with the functions.

- Wrong screenshots.

- Sample code running error, or running results inconsistent with the expectation.

Risk Warnings

- Risk Warnings:

- Lack of risk warnings for operations that may damage the system or important data.

Content Compliance

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mindspore.numpy.randint

mindspore.numpy.randint(minval, maxval=None, shape=None, dtype=mstype.int32)

Return random integers from minval (inclusive) to maxval (exclusive). Return random integers from the discrete uniform distribution of the specified dtype in the “half-open” interval $[minval,maxval)$. If maxval is None (the default), the value range will be $[0,minval)$, in this case, minval must be greater than 0.

Parameters

• minval (Union[int]) – Start value of interval. The interval includes this value. When maxval is None, minval must be greater than 0. When maxval is not None, minval must be less than maxval.

• maxval (Union[int], optional) – End value of interval. The interval does not include this value.

• shape (Union[int, tuple(int)]) – Shape of the new tensor, e.g., $(2,3)$ or $2$.

• dtype (Union[mindspore.dtype, str], optional) – Designated tensor dtype, it must be int type. Default is mindspore.int32.

Returns

Tensor, with the designated shape and dtype, filled with random integers from minval (inclusive) to maxval (exclusive).

Raises

• TypeError – If input arguments have types not specified above.

• ValueError – If input arguments have values not specified above.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore.numpy as np
>>> from mindspore import set_seed
>>> set_seed(1)
>>> print(np.randint(1, 10, (2,3)))
[[4 9 7]
[9 1 2]]