mxnet.np.random.randint

randint(low, high=None, size=None, dtype=None, device=None, out=None)

Return random integers from low (inclusive) to high (exclusive).

Return random integers from the “discrete uniform” distribution of the specified dtype in the “half-open” interval [low, high). If high is None (the default), then results are from [0, low).

Parameters

  • low (int) – Lowest (signed) integer to be drawn from the distribution (unless high=None, in which case this parameter is one above the highest such integer).

  • high (int, optional) – If provided, one above the largest (signed) integer to be drawn from the distribution (see above for behavior if high=None).

  • size (int or tuple of ints, optional) – Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned.

  • dtype (dtype, optional) – Desired dtype of the result. All dtypes are determined by their name, i.e., ‘int64’, ‘int’, etc, so byteorder is not available and a specific precision may have different C types depending on the platform. The default value is ‘np.int’.

  • device (Device, optional) – Device context of output. Default is current device.

  • out (ndarray, optional) – The output ndarray (default is None).

Returns

out – size-shaped array of random integers from the appropriate distribution, or a single such random int if size not provided.

Return type

ndarray of ints

Examples

>>> np.random.randint(2, size=10)
array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0])
>>> np.random.randint(1, size=10)
array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])

Generate a 2 x 4 array of ints between 0 and 4, inclusive:

>>> np.random.randint(5, size=(2, 4))
array([[4, 0, 2, 1],
    [3, 2, 2, 0]])