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)
, thenm * 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]])