mygrad.random.randint

mygrad.random.randint(low, high=None, shape: ~mygrad.typing._shape.Shape | None = None, dtype=<class 'int'>) → Tensor

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 or array-like of ints

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

high: int or array-like of ints, optional

If provided, one above the largest (signed) integer to be drawn from the distribution (see above for behavior if high=None). If array-like, must contain integer values

shape: 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. Byteorder must be native. The default value is int.

Returns:

int or mygrad.Tensor of ints

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

Examples

>>> from mygrad.random import randint
>>> randint(low=1, high=7, shape=(2,5))
Tensor([[2, 4, 1, 5, 1],
        [6, 2, 5, 4, 6]])

>>> randint(low=4, high=100)
Tensor(57)