dpnp.random.rand

dpnp.random.rand(*args, device=None, usm_type='device', sycl_queue=None)[source]

Random values in a given shape.

Create an array of the given shape and populate it with random samples from a uniform distribution over [0, 1).

For full documentation refer to numpy.random.rand.

Parameters:

  • *args (sequence of ints, optional) -- The dimensions of the returned array, must be non-negative. If no argument is given a single Python float is returned.

  • device ({None, string, SyclDevice, SyclQueue, Device}, optional) --

    An array API concept of device where the output array is created. device can be None, a oneAPI filter selector string, an instance of dpctl.SyclDevice corresponding to a non-partitioned SYCL device, an instance of dpctl.SyclQueue, or a dpctl.tensor.Device object returned by dpnp.ndarray.device.

    Default: None.

  • usm_type ({"device", "shared", "host"}, optional) -- The type of SYCL USM allocation for the output array. Default: "device".

  • sycl_queue ({None, SyclQueue}, optional) -- A SYCL queue to use for output array allocation and copying. The sycl_queue can be passed as None (the default), which means to get the SYCL queue from device keyword if present or to use a default queue. Default: None.

Returns:

out -- Random values in a given shape (d0, d1, ..., dn). Output array data type is dpnp.float64 if a device supports it, or dpnp.float32 type otherwise.

Return type:

dpnp.ndarray

See also

dpnp.random.random

Return random floats in the half-open interval [0.0, 1.0).

dpnp.random.random_sample

Return random floats in the half-open interval [0.0, 1.0).

dpnp.random.uniform

Draw samples from a uniform distribution.

Examples

>>> import dpnp as np
>>> s = np.random.rand(3, 2)