dpnp.random.RandomState

class dpnp.random.RandomState(seed=None, device=None, sycl_queue=None)

A container of a pseudo-random number generator on a SYCL device, with the legacy API of NumPy.

For full documentation refer to numpy.random.RandomState.

Parameters:

seed{None, int, array_like[ints], BitGenerator}, optional

A random seed to initialize the pseudo-random number generator, as for numpy.random.RandomState: an integer in [0, 2**32 - 1] or a 1-D array of such integers. With None, fresh entropy is pulled from the operating system. A dpnp.random.BitGenerator is used as the bit generator, on its own queue.

Default: None.

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 dpnp.tensor.Device object returned by dpnp.ndarray.device.

Default: None.

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.

Limitations

Unless seed is a dpnp.random.BitGenerator, the bit generator is dpnp.random.Philox4x3210 rather than MT19937, so the values drawn differ from NumPy's, and the state is that of dpnp.random.Philox4x3210. device and sycl_queue cannot be given with a dpnp.random.BitGenerator. The values for a seed are the same on every device, and those of dpnp.random.default_rng(seed) for the distributions whose checks agree.

Every method returns a dpnp.ndarray, zero-dimensional when size is None and the parameters are scalars, rather than a Python scalar. The floating-point methods take a dtype, which defaults to the default floating-point type of the device, and every method a usm_type, the type of USM allocation of the output. Parameters that are on the device are checked as NumPy checks all parameters, so a call with such parameters waits for the device, unlike the methods of dpnp.random.Generator.