dpnp.full_like¶

dpnp.full_like(a, /, fill_value, *, dtype=None, order='K', subok=False, shape=None, device=None, usm_type=None, sycl_queue=None)[source]¶

Return a full array with the same shape and type as a given array.

For full documentation refer to numpy.full_like.

Parameters:

a{dpnp.ndarray, usm_ndarray}

The shape and dtype of a define these same attributes of the returned array.

fill_value{scalar, array_like}

Fill value, in any form that can be converted to an array. This includes scalars, lists, lists of tuples, tuples, tuples of tuples, tuples of lists, and ndarrays.

dtype{None, str, dtype object}, optional

The desired dtype for the array, e.g., dpnp.int32. If None, uses a default floating point data type for the device on which the input array is allocated.

Default: None.

order{None, "C", "F", "A", "K"}, optional

Memory layout of the newly output array. order=None is an alias for order="K".

Default: "K".

shape{None, int, sequence of ints}

Overrides the shape of the result.

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.

usm_type{None, "device", "shared", "host"}, optional

The type of SYCL USM allocation for the output array.

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.

Returns:

outdpnp.ndarray: Array of fill_value with the same shape and type as a.

Limitations

Parameter subok is supported only with default value False. Otherwise, the function raises NotImplementedError exception.

See also

dpnp.empty_like: Return an empty array with shape and type of input.
dpnp.ones_like: Return an array of ones with shape and type of input.
dpnp.zeros_like: Return an array of zeros with shape and type of input.
dpnp.full: Return a new array of given shape filled with value.

Examples

>>> import dpnp as np
>>> a = np.arange(6)
>>> np.full_like(a, 1)
array([1, 1, 1, 1, 1, 1])

Creating an array on a different device or with a specified usm_type

>>> x = np.full_like(a, 1) # default case
>>> x, x.device, x.usm_type
(array([1, 1, 1, 1, 1, 1]), Device(level_zero:gpu:0), 'device')

>>> y = np.full_like(a, 1, device="cpu")
>>> y, y.device, y.usm_type
(array([1, 1, 1, 1, 1, 1]), Device(opencl:cpu:0), 'device')

>>> z = np.full_like(a, 1, usm_type="host")
>>> z, z.device, z.usm_type
(array([1, 1, 1, 1, 1, 1]), Device(level_zero:gpu:0), 'host')