dpnp.ones_like
- dpnp.ones_like(a, /, *, dtype=None, order='K', subok=False, shape=None, device=None, usm_type=None, sycl_queue=None)[source]
Return an array of ones with the same shape and type as a given array.
For full documentation refer to
numpy.ones_like
.- Parameters:
a ({dpnp.ndarray, usm_ndarray}) -- The shape and dtype of a define these same attributes of the returned array.
dtype ({None, dtype}, optional) -- The desired dtype for the array, e.g., dpnp.int32. Default is the default floating point data type for the device where input array is allocated.
order ({None, "C", "F", "A", "K"}, optional) -- Memory layout of the newly output array.
order=None
is an alias fororder="K"
. Default:"K"
.shape ({None, int, sequence of ints}) -- Overrides the shape of the result.
device ({None, string, SyclDevice, SyclQueue}, optional) -- An array API concept of device where the output array is created. The device can be
None
(the default), an OneAPI filter selector string, an instance ofdpctl.SyclDevice
corresponding to a non-partitioned SYCL device, an instance ofdpctl.SyclQueue
, or a Device object returned bydpnp.dpnp_array.dpnp_array.device
property.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:
out -- Array of ones with the same shape and type as a.
- Return type:
dpnp.ndarray
Limitations
Parameter subok is supported only with default value
False
. Otherwise, the function raisesNotImplementedError
exception.See also
dpnp.empty_like
Return an empty array with shape and type of input.
dpnp.zeros_like
Return an array of zeros with shape and type of input.
dpnp.full_like
Return a new array with shape of input filled with value.
dpnp.ones
Return a new array setting values to one.
Examples
>>> import dpnp as np >>> x0 = np.arange(6) >>> x0 array([0, 1, 2, 3, 4, 5]) >>> np.ones_like(x0) array([1, 1, 1, 1, 1, 1])
Creating an array on a different device or with a specified usm_type
>>> x = np.ones_like(x0) # default case >>> x, x.device, x.usm_type (array([1, 1, 1, 1, 1, 1]), Device(level_zero:gpu:0), 'device')
>>> y = np.ones_like(x0, device="cpu") >>> y, y.device, y.usm_type (array([1, 1, 1, 1, 1, 1]), Device(opencl:cpu:0), 'device')
>>> z = np.ones_like(x0, usm_type="host") >>> z, z.device, z.usm_type (array([1, 1, 1, 1, 1, 1]), Device(level_zero:gpu:0), 'host')