dpnp.empty

dpnp.empty(shape, *, dtype=None, order='C', like=None, device=None, usm_type='device', sycl_queue=None)[source]

Return a new array of given shape and type, without initializing entries.

For full documentation refer to numpy.empty.

Parameters:

  • shape ({int, sequence of ints}) -- Shape of the new array, e.g., (2, 3) or 2.

  • 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"}, optional) -- Memory layout of the newly output array. Default: "C".

  • 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 of dpctl.SyclDevice corresponding to a non-partitioned SYCL device, an instance of dpctl.SyclQueue, or a Device object returned by dpnp.dpnp_array.dpnp_array.device property.

  • usm_type ({None, "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 -- Array of uninitialized data of the given shape, dtype, and order.

Return type:

dpnp.ndarray

Limitations

Parameter like is supported only with default value None. Otherwise, the function raises NotImplementedError exception.

See also

dpnp.empty_like

Return an empty array with shape and type of input.

dpnp.ones

Return a new array setting values to one.

dpnp.zeros

Return a new array setting values to zero.

dpnp.full

Return a new array of given shape filled with value.

Examples

>>> import dpnp as np
>>> np.empty(4)
array([9.03088525e-312, 9.03088525e-312, 9.03088525e-312, 9.03088525e-312])

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

>>> x = np.empty((3, 3)) # default case
>>> x.shape, x.device, x.usm_type
((3, 3), Device(level_zero:gpu:0), 'device')

>>> y = np.empty((3, 3), device="cpu")
>>> y.shape, y.device, y.usm_type
((3, 3), Device(opencl:cpu:0), 'device')

>>> z = np.empty((3, 3), usm_type="host")
>>> z.shape, z.device, z.usm_type
((3, 3), Device(level_zero:gpu:0), 'host')