dpnp.asarray_chkfinite

dpnp.asarray_chkfinite(a, dtype=None, order=None, *, device=None, usm_type=None, sycl_queue=None)[source]

Convert the input to an array, checking for NaNs or Infs.

For full documentation refer to numpy.asarray_chkfinite.

Parameters:

  • arr (array_like) -- Input data, in any form that can be converted to an array. This includes lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. Success requires no NaNs or Infs.

  • dtype ({None, str, dtype object}, optional) -- By default, the data-type is inferred from the input data. Default: None.

  • order ({None, "C", "F", "A", "K"}, optional) -- Memory layout of the newly output array. Default: "K".

  • 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. 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:

out -- Array interpretation of a. No copy is performed if the input is already an ndarray.

Return type:

dpnp.ndarray

Raises:

ValueError -- Raises ValueError if a contains NaN (Not a Number) or Inf (Infinity).

See also

dpnp.asarray

Create an array.

dpnp.asanyarray

Converts an input object into array.

dpnp.ascontiguousarray

Convert input to a c-contiguous array.

dpnp.asfortranarray

Convert input to an array with column-major memory order.

dpnp.fromiter

Create an array from an iterator.

dpnp.fromfunction

Construct an array by executing a function on grid positions.

Examples

>>> import dpnp as np

Convert a list into an array. If all elements are finite, asarray_chkfinite is identical to asarray.

>>> a = [1, 2]
>>> np.asarray_chkfinite(a, dtype=np.float32)
array([1., 2.])

Raises ValueError if array_like contains NaNs or Infs.

>>> a = [1, 2, np.inf]
>>> try:
...     np.asarray_chkfinite(a)
... except ValueError:
...     print('ValueError')
ValueError

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

>>> x = np.asarray_chkfinite([1, 2, 3]) # default case
>>> x, x.device, x.usm_type
(array([1, 2, 3]), Device(level_zero:gpu:0), 'device')

>>> y = np.asarray_chkfinite([1, 2, 3], device="cpu")
>>> y, y.device, y.usm_type
(array([1, 2, 3]), Device(opencl:cpu:0), 'device')

>>> z = np.asarray_chkfinite([1, 2, 3], usm_type="host")
>>> z, z.device, z.usm_type
(array([1, 2, 3]), Device(level_zero:gpu:0), 'host')