dpnp.eye

dpnp.eye(N, /, M=None, k=0, dtype=None, order='C', *, like=None, device=None, usm_type='device', sycl_queue=None)[source]

Return a 2-D array with ones on the diagonal and zeros elsewhere.

For full documentation refer to numpy.eye.

Parameters:

  • N (int) – Number of rows in the output.

  • M (int, optional) – Number of columns in the output. If None, defaults to N.

  • k (int, optional) – Index of the diagonal: 0 (the default) refers to the main diagonal, a positive value refers to an upper diagonal, and a negative value to a lower diagonal.

  • dtype (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 ({"C", "F", None}, 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 is “device”.

  • sycl_queue ({None, SyclQueue}, optional) – A SYCL queue to use for output array allocation and copying.

Returns:

out – An array where all elements are equal to zero, except for the k-th diagonal, whose values are equal to one.

Return type:

dpnp.ndarray

Limitations

Parameter order is supported only with values "C", "F" and None. Parameter like is supported only with default value None. Otherwise, the function raises NotImplementedError exception.

Examples

>>> import dpnp as np
>>> np.eye(2, dtype=int)
array([[1, 0],
       [0, 1]])

>>> np.eye(3, k=1)
array([[0.,  1.,  0.],
       [0.,  0.,  1.],
       [0.,  0.,  0.]])

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

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

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

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