xorbits.numpy.ones_like(a, dtype=None, gpu=None, order='K')[source]#

Return an array of ones with the same shape and type as a given array.

  • a (array_like) – The shape and data-type of a define these same attributes of the returned array.

  • dtype (data-type, optional) –

    Overrides the data type of the result.

    New in version 1.6.0(numpy).

  • order ({'C', 'F', 'A', or 'K'}, optional) –

    Overrides the memory layout of the result. ‘C’ means C-order, ‘F’ means F-order, ‘A’ means ‘F’ if a is Fortran contiguous, ‘C’ otherwise. ‘K’ means match the layout of a as closely as possible.

    New in version 1.6.0(numpy).

  • subok (bool, optional. (Not supported yet)) – If True, then the newly created array will use the sub-class type of a, otherwise it will be a base-class array. Defaults to True.

  • shape (int or sequence of ints, optional. (Not supported yet)) –

    Overrides the shape of the result. If order=’K’ and the number of dimensions is unchanged, will try to keep order, otherwise, order=’C’ is implied.

    New in version 1.17.0(numpy).


out – Array of ones with the same shape and type as a.

Return type


See also


Return an empty array with shape and type of input.


Return an array of zeros with shape and type of input.


Return a new array with shape of input filled with value.


Return a new array setting values to one.


>>> x = np.arange(6)  
>>> x = x.reshape((2, 3))  
>>> x  
array([[0, 1, 2],
       [3, 4, 5]])
>>> np.ones_like(x)  
array([[1, 1, 1],
       [1, 1, 1]])
>>> y = np.arange(3, dtype=float)  
>>> y  
array([0., 1., 2.])
>>> np.ones_like(y)  
array([1.,  1.,  1.])
gpubool, optional

Allocate the tensor on GPU if True, None as default

This docstring was copied from numpy.