flopscope.numpy.ones

fnp.ones(shape, dtype=None, order='C', *, device=None, like=None)[flopscope source][numpy source]

Return a new array of given shape and type, filled with ones.

Adapted from NumPy docs np.ones

Areacore

Typefree

NumPy Refnp.ones

Cost

Flopscope Context

Create one-filled array.

Parameters

shape:int or sequence of ints: Shape of the new array, e.g., (2, 3) or 2.
dtype:data-type, optional: The desired data-type for the array, e.g., flops.int8. Default is flops.float64.
order:{'C', 'F'}, optional, default: C: Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory.
device:str, optional: The device on which to place the created array. Default: None. For Array-API interoperability only, so must be "cpu" if passed.
Added in version 2.0.0.
like:array_like, optional: Reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as like supports the __array_function__ protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.
Added in version 1.20.0.

>>> import flopscope.numpy as fnp
>>> flops.ones(5)
array([1., 1., 1., 1., 1.])

>>> flops.ones((5,), dtype=int)
array([1, 1, 1, 1, 1])

>>> flops.ones((2, 1))
array([[1.],
       [1.]])

>>> s = (2,2)
>>> flops.ones(s)
array([[1.,  1.],
       [1.,  1.]])