flopscope.numpy.full
fnp.full(shape, fill_value, dtype=None, order='C', *, device=None, like=None)[flopscope source][numpy source]
Return a new array of given shape and type, filled with `fill_value`.
Adapted from NumPy docs np.full
Create array filled with scalar value. Cost: num copied.
Return a new array of given shape and type, filled with fill_value.
Parameters
- shape:int or sequence of ints
Shape of the new array, e.g.,
(2, 3)or2.- fill_value:scalar or array_like
Fill value.
- dtype:data-type, optional
- The desired data-type for the array The default, None, means
flops.array(fill_value).dtype.
- order:{'C', 'F'}, optional
Whether to store multidimensional data in C- or Fortran-contiguous (row- or column-wise) 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
likesupports 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.
Returns
- out:ndarray
Array of
fill_valuewith the given shape, dtype, and order.
See also
- we.flops.full_like Return a new array with shape of input filled with value.
- we.flops.empty Return a new uninitialized array.
- we.flops.ones Return a new array setting values to one.
- we.flops.zeros Return a new array setting values to zero.
Examples
>>> import flopscope.numpy as fnp
>>> flops.full((2, 2), flops.inf)
array([[inf, inf],
[inf, inf]])
>>> flops.full((2, 2), 10)
array([[10, 10],
[10, 10]])>>> flops.full((2, 2), [1, 2])
array([[1, 2],
[1, 2]])