cupyx.zeros_like_pinned#
- cupyx.zeros_like_pinned(a, dtype=None, order='K', subok=None, shape=None)[source]#
Returns a new, zero-initialized NumPy array with the same shape and dtype as those of the given array.
This is a convenience function which is just
numpy.zeros_like()
, except that the underlying memory is pinned/pagelocked.This function currently does not support
subok
option.- Parameters:
a (numpy.ndarray or cupy.ndarray) – Base array.
dtype – Data type specifier. The dtype of
a
is used by default.order ({'C', 'F', 'A', or 'K'}) – Overrides the memory layout of the result.
'C'
means C-order,'F'
means F-order,'A'
means'F'
ifa
is Fortran contiguous,'C'
otherwise.'K'
means match the layout ofa
as closely as possible.subok – Not supported yet, must be None.
shape (int or tuple of ints) – 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.
- Returns:
An array filled with zeros.
- Return type:
See also