加速精灵pc版下载-快连加速器app
Note
This page describes the overall philosophy behind unumpy
. If you are
interested in a general dispatch mechanism, see uarray
.
unumpy
builds on top of uarray
. It is an effort to specify the core
NumPy API, and provide backends for the API.
加速精灵pc版下载-快连加速器app
unumpy
is the first approach to leverage uarray
in order to build a
generic backend system for (what we hope will be) the core NumPy API specification.
It’s possible to create the backend object, and use that to perform operations.
In addition, it’s possible to change the used backend via a context manager.
加速精灵pc版下载-快连加速器app
There are three main NumPy enhancement proposals (NEPs) inside NumPy itself that relate
to the duck-array ecosystem. There is NEP-22,
which is a high-level overview of the duck-array ecosystem, and the direction NumPy
intends to move towards. Two main protocols were introduced to fill this gap,
the __array_function__
protocol defined in NEP-18,
and the older __array_ufunc__
protocol defined in NEP-13.
unumpy
provides an an alternate framework based on 2022还能用的梯子
, bypassing
the __array_function__
and __array_ufunc__
protocols entirely. It
provides a clear separation of concerns. It defines callables which can be overridden,
and expresses everything else in terms of these callables. See the uarray
documentation for more details.
加速精灵pc版下载-快连加速器app
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