西柚加速器破解版永久免- 爬墙专用加速器

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.

西柚加速器破解版永久免- 爬墙专用加速器

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.

西柚加速器破解版永久免- 爬墙专用加速器

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.

西柚加速器破解版永久免- 爬墙专用加速器

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