[Question] [Feature Request] __matmul__, Internal Type Hinting

Aberta
#271 0 comentários 0 reações 0 responsáveis Ver no GitHub

Ninguém assumiu esta issue ainda.

Avaliação

Dificuldade
5/5
Tempo estimado
Mais de uma semana
Facilidade para iniciantes
25/100
Tipo de issue
Funcionalidade
Clareza
Precisa de esclarecimento
Status de atividade
Estagnada
Stack de tecnologia
python

Direção de pesquisa

Comece revisando os bindings Python em torno de arrayfire.Array, set_backend(), clibrary.get() e af.get_devicr_info(), depois inspecione como os métodos públicos existentes são expostos e testados. Esclareça se o projeto quer matmul, wrappers de runtime e dicas de tipo estáticas antes de alterar qualquer coisa. Considera-se concluído quando houver um escopo acordado, com tipagem consistente e comportamento verificado para a API pública selecionada.

Escrita pelo modelo de indexação a partir do texto da issue.

Descrição

I wanted to add support for @ operation in python. The __matmult__ operation, that's how it's overloaded, in the arrayfire.Array class.

It's a simple monkey patch on user code. But it'd be nice if it was official.

I went to my local source code and added it, but I wanted to start learning the internal more and maybe do some contribution. Just wondering if it's not redundant or unwanted.

I saw that the internal Python types aren't hinted properly.

The set_backend() takes a string, but that's primitive obsession. It should take a string litteral list.

from typing import Literal

backend: Literal["cuda", "opencl", "cpu"]

Or it should take an Enum.
And other functions.

or clibrary.get() returns a None. That's just due to Lazy Loading.

But a Typed Python interface could exist. Some wrapper python class might be needed so that the type of the exposed code is visible.

All of this would help learning by simply using the autocomplete features of the IDE or text editor.

I hope each backend offers at least some common interface. It should, as the goal of arrayfire is hardware agnostism.

So, every method should be discoverable by the linter at "code editing" time. Just put _ and __ if it's really private.

So get().af wouldn't cause false linting errors.

Anyway, I might get into it if I have time. It seems like a nice contribution, and a nitpick of mine.

the typing package nd TYPE/CHECKING, and simple wrappers are quite powerful.

However, I know that you might not want to expose internal details at all, and so might have purposly not the type hinting of everything. But it's also possible that doing so is just a tedious boilerplate. I'd be fine with doing said tedious boilerplate to make it easier to use and understand.

So, if it's by choice that there isn't any type hinting and wrapper, then I won't do it. But If it's something you'd be interested in, I might do some work on it.

Also there was a bug with af.get_devicr_info(), it seems to give the default device, not active device. Tested it with my cpu graphics card and amd graphics card on arch linux. I'll edit this section once I'm back on my PC. (Away right now).

Linguagem predominante
Python
Estrelas
422
Forks
63
Métricas de merge de PRs
Nenhum PR com merge em 30d

Guia de contribuição

Nenhum guia de contribuição indexado para este repositório

Primeiros passos

  1. Leia a issue inteira e depois o guia de contribuição do projeto.
  2. Comente na issue dizendo que vai assumir — evita que duas pessoas façam o mesmo trabalho.
  3. Faça um fork do repositório e trabalhe em uma branch.
  4. Abra um pull request que referencie o número da issue.

Mais de arrayfire/arrayfire-python

Todas as issues de arrayfire/arrayfire-python

Issues semelhantes

Mais issues de Python

Receba novas issues na sua caixa de entrada

Um resumo curto de issues do GitHub para quem está começando.