QuantEcon / QuantEcon/lecture-python-programming.fa

_admonition/gpu.md is present but untranslated (still English)

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描述

lectures/_admonition/gpu.md in this repo is byte-identical to the English source — it was seeded but never translated. It is included by three lectures (autodiff, jax_intro, numpy_vs_numba_vs_jax), so the English GPU admonition renders inside three otherwise-Persian pages.

For comparison, .zh-cn has a properly translated copy, and .fr was missing the file entirely (fixed in .fr#14).

Why this needs its own issue

A strict build will not catch it. The include resolves, so there is no warning and no error — -W (added to this repo's ci.yml in #137) only catches the missing-file case, not the untranslated-content case. Nothing in the current pipeline flags an asset that exists but was never translated.

That is worth noting beyond this one file: shared assets under lectures/_admonition/ sit outside the set that translation sync moves, so they are neither synced nor reviewed. See action-translation#117 for the same class on quant-econ.bib.

Fix

Translate the admonition body into Persian, keeping the directive header and :class: warning option line unchanged, and keeping the Google Colab URL and the literal UI label intact.

Current content:

:class: warning

This lecture was built using a machine with access to a GPU --- although it will also run without one.

[Google Colab](https://colab.research.google.com/) has a free tier with GPUs
that you can access as follows:

1. Click on the "play" icon top right
2. Select Colab
3. Set the runtime environment to include a GPU

Found while enabling strict builds across the programming trio (QuantEcon/project-translation#9).

貢獻指南

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從這裡開始

  1. 先讀完整個 Issue,再讀專案的貢獻指南。
  2. 在 Issue 下留言說明你要接手 —— 這能避免兩個人做同樣的事。
  3. Fork 儲存庫,在一個分支上完成修改。
  4. 送出 Pull Request,並在描述裡引用這個 Issue 編號。

研究方向

開啟 lectures/_admonition/gpu.md,並與英文來源和已翻譯的 .zh-cn 副本進行比較。將 admonition 內文翻譯成波斯語,同時保留 directive header、warning class、Google Colab URL 和字面 UI 標籤;確認結果在 autodiff、jax_intro 和 numpy_vs_numba_vs_jax 中能正確轉譯。

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評估

技術堆疊
python
領域
documentation, localization
Issue 類型
文件
難度
2/5
預估耗時
1-3 小時
活躍度
冷清
描述清晰度
描述清楚
新手友好度
78/100

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