QuantEcon / QuantEcon/lecture-python-programming.fa
_admonition/gpu.md is present but untranslated (still English)
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- Langage dominant
- Python
- Étoiles
- 1
- Forks
- 1
- Merge moyen
- 10 h 5 min
- PR mergées (30 j)
- 5
Description
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).
Guide de contribution
Aucun guide de contribution indexé pour ce dépôt
Par où commencer
- Lisez l'issue en entier, puis le guide de contribution du projet.
- Signalez en commentaire que vous la prenez — cela évite que deux personnes fassent le même travail.
- Forkez le dépôt et travaillez sur une branche.
- Ouvrez une pull request qui référence le numéro de l'issue.
Piste de recherche
Ouvrez lectures/_admonition/gpu.md et comparez-le avec la source anglaise et la copie traduite .zh-cn. Traduisez le corps de l’admonition en persan tout en conservant l’en-tête de la directive, la classe warning, l’URL Google Colab et le libellé littéral de l’UI ; vérifiez que le résultat se rende correctement dans autodiff, jax_intro et numpy_vs_numba_vs_jax.
Rédigé par le modèle d'indexation à partir du texte de l'issue.
Évaluation
- Stack technique
- python
- Domaine
- documentation, localization
- Type d'issue
- Documentation
- Difficulté
- 2/5
- Temps estimé
- 1-3 heures
- Activité
- Calme
- Clarté
- Clairement spécifiée
- Accessibilité débutants
- 78/100