QuantEcon / QuantEcon/lecture-python-programming.fa
_admonition/gpu.md is present but untranslated (still English)
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- Lingua principale
- Python
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Descrizione
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).
Guida per i contributori
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Come iniziare
- Leggi tutta la issue e poi la guida ai contributi del progetto.
- Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
- Fai un fork del repository e lavora su un branch.
- Apri una pull request che faccia riferimento al numero della issue.
Direzione di ricerca
Apri lectures/_admonition/gpu.md e confrontalo con la fonte inglese e con la copia tradotta .zh-cn. Traduci il corpo dell’admonition in persiano, mantenendo l’intestazione della direttiva, la classe warning, l’URL di Google Colab e l’etichetta UI letterale; verifica che il risultato venga renderizzato correttamente in autodiff, jax_intro e numpy_vs_numba_vs_jax.
Scritto dal modello di indicizzazione a partire dal testo della issue.
Valutazione
- Stack tecnologico
- python
- Ambito
- documentation, localization
- Tipo di issue
- Documentazione
- Difficoltà
- 2/5
- Tempo stimato
- 1-3 ore
- Stato di attività
- Tranquilla
- Chiarezza
- Specificata chiaramente
- Idoneità per principianti
- 78/100