QuantEcon / QuantEcon/lecture-python-programming.fa
_admonition/gpu.md is present but untranslated (still English)
Dieses Issue hat noch niemand übernommen.
- Vorherrschende Sprache
- Python
- Sterne
- 1
- Forks
- 1
- Ø Merge
- 10 Std. 5 Min.
- Gemergte PRs (30 T.)
- 5
Beschreibung
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).
Beitragsleitfaden
Für dieses Repository ist kein Beitragsleitfaden indexiert
Erste Schritte
- Lies das ganze Issue und danach den Beitragsleitfaden des Projekts.
- Schreib ins Issue, dass du es übernimmst — das erspart doppelte Arbeit.
- Forke das Repository und arbeite in einem Branch.
- Öffne einen Pull Request, der die Issue-Nummer nennt.
Rechercherichtung
Öffne lectures/_admonition/gpu.md und vergleiche die Datei mit der englischen Quelle und der übersetzten .zh-cn-Kopie. Übersetze den Inhalt der Admonition ins Persische und bewahre dabei den Directive-Header, die Warning-Klasse, die Google-Colab-URL und das wörtliche UI-Label. Überprüfe, dass das Ergebnis in autodiff, jax_intro und numpy_vs_numba_vs_jax korrekt gerendert wird.
Vom Indexierungsmodell aus dem Issue-Text verfasst.
Bewertung
- Tech-Stack
- python
- Bereich
- documentation, localization
- Issue-Typ
- Dokumentation
- Schwierigkeit
- 2/5
- Geschätzter Aufwand
- 1-3 Stunden
- Aktivitätsstatus
- Ruhig
- Klarheit
- Klar beschrieben
- Anfängerfreundlichkeit
- 78/100