[action-translation] resync: career.md - #188
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Pull request overview
This PR forward-resyncs the Chinese translation of lectures/career.md to match the upstream JAX-based implementation in the source repository, replacing the older NumPy/Numba/quantecon.random approach and bringing headings/content back in sync.
Changes:
- Resynced the lecture content to a JAX-based implementation (imports, Bellman operator via
jax.vmap, solver viajax.lax.while_loop, and simulation viajax.lax.scan/jax.vmap). - Added GPU include admonition and updated exercise/solution blocks to match current source structure.
- Added translation sync state metadata for
career.md.
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 4 comments.
| File | Description |
|---|---|
| lectures/career.md | Full-document resync to the upstream JAX-based lecture version, including new code cells, headings, and exercises. |
| .translate/state/career.md.yml | Records the source commit SHA and resync metadata for translation tracking. |
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| v_star, _, _ = solve_model(cw) | ||
| greedy_star = get_greedy(v_star, cw) | ||
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| key = jr.key(42) |
| def draw(key, cdf): | ||
| "根据给定的累积分布函数从分布中抽取一个下标。" | ||
| return jnp.searchsorted(cdf, jr.uniform(key), side="right") |
| return jnp.median(times) | ||
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| median_passage_time(cw, greedy_star, jr.key(42)) |
| v_patient, _, _ = solve_model(cw_patient) | ||
| greedy_patient = get_greedy(v_patient, cw_patient) | ||
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| median_passage_time(cw_patient, greedy_patient, jr.key(42)) |
✅ Translation Quality ReviewVerdict: PASS | Model: claude-sonnet-5 | Date: 2026-07-22 📝 Translation Quality
Summary: This is a high-quality, accurate, and fluent translation that faithfully preserves the technical content, mathematical notation, and code structure of the source document. Terminology usage aligns well with the provided glossary, and formatting/MyST directives are fully intact. Minor stylistic differences exist in a few sentences where the translation is slightly more elaborative than the source, but these do not affect accuracy or clarity in any meaningful way. Mathematical notation, LaTeX equations, and code cells are fully preserved and correctly formatted throughout. Technical terminology (贝尔曼算子, 贴现因子, 贪婪策略, 价值函数, etc.) is consistent with the glossary and used correctly across the document. The added translation metadata block and font-loading code insertion are appropriately handled without disrupting document structure. Complex JAX-related technical explanations (vmap, in_axes, while_loop) are translated clearly and accurately, preserving technical precision. Suggestions:
🔍 Diff Quality
Summary: The resynced target correctly mirrors the current English source's structure, code, and content, with an appropriately updated translation metadata block. This review was generated automatically by action-translation review mode. |
Addresses the terminology-consistency and emphasis suggestions from the AI review on #188. The 维持现状/保持现状 variants predate this resync on main; unified on the definitional term. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Re the review's three suggestions: Suggestions 1–2 addressed in 8ae3b2d: 'stay put' is now 原地不动 in all ten occurrences (the 维持现状/保持现状 variants predate this resync on Suggestion 3 is a false positive: the The recurring-phrase consistency gap itself is now a feature request on the engine — see the issue linked below. |
Forward Resync: career.md
Source: QuantEcon/lecture-python.myst — lectures/career.md
Source commit:
775c47cThis PR resyncs the translation to match the current source document.
Reason: The Chinese translation uses an entirely different (older) implementation based on NumPy/Numba/quantecon.random instead of the JAX-based implementation in the source. Missing content includes: 'Job Search VI' title (says V), gpu.md include admonition, JAX imports, NamedTuple-based CareerWorkerProblem factory function, jax.vmap-based Bellman operator implementation, jax.lax.while_loop solve_model, the note about JAX scaling to GPU/25000 simulations, jax-based simulate_path and passage_time functions using jr.split/jax.lax.scan/jax.vmap. The target instead has older numba/quantecon-based code for gen_probs, CareerWorkerProblem class, operator_factory, solve_model, gen_path, passage_time, median_time - substantively different implementation details throughout Implementation section and exercises. This represents significant CONTENT_CHANGES since the source has been updated to a JAX-based approach but the translation still reflects the old NumPy/Numba approach.
Changes
Whole-file resync applied. The entire document was resynced in a single pass.
Created by action-translation forward resync