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✅ Translation Quality ReviewVerdict: PASS | Model: claude-sonnet-4-6 | Date: 2026-04-14 📝 Translation Quality
Summary: The translation is of high quality across all modified sections. Technical accuracy is excellent, with correct rendering of JAX, Numba, and NumPy concepts. Fluency is natural and the academic register is appropriate throughout. Terminology follows the reference glossary consistently. Formatting is well-preserved with no syntax errors detected. Minor issues include slightly awkward phrasing in a few places (notably the broken English sentence in the JIT Compilation section and a word choice issue with '改善' vs '缩短'), but these do not significantly impact comprehension. Technical terminology is consistently and correctly translated throughout all modified sections, including JIT编译, 向量化, 纯函数, and domain-specific finance terms like 欧式看涨期权 and 随机波动率. The translation of the Exercises section accurately captures all parameters, mathematical notation, and instructions from the English source, including the Monte Carlo option pricing exercise. MyST directives, code blocks, LaTeX math equations, and cross-references are all preserved correctly with no formatting errors in the modified sections. The NumPy vs Numba vs JAX comparison sections (NumPy vectorization, A Comparison with Numba, Parallelized Numba, Vectorized code with JAX, JAX plus vmap, Summary, Numba Version, JAX Version, Summary) are fluently translated and maintain the technical accuracy of the performance comparisons. The preamble/frontmatter translation metadata is correctly structured with appropriate heading mappings, following the established translation sync system conventions. Suggestions:
🔍 Diff Quality
Summary: All three files are correctly modified with changes appearing in the right positions, document structure preserved, and heading maps accurately updated to reflect the restructured JIT Compilation section and new Size Experiment subsection. This review was generated automatically by action-translation review mode. |
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Pull request overview
Automated zh-cn translation sync aligning several JAX/Numba-related lectures with upstream “Minor edits” updates.
Changes:
- Updates lecture content in
jax_intro.md,numba.md, andnumpy_vs_numba_vs_jax.md(timing examples, structure, and wording). - Adjusts translation metadata (headings/anchors) in updated lecture front-matter.
- Updates
.translate/state/*.ymlto reflect new upstream source SHA and sync state.
Reviewed changes
Copilot reviewed 6 out of 6 changed files in this pull request and generated 4 comments.
Show a summary per file
| File | Description |
|---|---|
| lectures/numpy_vs_numba_vs_jax.md | Updates vectorized/parallel/JAX/vmap sections and timing snippets; changes some example code. |
| lectures/numba.md | Restructures the “Compiling Functions” section and updates anchors/headings. |
| lectures/jax_intro.md | Restructures JIT compilation section and updates heading metadata; modifies examples. |
| .translate/state/numpy_vs_numba_vs_jax.md.yml | Updates translation sync state (sha/date/mode/tool version/section count). |
| .translate/state/numba.md.yml | Updates translation sync state (sha/date/mode/tool version/section count). |
| .translate/state/jax_intro.md.yml | Updates translation sync state (sha/date/mode/tool version/section count). |
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| for j in range(n): | ||
| x = grid[i] | ||
| y = grid[j] | ||
| z = np.cos(x**2 + y**2) / (1 + x**2 + y**2) | ||
| if z > m: | ||
| m = z | ||
| m = max(m, z) |
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compute_max_numba_parallel updates the shared variable m inside a numba.prange loop (m = max(m, z)), which is a data race and can return incorrect results. Use a thread-safe reduction pattern instead (e.g., compute per-i maxima into an array inside the prange loop and take np.max afterward, or use a supported Numba reduction).
| JAX as a NumPy Replacement::Differences::Speed!: 精度 | ||
| JAX as a NumPy Replacement::Differences::Precision: 不可变性 | ||
| JAX as a NumPy Replacement::Differences::Immutability: 变通方法 |
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The translation heading mapping under JAX as a NumPy Replacement::Differences is inconsistent: Speed! is mapped to 精度, Precision to 不可变性, and Immutability to 变通方法, but the document section headings are 精度/不可变性/变通方法 (and there is no Speed! section). This will break navigation/translation alignment; please correct the heading keys/values to match the actual sections.
| JAX as a NumPy Replacement::Differences::Speed!: 精度 | |
| JAX as a NumPy Replacement::Differences::Precision: 不可变性 | |
| JAX as a NumPy Replacement::Differences::Immutability: 变通方法 | |
| JAX as a NumPy Replacement::Differences::Precision: 精度 | |
| JAX as a NumPy Replacement::Differences::Immutability: 不可变性 | |
| JAX as a NumPy Replacement::Differences::Workarounds: 变通方法 |
| ```{code-cell} | ||
| def f(x): | ||
| y = jnp.cos(2 * x**2) + jnp.sqrt(jnp.abs(x)) + 2 * jnp.sin(x**4) - x**2 | ||
| return y | ||
| ``` | ||
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This code-cell block is missing a closing triple-backtick fence after the function definition, so the rest of the markdown will be parsed as code. Add the closing fence (and, if intended, put x = jnp.linspace(...) in its own subsequent code-cell).
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@copilot apply changes based on this feedback
Also deal with the merge conflict by only incorprate changes that are in QuantEcon/lecture-python-programming#528
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Merged main into this branch and resolved all merge conflicts by preserving earlier translation PR content and applying only PR #528 changes. Key fixes in bf85634:
- Heading mapping: Fixed the shifted key/value alignment (Speed!→精度 is now correct: Precision→精度, Immutability→不可变性, etc.)
{ref}target: The(jax_speed)=label now exists from the earlier translation of the Speed! section, so the reference resolves correctly- Code cell structure: The function definition and
x = jnp.linspace(0, 10, n)are correctly in the same code cell, matching upstream - JIT section: Removed the "simple example" subsection (now in Speed! section from earlier PR), restructured to match PR #528
- Parallel Numba: Simplified to remove incorrect attempt and v2, keeping only the correct version with
m = max(m, z) - Timer/comments: Updated
qe.Timer(precision=8)→qe.Timer(), added# First run/# Second run/# Hold interpretercomments throughout
| 通常，运行时间会先增加然后再减少（这在 GPU 上会更加明显）。 | ||
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| 这是因为 JIT 编译器针对数组大小进行专门优化以利用并行化——因此当数组大小改变时会生成新的编译代码。 | ||
| 当我们在 {ref}`上面 <jax_speed>` 对一个大型数组应用 `cos` 时，我们看到了 JAX 的 JIT 编译器结合并行硬件的强大之处。 |
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This {ref} target (<jax_speed>) is unresolved: there is no (jax_speed)= label in this file or elsewhere in the repo, so the reference will break during documentation build. Either reintroduce the missing label at the intended location (e.g., the earlier speed example) or remove/replace the reference with an existing label/section.
| 当我们在 {ref}`上面 <jax_speed>` 对一个大型数组应用 `cos` 时，我们看到了 JAX 的 JIT 编译器结合并行硬件的强大之处。 | |
| 当前面我们对一个大型数组应用 `cos` 时，我们看到了 JAX 的 JIT 编译器结合并行硬件的强大之处。 |
Resolve merge conflicts by preserving earlier translation PR content and applying only PR #528 specific changes: - jax_intro.md: Restructure JIT section, add timer comments - numba.md: Change int(n) to n - numpy_vs_numba_vs_jax.md: Simplify parallel Numba section, update timers Co-authored-by: HumphreyYang <39026988+HumphreyYang@users.noreply.github.com>
…ba_vs_jax.md Agent-Logs-Url: https://github.com/QuantEcon/lecture-python-programming.zh-cn/sessions/92cf1688-2d57-44e9-8f1e-f49228181b4f Co-authored-by: HumphreyYang <39026988+HumphreyYang@users.noreply.github.com>
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@copilot Please handle the merge conflict again by only incorprate changes that are in QuantEcon/lecture-python-programming#528 and keep what's in the main for the rest |
Resolve merge conflicts by keeping main's content as base and applying
only the specific changes from upstream PR #528 (Minor edits):
jax_intro.md:
- Update heading map (remove 'Evaluating a more complicated function', capitalize 'Whole', remove 'Summary')
- Restructure JIT section: remove subsection heading, promote sub-headings to ###
- Change 'the *entire* function' to 'the entire function'
- Fix jax_speed undefined label by removing duplicate (jax_speed)= target
numba.md:
- Change int(n) to n in three Timer calls
numpy_vs_numba_vs_jax.md:
- Replace qe.Timer(precision=8) with qe.Timer() throughout
- Change 'if z > m: m = z' to 'm = max(m, z)' in compute_max_numba
- Split code cells and add # First run/# Second run/# Hold interpreter comments
- Remove incorrect parallel attempt and v2 alternative
- Change static_argnums=(1,) to static_argnames=('n',)
- Condense note block text
- Various text tweaks to match upstream
Co-authored-by: HumphreyYang <39026988+HumphreyYang@users.noreply.github.com>
Re-merged main and applied only PR #528 changes in
Note: The duplicate "速度！" section (lines 126 vs 234) is a pre-existing issue in main from overlapping translation PRs — I left it untouched per your instruction to keep main content. |
…ding - Add #### 大小实验 heading to match English #### Size Experiment structure - Remove duplicate #### 速度！ section (was duplicated from overlapping translation PRs) - Add Size Experiment entry to heading map in frontmatter Agent-Logs-Url: https://github.com/QuantEcon/lecture-python-programming.zh-cn/sessions/9216d7c8-4733-4e5e-a1c5-74a4d6018ce1 Co-authored-by: HumphreyYang <39026988+HumphreyYang@users.noreply.github.com>
Automated Translation Sync
This PR contains automated translations from QuantEcon/lecture-python-programming.
Source PR
#528 - Minor edits
Files Updated
lectures/jax_intro.md.translate/state/jax_intro.md.ymllectures/numba.md.translate/state/numba.md.ymllectures/numpy_vs_numba_vs_jax.md.translate/state/numpy_vs_numba_vs_jax.md.ymlThe following sections were not modified by this source PR and are missing from the target. They have been omitted from this PR to keep it scoped to the source PR's actual changes. An earlier translation PR should add them. If that PR is abandoned, run
/translate-resyncto recover.lectures/jax_intro.md:Vectorization with \vmap`,Automatic differentiation: a preview`lectures/numba.md:Sharp Bitslectures/numpy_vs_numba_vs_jax.md:Overall recommendationsDetails
This PR was created automatically by the translation action.