feat: support array API #3922
feat: support array API #3922
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Fix deepmodeling#3430. This PR sets up the basic support for the array API, and make an example function (`compute_smooth_weight`) to support the array API. I believe NumPy and JAX have supported it (or through `array-api-compat`), so we don't need to write things twice for NumPy and JAX (although we can write them using the ChatGPT, it's still better to maintain only one thing). There are some challeging to use it in the TorchScript, so I give it up. Supporting more function can be implemented in the following PRs. Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
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Outside diff range and nitpick comments (1)
deepmd/dpmodel/utils/env_mat.py (1)
Line range hint
69-72: Consider simplifying conditional logic with a ternary operator.- if radial_only: - env_mat = t0 * weight - else: - env_mat = np.concatenate([t0, t1], axis=-1) * weight + env_mat = t0 * weight if radial_only else np.concatenate([t0, t1], axis=-1) * weightThis simplification reduces the lines of code and enhances readability by using a ternary operator instead of a full if-else block.
Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## devel #3922 +/- ##
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Coverage 82.73% 82.73%
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Files 519 520 +1
Lines 50539 50549 +10
Branches 3015 3015
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+ Hits 41812 41821 +9
- Misses 7791 7792 +1
Partials 936 936 ☔ View full report in Codecov by Sentry. |
Fix deepmodeling#3430. This PR sets up the basic support for the array API, and make an example function (`compute_smooth_weight`) to support the array API. I believe NumPy and JAX have supported it (or through `array-api-compat`), so we don't need to write things twice for NumPy and JAX (although we can write them using the ChatGPT, it's still better to maintain only one thing). There are some challeging to use it in the TorchScript, so I give it up. Supporting more function can be implemented in the following PRs. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **New Features** - Introduced testing for `compute_smooth_weight` function using `array_api_strict` for enhanced array operations. - **Chores** - Updated dependencies to include `'array-api-compat'` and `'array-api-strict>=2'` for improved compatibility and testing capabilities. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
Fix #3430.
This PR sets up the basic support for the array API, and make an example function (
compute_smooth_weight) to support the array API. I believe NumPy and JAX have supported it (or througharray-api-compat), so we don't need to write things twice for NumPy and JAX (although we can write them using the ChatGPT, it's still better to maintain only one thing). There are some challeging to use it in the TorchScript, so I give it up. Supporting more function can be implemented in the following PRs.Summary by CodeRabbit
New Features
compute_smooth_weightfunction usingarray_api_strictfor enhanced array operations.Chores
'array-api-compat'and'array-api-strict>=2'for improved compatibility and testing capabilities.