[pull] master from deepmodeling:master - #14
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This is useful when the LR is within the JAX JIT compilation - the step is given as a `jnp.ndarray` and NumPy should not be used. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Learning-rate API now accepts array-like steps and computes schedules using backend-agnostic array operations; exponential and cosine schedulers support array inputs and preserve minimum learning-rate behavior. * **Tests** * Added cross-backend consistency tests to validate identical learning-rate outputs across NumPy, PyTorch, JAX and array-api backends. * **Chores** * Updated test dependency constraint and bumped default test API version used by strict array-api tests. <sub>✏️ Tip: You can customize this high-level summary in your review settings.</sub> <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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