[StandardScaler] Rust- and numpy-backed implementation of StandardScaler#30
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e-strauss wants to merge 2 commits into
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[StandardScaler] Rust- and numpy-backed implementation of StandardScaler#30e-strauss wants to merge 2 commits into
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| let mut compute = || { | ||
| let stats: Vec<(f32, f32)> = (0..n_cols) | ||
| .into_par_iter() |
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This is good, but we may want to use SIMD (std::simd) for the kernels in the future.
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Introduces a parallel Rust `StandardScaler` kernel (`fit` + `transform`) and a NumPy-backed `StandardScaler`, wired through the Python adapter with sklearn-compatible fallback behavior. Adds correctness/fallback tests for both backends, and adds comprehensively benchmark and comparison of backends.
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Rust- and numpy-backed implementation of StandardScaler
StandardScalerThis PR does not contain the integration into stratum optimizer yet, e.g. for operator selection.
The benchmark evaluates the impact of the number of rows and columns of the Input X. Each datapoint is the average of 5 repeated runs.
Benchmark results:
Micro Benchmark number of concurrent tasks for Rust
Parallel StandardScaler Benchmark