renewable-huber-native-cuda

Optional Rust/CUDA 12 engine for renewable-huber. Version 0.6.1 requires exactly renewable-huber==0.6.1.

python -m pip install renewable-huber-native-cuda==0.6.1

Published wheels currently support CPython 3.10–3.12 on Windows x86-64. The wheel does not bundle NVIDIA libraries. It requires a compatible NVIDIA driver and a CUDA 12 runtime discoverable through CUDA_PATH, including cudart, cuBLAS/cuBLASLt, cuSOLVER, cuSPARSE and nvJitLink DLLs. Rust, CMake, Visual Studio and nvcc are not required to install the wheel.

from renewable_huber import RenewableHuberRegressor

model = RenewableHuberRegressor(
    backend="native_cuda",
    device="cuda",
    dtype="float32",
    penalty="none",
)
model.fit(X, y)

The whole-batch engine accepts contiguous host NumPy arrays. Its update path also accepts C-contiguous CuPy, PyTorch-CUDA and TensorFlow-eager GPU tensors through DLPack in exact float32 or float64. All inputs must already be on the selected engine device; dtype casts, contiguous copies, cross-device copies and host staging are never implicit. CuPy/PyTorch negotiate the consumer stream directly; TensorFlow uses an explicit producer synchronization boundary before zero-copy export.

Device-resident prediction is not part of the current ABI: predict accepts host input and returns a NumPy array. The engine currently supports penalty="none" and is always selected explicitly; backend="auto" never chooses native CUDA. See the project support matrix for CUDA Graph and fast-math limits.

Source builds require CUDA Toolkit 12.x (12.8+ for the release architecture set), Visual Studio 2022 C++ Build Tools on Windows, CMake, Ninja, Rust and Maturin. Developer builds target the active GPU by default and are not portable release wheels.