This repo uses the GPU-optimization work byyunchih, which improves several processes in theTrackingthread, i.e.FAST corner detectionandORB feature extraction, with CUDA APIs. In general, where possible you can parallelize all OpenCV functions by replacing them with OpenCV CUDA functions. I would ...
# visualize the first prediction's explanation with a force plotshap.plots.force(shap_values[0]) If we take many force plot explanations such as the one shown above, rotate them 90 degrees, and then stack them horizontally, we can see explanations for an entire dataset (in the notebook th...
现在可以在计算 SHAP 值时利用 GPU 硬件,从而加快整个模型解释过程。 GPUTreeShap enables massively exact calculation of the shape values for tree-based algorithms.图 4 显示了 GPUTreeSHAP 如何提供在 CPU 上使用带有 GPU 的 SHAP 时获得的增益估计。根据GPUTreeShap: Massively Parallel Exact Calculatio...
NVIDIA-Docker is a Docker solution for NVIDIA’s popular CUDA framework which can help in maximum resource utilization on the GPU. It provides a runtime that mounts the underlying NVIDIA driver to a container which is totally independent of the version of CUDA that is installed in the machine...