TensorRT also includes optional high speed mixed precision capabilities with the NVIDIA TensorRT also supplies a runtime that you can use to execute this network onĪll of NVIDIA’s GPU’s from the NVIDIA Pascal™ generation onwards. Implementation of that model leveraging a diverse collection of highly optimized ![]() Optimizations, layer fusions, among other optimizations, while also finding the fastest ![]() TensorRT to optimize and run them on an NVIDIA GPU. The Network Definition API or load a pre-defined model via the parsers that allow TensorRT provides APIs via C++ and Python that help to express deep learning models via Trained parameters, and produces a highly optimized runtime engine that performs ![]() TensorRT takes a trained network, which consists of a network definition and a set of That facilitates high-performance inference on NVIDIA graphics processing units (GPUs). The core of NVIDIA ® TensorRT™ is a C++ library
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