TIM-VX is a software integration module provided by VeriSilicon to facilitate deployment of Neural-Networks on OpenVX enabled ML accelerators. It serves as the backend binding for runtime frameworks such as Android NN, Tensorflow-Lite, MLIR, TVM and more.
Main Features
- Over 130 internal operators with rich format support for both quantized and floating point
- Simplified binding API calls to create Tensors and Operations
- Dynamic graph construction and supports shape inferencing
- Built-in custom layer extensions
- A set of utility functions for debugging
Roadmap of TIM-VX will be updated here in the future.
TIM-VX uses bazel build system by default. Install bazel first to get started.
TIM-VX needs to be compiled and linked against VeriSilicon OpenVX SDK which provides related header files and pre-compiled libraries. A default linux-x86_64 SDK is provided which contains the simulation environment on PC. Platform specific SDKs can be obtained from respective SoC vendors.
To build TIM-VX
bazel build libtim-vx.soTo run sample LeNet
# set VIVANTE_SDK_DIR for runtime compilation environment
export VIVANTE_SDK_DIR=`pwd`/prebuilt-sdk/x86_64_linux
bazel build //samples/lenet:lenet_asymu8_cc
bazel run //samples/lenet:lenet_asymu8_ccTo development for TIM-VX, you first need to get familiar with OpenVX API and OpenVX NN Extension API. Please head over to Khronos to read the spec.