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VeriSilicon Tensor Interface Module
| Date | Stars |
|---|---|
| 2026-07-30 | 259 |
| 2026-08-10 | 260 |
| 2026-08-18 | 261 |
| 2026-09-06 | 262 |
| 2026-10-09 | 262 |
| 2026-10-13 | 263 |
| 2026-11-03 | 264 |
| 2026-11-04 | 263 |
Today
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# TIM-VX - Tensor Interface Module
[](https://github.com/VeriSilicon/TIM-VX/actions/workflows/bazel_x86_vsim_unit_test.yml)
[](https://github.com/VeriSilicon/TIM-VX/actions/workflows/cmake_x86_vsim.yml)
- [TIM-VX - Tensor Interface Module](#tim-vx---tensor-interface-module)
- [Framework Support](#framework-support)
- [Architecture Overview](#architecture-overview)
- [Technical documents](#technical-documents)
- [Get started](#get-started)
- [Build and Run](#build-and-run)
- [cmake](#cmake)
- [Build with local google test source](#build-with-local-google-test-source)
- [Build for evk-boards](#build-for-evk-boards)
- [Important notice for integration](#important-notice-for-integration)
- [Bazel](#bazel)
- [Other](#other)
- [Reference board](#reference-board)
- [Support](#support)
TIM-VX is a software integration module provided by VeriSilicon to facilitate deployment of Neural-Networks on Verisilicon ML accelerators. It serves as the backend binding for runtime frameworks such as Android NN, Tensorflow-Lite, MLIR, TVM and more.
Main Features
- Over [150 operators](https://github.com/VeriSilicon/TIM-VX/blob/main/src/tim/vx/ops/README.md) with rich format support for both quantized and floating point
- Simplified C++ binding API calls to create Tensors and Operations [Guide](https://github.com/VeriSilicon/TIM-VX/blob/main/docs/Programming_Guide.md)
- Dynamic graph construction with support for shape inference and layout inference
- Built-in custom layer extensions
- A set of utility functions for debugging
## Framework Support
- [Tensorflow-Lite](https://github.com/VeriSilicon/tflite-vx-delegate) (External Delegate)
- [Tengine](https://github.com/OAID/Tengine) (Official)
- [TVM](https://github.com/VeriSilicon/tvm) (Fork)
- [Paddle-Lite](https://github.com/PaddlePaddle/Paddle-Lite) (Official)
- [OpenCV](https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU) (Offical)
- [ONNXRuntime](https://github.com/microsoft/onnxruntime/tree/main/onnxruntime/core/providers/vsinpu) (Official)
Feel free to raise a github issue if you wish to add TIM-VX for other frameworks.
## Architecture Overview
## Technical documents
* [Add customized operator](docs/customized_op.md)
# Get started
## Build and Run
TIM-VX supports both [bazel](https://bazel.build) and [cmake](https://cmake.org).
----
### cmake
To build TIM-VX for x86 with prebuilt:
```shell
mkdir host_build
cd host_build
cmake ..
make -j8
make install
```
All install files (both headers and *.so) is located in : `host_build/install`
cmake options:
| option name | Summary | Default |
| ----- | ----- | ----- |
|`TIM_VX_ENABLE_TEST`| Enable unit test case for public APIs and ops | OFF |
|`TIM_VX_ENABLE_LAYOUT_INFER`| Build with tensor data layout inference support| ON |
|`TIM_VX_USE_EXTERNAL_OVXLIB`| Replace internal with a prebuilt libovxlib library | OFF |
|`OVXLIB_LIB`|full path to libovxlib.so include so name, required if `TIM_VX_USE_EXTERNAL_OVXLIB`=ON | Not set |
|`OVXLIB_INC`|ovxlib's include path, required if `TIM_VX_USE_EXTERNAL_OVXLIB`=ON| Not set |
|`EXTERNAL_VIV_SDK`| Give external vivante openvx driver libraries | Not set|
|`TIM_VX_BUILD_EXAMPLES`| Build example applications | OFF |
|`TIM_VX_ENABLE_40BIT` | Enable large memory (over 4G) support in NPU driver | OFF |
|`TIM_VX_ENABLE_PLATFORM` | Enable multi devices support | OFF |
|`TIM_VX_ENABLE_PLATFORM_LITE` | Enable lite multi-device support, only work when `TIM_VX_ENABLE_PLATFORM`=ON | OFF |
|`VIP_LITE_SDK` | full path to VIPLite sdk, required when `TIM_VX_ENABLE_PLATFORM_LITE`=ON | Not set |
|`TIM_VX_ENABLE_GRPC` | Enable gPRC support, only work when `TIM_VX_ENABLE_PLATFORM`=ON | Excerpt of 7,791 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:09213046c6a0e391, topic:deep-learning, topic:neural-network, topic:tensorflow