51 lines
2.3 KiB
Markdown
51 lines
2.3 KiB
Markdown
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# TIM-VX - Tensor Interface Module
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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.
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Main Features
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- 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
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- Simplified C++ binding API calls to create Tensors and Operations [Guide](https://github.com/VeriSilicon/TIM-VX/blob/main/docs/Programming_Guide.md)
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- Dynamic graph construction with support for shape inference and layout inference
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- Built-in custom layer extensions
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- A set of utility functions for debugging
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## Framework Support
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- [Tensorflow-Lite](https://github.com/VeriSilicon/tflite-vx-delegate) (External Delegate)
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- [Tengine](https://github.com/OAID/Tengine) (Official)
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- [TVM](https://github.com/VeriSilicon/tvm) (Fork)
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- MLIR Dialect (In development)
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Feel free to raise a github issue if you wish to add TIM-VX for other frameworks.
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## Get started
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### Build and Run
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TIM-VX supports both [bazel](https://bazel.build) and cmake. [Install bazel](https://docs.bazel.build/versions/master/install.html) to get started.
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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.
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To build TIM-VX
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```shell
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bazel build libtim-vx.so
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```
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To run sample LeNet
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```shell
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# set VIVANTE_SDK_DIR for runtime compilation environment
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export VIVANTE_SDK_DIR=`pwd`/prebuilt-sdk/x86_64_linux
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bazel build //samples/lenet:lenet_asymu8_cc
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bazel run //samples/lenet:lenet_asymu8_cc
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```
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To build and run Tensorflow-Lite with TIM-VX, please see [README](https://github.com/VeriSilicon/tflite-vx-delegate#readme)
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To build and run TVM with TIM-VX, please see [TVM README](https://github.com/VeriSilicon/tvm/blob/vsi_npu/README.VSI.md)
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# Support
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create issue on github or email to ML_Support@verisilicon.com
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