WasmEdge Tools for Tensorflow Extension (WILL BE DEPRECATED SOON)

The WasmEdge extension will be deprecated soon and be replaced by the WasmEdge-Image plug-in, WasmEdge-Tensorflow plug-in, and WasmEdge-TensorflowLite plug-in.

The WasmEdge is a high performance WebAssembly runtime optimized for server side applications. This project provides WasmEdge tools accessing with Tensorflow C library.

Getting Started

Install the WasmEdge-Tensorflow-Tools and dependencies

wget -qO- https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/install.sh | bash -s -- -e all -v 0.12.1

Example

We provide a simple tool for showing the tensors information of TensorFlow-Lite models. Take the bird v1 tflite model for example.

./show-tflite-tensor lite-model_aiy_vision_classifier_birds_V1_3.tflite

The output will be as following:

Input tensor nums: 1
    Input tensor name: module/hub_input/images_uint8
        dimensions: [1 , 224 , 224 , 3]
        data type: UInt8
        tensor byte size: 150528
Output tensor nums: 1
    Output tensor name: module/prediction
        dimensions: [1 , 965]
        data type: UInt8
        tensor byte size: 965

Build

Get Source Code

git clone https://github.com/second-state/WasmEdge-tensorflow-tools.git
cd WasmEdge-tensorflow-tools
git checkout 0.12.1

Check Dependencies

WasmEdge will try to use the latest LLVM release to create our nightly build. If you want to build from source, you may need to install these dependencies by yourself or using our docker images which provides several Linux distribution support.

GCC 11.1.0 (>= 9.4.0)

Prepare the Environment

Option 1: Use Docker Images

Repository on dockerhub wasmedge/wasmedge

You can use the following commands to get our latest docker image:

docker pull wasmedge/wasmedge # Equals to wasmedge/wasmedge:latest

The followings are available tags of docker images to build and run WasmEdge-Tensorflow-Tools:

tag name	arch	based operating system	LLVM version	ENVs	compatibility	comments
`latest`	x86_64	Ubuntu 20.04 LTS	12.0.0	CC=clang, CXX=clang++	Ubuntu 20.04+	This is for CI, will always use the latest Ubuntu release
`ubuntu-build-gcc`	x86_64	Ubuntu 20.04 LTS	12.0.0	CC=gcc, CXX=g++	Ubuntu 20.04+	This is for CI, will always use the latest Ubuntu release
`ubuntu-build-clang`	x86_64	Ubuntu 20.04 LTS	12.0.0	CC=clang, CXX=clang++	Ubuntu 20.04+	This is for CI, will always use the latest Ubuntu release
`manylinux2014_x86_64`	x86_64	CentOS 7, 7.9.2009	12.0.0	CC=gcc, CXX=g++	Ubuntu 16.04+, CentOS 7+	This is for developers who familiar with CentOS on x86_64 architecture

Option 2: Install dependencies on Ubuntu 20.04 manually

# Tools and libraries
sudo apt install -y \
    software-properties-common \
    cmake \
    libboost-all-dev

# WasmEdge supports both clang++ and g++ compilers
# You can choose one of them for building this project
# If you prefer GCC
sudo apt install -y gcc g++
# Else you can choose clang
sudo apt install -y clang-12

Build WasmEdge-Tensorflow-Tools

WasmEdge-Tensorflow-Tools depends on WasmEdge-core, WasmEdge-image, and WasmEdge-tensorflow. You have to prepare the WasmEdge-core, WasmEdge-image, and the WasmEdge-tensorflow before you build WasmEdge-Tensorflow-Tools. We provides two options for setting up the WasmEdge-core:

Create and Enter the Build Folder

# After pulling our WasmEdge docker image
docker run -it --rm \
    -v <path/to/your/WasmEdge-tensorflow/source/folder>:/root/WasmEdge-tensorflow-tools \
    wasmedge/wasmedge:latest
# In docker
cd /root/WasmEdge-tensorflow-tools
mkdir -p build && cd build

Option 1. Use built-in CMakeLists to get WasmEdge-Core, WasmEdge-image, and WasmEdge-tensorflow (Recommended)

# In docker
cmake -DCMAKE_BUILD_TYPE=Release .. && make

Option 2. Use specific version of WasmEdge-Core by giving WASMEDGE_CORE_PATH

You can also specify the WasmEdge-image by assigning WASMEDGE_IMAGE_PATH, and the WasmEdge-tensorflow by assigning WASMEDGE_TENSORFLOW_PATH. The dependencies not assigned will be fetched with the default versions automatically.

# In docker
cmake \
    -DWASMEDGE_CORE_PATH=<path/to/WasmEdge/source> \
    -DWASMEDGE_IMAGE_PATH=<path/to/WasmEdge-image/source> \
    -DWASMEDGE_TENSORFLOW_PATH=<path/to/WasmEdge-tensorflow/source> \
    -DCMAKE_BUILD_TYPE=Release .. && make

The executable build/tools/wasmedge-tensorflow is the runner for executing WASM or compiled WASM. The executable build/tools/wasmedge-tensorflow-lite is the runner for executing WASM or compiled WASM with only TensorFlow-lite host functions supported.

second-state / WasmEdge-tensorflow-tools

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