This repo is a fork of the tflite-support repo, with the addition of the tflite_model_runner related code to show how it is built using bazel and emsdk.

1. Add emscripten toolchain to the WORKSPACE file. This will set up emsdk and provide a useful build rule wasm_cc_binary that can be used to build WASM module from a cc_binary (see below).
2. I also added a small patch for the com_google_glog library. Without it, the emscripten build will fail on Mac/Linux. The glog v0.5.0 release has a fix for this issue, but it requires some TFLite code refactoring. I will talk to the TFLite team about this. For now we will just use the patch.
3. The cpp code is here.
   • tflite_model_runner.* implement the model runner.
   • tflite_model_runner_wasm.cc sets up the WASM related bindings.
   • The BUILD file uses the wasm_cc_binary rule to build the WASM module. It is currently linking with XNNPACK, with WASM SIMD and multi-threading turned on.
4. The demo code is here. To run the demo:
   • Run yarn && yarn build in the demo directory. yarn build runs build.sh where you can see how the bazel build command is used and how to extract the output files.
   • Run yarn start to start the demo locally. It creates a model runner instance with the MobilenetV2 model and classfies an image. See the script.js file for details about how things are used from the JS side.
   • Since this build configuration is for SIMD+multi-threading, please make sure Chrome has these two features turned on from chrome://flags.
   • Run yarn run electron to start the demo in electron.js.
   • Run yarn run electron-packager to build an electron.js app of this demo.
5. The WebNN delegate support
   • tensorflow_lite_webnn_delegate.patch: the WebNN delegate implementation.
   • Add TFLiteWebModelRunnerOptions.enableWebNNDelegate to enable or disable WebNN delegate.
   • Demo in browser is using webnn-polyfill.
   • Demo in electron.js could use WebNN-native node.js binding for more details.