CODEWITHSUNDEEP
tensorflowgradlebazelaartensorflow-lite
Aviram Fireberger
Aviram Fireberger

Reputation: 4168

Can TensorFlow lite can be build with custom CPU?

I'm looking the TF Lite Android App

Which can be found on GIT: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/java/demo

How can I compile the tensorflow lite framework to use the optimized "atom" cpu type?

Is it possible to compile it on a MAC os with the CPU optimizations for the "atom" cpu?

I want to run the app on an Android device (SDK 22) with an "Intel Atom" Processor. When I run the application without any changes through Android Studio the rate was about 1200ms per frame. Compering the same APK installed on my Galaxy S9 (arm - snapdragon processor) was about 30ms per frame.

In the "build.gradle" there is this section:

dependencies {
...    
compile 'org.tensorflow:tensorflow-lite:0.0.0-nightly'

...
}

So it's seems that it's downloading the framework,

How can I compile it locally with the CPU optimization and set the app to use it instead of downloading the non optimized nightly version?

I tried to run this tutorial : Installing TensorFlow from Sources with the cpu flags but not sure exactly how it's helping me with the Android scenario..

Upvotes: 1

Views: 1257

Answers (1)

Jin
Jin

Reputation: 13473

Assuming that your Atom device is x86, use the --fat_apk_cpu flag to specify the x86 ABI:

$ bazel build -c opt --cxxopt='--std=c++11' \ 
    --fat_apk_cpu=x86 \
    //tensorflow/contrib/lite/java/demo/app/src/main:TfLiteCameraDemo

Switch x86 with x86_64 if you're building for a 64-bit device.

The built APK, available at bazel-bin/tensorflow/contrib/lite/java/demo/app/src/main/TfLiteCameraDemo.apk, will contain the x86 .so file:

$ zipinfo bazel-bin/tensorflow/contrib/lite/java/demo/app/src/main/TfLiteCameraDemo.apk | grep lib
-rw----     2.0 fat  1434712 b- defN 80-Jan-01 00:00 lib/x86/libtensorflowlite_jni.so

If your device is connected, you can use bazel mobile-install instead of bazel build to directly install the app:

$ bazel mobile-install -c opt --cxxopt='--std=c++11' \ 
  --fat_apk_cpu=x86 \ 
  --start_app \
  //tensorflow/contrib/lite/java/demo/app/src/main:TfLiteCameraDemo

Upvotes: 3

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