This is an end-to-end example of recommendation application built with TensorFlow 2.0, and the model is trained based on the public MovieLens dataset. The dataset and model is used for research purpose. This demo is supposed to be a reference architecture to demonstrate how to build and run on-device recommendation model without in TF Lite talking to a server.
These instructions walk you through running the demo on an Android device.
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If you don't have already, install Android Studio, following the instructions on the website.
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Android Studio 3.2 or later.
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You need an Android device or Android emulator and Android development environment with minimum API 15.
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Open Android Studio, and from the Welcome screen, select
Open an existing Android Studio project. -
From the Open File or Project window that appears, navigate to and select the
recommendation/androiddirectory from wherever you cloned the TensorFlow Lite sample GitHub repo. -
You may also need to install various platforms and tools according to error messages.
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If it asks you to use Instant Run, click Proceed Without Instant Run.
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You need to have an Android device plugged in with developer options enabled at this point. See here for more details on setting up developer devices.
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If you already have Android emulator installed in Android Studio, select a virtual device with minimum API 15.
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Click
Runto run the demo app on your Android device.
- Use the following command to build a demo apk:
cd lite/examples/recommendation/android # Folder for Android app.
./gradlew build
- Use the following command to install the apk onto your connected device:
adb install -t app/build/outputs/apk/debug/app-debug.apk