Hi TensorFlow Lite users,
Earlier this year we announced a new Google Play Services API for TensorFlow Lite on Android in Beta. This API supported CPU, XNNPack and NNAPI, but GPU delegate wasn’t supported.
We’re happy to announce that it now supports the GPU delegate. This means you can now execute your models on GPU without having to bundle GPU libraries to your app. We expect savings up to 5MB in APK size by migrating to TensorFlow Lite in Play Services, if you were using the bundled TFLite and GPU delegate on Android. Most migrations are straightforward. If you’re interested, go to the TFLite documentation to learn how to migrate.
TFLite in Google Play Services is already being used by many first party Google apps as well as apps by external developers. It is serving a significant volume of users in production at Google scale.
The Android ML team is also accepting applications for early access to the Acceleration Service for Android, a set of API to enable you to select the optimal hardware accelerator available on-device. Read more about it here.
Thomas on behalf of the TensorFlow Lite and Android ML Platform teams.