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Version: 0.1

Add Package to Existing App

In this tutorial, you will learn how to add the PyTorch Live core package to an existing React Native project.

If you have an existing React Native project and you want to add ML capabilities, you can add the react-native-pytorch-core package. This package includes all code needed to run ML inference, the Canvas, Camera, and the ImageUtils.


yarn add react-native-pytorch-core

On iOS you are done, but Android requires the following additional steps for the react-native-pytorch-core package to work.

Additional Assets for Metro

If the PyTorch Mobile models are part of the React Native bundle, the Metro configuration needs to be changed to resolve the ptl files.


This is only required if models are loaded from the bundle using require('./path/to/model.ptl'). It is not required if models are loaded from the local file system or via a URL.

// get defaults assetExts array
const defaultAssetExts = require('metro-config/src/defaults/defaults')

module.exports = {
// ...

resolver: {
assetExts: [...defaultAssetExts, 'ptl'],

// ...

Additional steps on Android

For the react-native-pytorch-core React Native package to work on Android, it requires three changes to the and the two build.gradle files to increase JVM memory, add Sonatype repository, and packaging options with pick first rule.

Increase JVM Memory

Increase the memory for the JVM to avoid OutOfMemory exceptions during the packaging process.


Without the increased memory, the packaging process might fail with the following error:

* What went wrong:
Execution failed for task ':app:packageDebug'.
> A failure occurred while executing$IncrementalSplitterRunnable
> java.lang.OutOfMemoryError (no error message)

Sonatype Repository

The PyTorch Mobile for Android dependencies are in the Sonatype repository. Add the repository url to the allprojects > repositories.

allprojects {
repositories {
// ...

maven {

// ...

Packaging Options

Add pickFirst rule to packagingOptions. This is required because both React Native and PyTorch Mobile for Android use fbjni. This rule will pick the first shared object (dynamic) library.


The comment for the packagingOptions shows the error that will show if pickFirst is not set.

android {
// ...

* Without the packaging options, it will result in the following build error:
* * What went wrong:
* Execution failed for task ':app:mergeDebugNativeLibs'.
* > A failure occurred while executing$ActionFacade
* > More than one file was found with OS independent path 'lib/x86/'
packagingOptions {
pickFirst '**/*.so'

// ...

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