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Package Exports

  • @tensorflow/tfjs-node

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (@tensorflow/tfjs-node) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

TensorFlow backend for TensorFlow.js via Node.js

This repo is under active development and is not production-ready. We are actively developing as an open source project.

Installing

npm install @tensorflow/tfjs-node
(or)
yarn add @tensorflow/tfjs-node

Before executing any TensorFlow.js code, load and set the backend to 'tensorflow'.

import * as tf from '@tensorflow/tfjs';
import '@tensorflow/tfjs-node';

tf.setBackend('tensorflow');

Development

# Download and install JS dependencies, including libtensorflow 1.8.
yarn

# Run TFJS tests against Node.js backend:
yarn test

See the demo directory that trains MNIST using TensorFlow.js with the TensorFlow C backend.

cd demo/
yarn

# Run the training script. See demo/package.json for this script.
yarn mnist

The important line to note is at the top of mnist.ts, which sets the backend to TensorFlow.

Optional: Build libtensorflow From TensorFlow source

This requires installing bazel first.

bazel build //tensorflow/tools/lib_package:libtensorflow

Supported Platforms

  • Mac OS
  • Linux
  • Windows coming soon