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