TensorFlow backend for TensorFlow.js via Node.js

Installing

TensorFlow.js for Node currently supports the following platforms:
- Mac OS X CPU (10.12.6 Siera or higher)
- Linux CPU (Ubuntu 14.04 or higher)
- Linux GPU (Ubuntu 14.04 or higher and Cuda 9.0 w/ CUDNN v7) (see installation instructions)
- Windows CPU (Win 7 or higher)
- Windows GPU (Win 7 or higher and Cuda 9.0 w/ CUDNN v7) (see installation instructions)

Other Linux variants might also work but this project matches core TensorFlow installation requirements.

#### Installing CPU TensorFlow.js for Node:

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

#### Installing Linux/Windows GPU TensorFlow.js for Node:

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

#### Windows Requires Python 2.7

Windows build support for node-gyp requires Python 2.7. Be sure to have this version before installing @tensorflow/tfjs-node or @tensorflow/tfjs-node-gpu. Machines with Python 3.x will not install the bindings properly.

For more troubleshooting on Windows, check out WINDOWS_TROUBLESHOOTING.md.

#### Mac OS X Requires Xcode

If you do not have Xcode setup on your machine, please run the following commands:

`sh
$ xcode-select --install
`

After that operation completes, re-run yarn add or npm install for the @tensorflow/tfjs-node package.

You only need to include @tensorflow/tfjs-node or @tensorflow/tfjs-node-gpu in the package.json file, since those packages ship with @tensorflow/tfjs already.

Using the binding

Before executing any TensorFlow.js code, import the node package:

`js
// Load the binding
import * as tf from '@tensorflow/tfjs-node';

// Or if running with GPU:
import * as tf from '@tensorflow/tfjs-node-gpu';
`

Note: you do not need to add the @tensorflow/tfjs package to your dependencies or import it directly.

Development

`sh


Download and install JS dependencies, including libtensorflow 1.8.

yarn

Run TFJS tests against Node.js backend:

yarn test
`

`sh


Switch to GPU for local development:


yarn enable-gpu
`

MNIST demo for Node.js

See the tfjs-examples repository for training the MNIST dataset using the Node.js bindings.

$3

This requires installing bazel first.

`sh
bazel build --config=monolithic //tensorflow/tools/lib_package:libtensorflow
``