Tensorflow Decision Forests support for Tensorflow.js

This package enables users to run arbitrary Tensorflow Decision Forests models
on the web that are converted using tfjs-converter.
Users can load a TFDF model from a URL, use TFJS tensors to set
the model's input data, run inference, and get the output back in TFJS tensors.
Under the hood, the TFDF C++ runtime is packaged in a set of WASM modules.

Usage

Import the packages

To use this package, you will need a TFJS backend installed.
You will also need to import @tensorflow/tfjs-core for
manipulating tensors, and @tensorflow/tfjs-converter for loading models.

$3

``js
// Import @tensorflow/tfjs-core
import * as tf from '@tensorflow/tfjs-core';
// Adds the CPU backend.
import '@tensorflow/tfjs-backend-cpu';
// Import @tensorflow/tfjs-converter
import * as tf from '@tensorflow/tfjs-converter';
// Import @tensorflow/tfjs-tfdf.
import * as tfdf from '@tensorflow/tfjs-tfdf';
`

$3

`html








`

Set WASM modules location (optional)

By default, it will try to load the WASM modules from the same location where
the package or your own script is served. Use setLocateFile to set your own
location. See src/tfdf_web_api_client.d.ts for more details.

`js
// base is the URL to the main javascript file's directory.
// To return the default URL of the file use ${base}${path}.
tfdf.setLocateFile((path, base) => {
return https://your-server/.../${path};
});
`

Load a TFDF model


`js
const tfdfModel = await tfdf.loadTFDFModel('url/to/your/model.json');
`

Run inference

`js
// Prepare input tensors.
const input = tf.tensor1d(['test', 'strings']);

// Run inference and get output tensors.
const outputTensor = await tfdfModel.executeAsync(input);
console.log(outputTensor.dataSync());
`

Development

Building

`sh
$ yarn
$ yarn build
`

Testing

`sh
$ yarn test
`

Deployment


`sh
$ yarn build-npm
``