@tensorflow/tfjs-backend-webgl

Usage

This package implements a GPU accelerated WebGL backend for TensorFlow.js.

Importing the backend

Note: this backend is included by default in @tensorflow/tfjs.

Via NPM

// Import @tensorflow/tfjs-core
import * as tf from '@tensorflow/tfjs-core';
// Adds the WebGL backend to the global backend registry.
import '@tensorflow/tfjs-backend-webgl';

Via a script tag

<!-- Import @tensorflow/tfjs-core -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-core"></script>

<!-- Adds the WebGL backend to the global backend registry -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-webgl"></script>

You can also get ES2017 code using the following links

<!-- Import @tensorflow/tfjs-core -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-core@2.0.0-rc.4/dist/tf-core.es2017.js"></script>

<!-- Adds the WebGL backend to the global backend registry -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-webgl@2.0.0-rc.4/dist/tf-backend-webgl.es2017.js"></script>

Similar packages

Other packages similar to @tensorflow/tfjs-backend-webgl

@tensorflow/tfjs-backend-cpu

@tensorflow/tfjs-backend-cpu is a CPU-based backend for TensorFlow.js. It is generally slower than the WebGL backend but can be used in environments where WebGL is not available or desired.

@tensorflow/tfjs-node

@tensorflow/tfjs-node is a Node.js backend for TensorFlow.js, providing high-performance machine learning computations on the server-side. It leverages the TensorFlow C library for accelerated performance.

gpu.js

gpu.js is a JavaScript library for GPU-accelerated computations. While it is not specifically designed for machine learning, it can be used to perform general-purpose computations on the GPU, similar to the WebGL backend of TensorFlow.js.