TensorFlow.js now has a WebAssembly backend

TensorFlow.js was developed by Google to let JavaScript developers dive into machine learning—and they don’t even need an advanced math degree to do so.

SEE ALSO: Web developers don’t need a math degree to get started with machine learning

The latest update to the open source machine learning library is a WebAssembly backend that was announced in a blog post. Let’s see what it can do!

The WebAssembly backend

WebAssembly (Wasm) is “a binary instruction format for a stack-based virtual machine” to serve as a portable target for compiling high-level languages on the web. It runs cross-browser and outside the browser.

The Wasm backend for TensorFlow.js offers support for the browser and Node.js and is designed to boost performance on lower-end mobile devices. After all, Wasm allows native decoding that is up to 20x faster than JavaScript can be parsed.

But be careful: In most cases, the previous WebGL backend will still outperform the Wasm backend. It can only be faster for ultra-lite models such as FaceMesh, which is designed “to infer the approximate surface geometry of a human face” and runs on WebAssembly:

Source.

As the WebGL backend is still in use as well, TensorFlow.js will define a priority for each backend and automatically choose which one to use in a specific environment. The TensorFlow team believes the Wasm backend will become increasingly popular as ultra-light models for edge devices are on the rise.

SEE ALSO: Introduction to machine learning in Node.js

You can install the WebAssembly backend either via npm or with script tags.

Head over to the TensorFlow Blog for further details.