tractjs

App Listed Dormant

Run ONNX and TensorFlow inference in the browser.

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Stars
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Forks
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Contributors
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Commits
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Latest release

About

From the project README ·

Run ONNX and TensorFlow inference in the browser. A thin wrapper on top of tract.

The Open Neural Network Exchange is a format which many popular libraries like PyTorch, TensorFlow and MXNet can export to which allows tractjs to run neural networks from (almost) any library.

Website | API Docs

Why tractjs instead of ONNX.js?

There is currently one other usable ONNX runner for the browser, ONNX.js. There are a couple of things tractjs does better:

  • tractjs supports more operators:
    • LSTMs (even bidirectional) are supported while ONNX.js does not support any recurrent networks.
    • Some ONNX-ML models like decision tree classifiers are also supported.
  • tractjs is more convenient to use. It can build to a single file tractjs.min.js which contains the inlined WASM and WebWorker. The WASM backend of ONNX.js can not as easily be used without a build system.

There are however also some downsides to tractjs. See the FAQ.

Read the full README

Getting started

Without a bundler
<html>
  <head>
    <meta charset="utf-8" />
    <script src="https://unpkg.com/tractjs/dist/tractjs.min.js"></script>
    <script>
      tractjs.load("path/to/your/model").then((model) => {
        model
          .predict([new tractjs.Tensor(new Float32Array([1, 2, 3, 4]), [2, 2])])
          .then((preds) => {
            console.log(preds);
          });
      });
    </script>
  </head>
</html>
With a bundler
npm install tractjs
import * as tractjs from "tractjs";

tractjs.load("path/to/your/model").then((model) => {
  model
    .predict([new tractjs.Tensor(new Float32Array([1, 2, 3, 4]), [2, 2])])
    .then((preds) => {
      console.log(preds);
    });
});
With Node.js

tractjs now runs in Node.js! Models are fetched from the file system.

const tractjs = require("tractjs");

tractjs.load("./path/to/your/model").then((model) => {
  model
    .predict([new tractjs.Tensor(new Float32Array([1, 2, 3, 4]), [2, 2])])
    .then((preds) => {
      console.log(preds);
    });
});

FAQ

Why does my model with dynamic input dimensions not work?

Currently, tract requires has some restrictions on dynamic dimensions. If your model has a dynamic dimension, there's multiple solutions:

  1. Declare a dynamic dimension via an input fact. Input facts are a way to provide additional information about input type and shape that can not be inferred via the model data:
const model = await tractjs.load("path/to/your/model", {
  inputFacts: {
    0: ["float32", [1, "s", 224, 224]],
  },
});
  1. Set fixed input dimensions via input facts. This is of course not ideal because subsequently the model can only be passed inputs with this exact shape:
const model = await tractjs.load("path/to/your/model", {
  inputFacts: {
    // be careful with image model input facts! here I use ONNX's NCHW format
    // if you are using TF you will probably need to use NHWC (`[1, 224, 224, 3]`).
    0: ["float32", [1, 3, 224, 224]],
  },
});
  1. Turn optimize off. This is the nuclear option. It will turn off all optimizations relying on information about input shape. This will make sure your model work (even with multiple dynamic dimensions) but significantly impact performance:
const model = await tractjs.load("path/to/your/model", {
  optimize: false,
});
What about size?

At the time of writing, tractjs is very large for web standards (6.2MB raw, 2.1MB gzipped). This is due to tract being quite large, and due to some overhead from inlining the WASM. But it's not as bad as it sounds. You can load tractjs lazily along your demo, where you will likely have to load significantly large weights too.

If you are working on a very size-sensitive application, get in touch and we can work on decreasing the size. There are some more optimizations to be done (e. g. an option not to inline WASM, and removing panics from the build). There is also ongoing work in tract to decrease size.

What about WebGL / WebNN support?

tractjs are bindings to the tract Rust library which was originally not intended to be run on the web. WebGL / WebNN support would be great, but would require lots of web-specific changes in tract so it is currently not under consideration.

License

Apache 2.0/MIT

All original work licensed under either of

  • Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
  • MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT) at your option.
Contribution

Contributions are very welcome! See CONTRIBUTING.md.

License
Not measured
Crate facts
Not measured
  • Runs on, Native code and Python bindings read crates on crates.io. This entry lists no crate.

Compare with similar projects

Order: strongest tier first, then most downloads, then name, with unmeasured values last. A library counts downloads over 30 days. An app counts binary downloads per release. An app with none counts its crate downloads over 30 days. ML Rust runs this catalogue, so its closest project always gets a row.

tractjs beside the projects that share a topic with it
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Run ONNX and TensorFlow inference in the browser.

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126 downloads over 30 days 0 107 0.3.1 GPU support unknown No native code found MIT
Why ListedNo archive, New or Featured rule places it, so it is Listed.

What it lacks for Featured

What else the check found

  • The last activity is on 23 Jul 2021, 1935 days ago. That reaches the 365 days the rules expect, so the project is dormant. Dormancy rule

Not measured: Unpatched vulnerabilities past the grace window, First release.

Exact rules: Listed, Featured app. The check on applied thresholds version 9.

Every rule outcome, as the check records it
  • expected-interval: app: E = 365 days
  • dormancy: last activity 2021-07-23, 1935 days ago, E = 365: dormant
  • featured: not featured: dormant and not stable
  • listed: listed: no archive, new or featured rule applies

Measurements and sources

Each signal row shows the raw value, its source and the fetch date. The Sources list gathers every distinct source on this page. Movement needs more history.

Sources4 sources
Adoption0 binary downloads per release4 not measured
Adoption measurements
SignalValueSourceFetchedCounts
Active dependentsNot measuredYes
New dependents (365 days)Not measuredYes
Peak active dependentsNot measuredYes
Active dependents as a share of the peakNot measuredYes
Binary downloads per release0GitHub releasesYes
MaintenanceLatest human commit: 5 years ago7 not measured
Maintenance measurements
SignalValueSourceFetchedCounts
Latest human commit2021-07-23GitHub repositoryYes
Latest release2021-07-23GitHub releasesYes
First releaseNot measuredYes
Latest versionNot measuredYes
Days the oldest outside issue waits for a reply0GitHub repositoryYes
Maintainer replies over 365 days0GitHub repositoryYes
Repository archivedfalseGitHub repositoryYes
Repository gonefalseGitHub repositoryYes
Release commit or manifest in the repoNot measuredYes
Published docsNot measuredYes
Latest release fails cargo checkNot measuredYes
Build check dateNot measuredYes
Build check toolchainNot measuredYes
SecurityNot measured
Security measurements
SignalValueSourceFetchedCounts
Unpatched vulnerabilities past the grace windowNot measuredYes
RustSec unmaintained advisoryNot measuredYes
Deprecation noticeNot measuredYes
Deprecated requirementNot measuredYes
Distribution0 binary downloads over the last 3 releases10 not measured
Distribution measurements
SignalValueSourceFetchedCounts
ReleasesNot measuredYes
Downloads over 30 daysNot measuredYes
Binary downloads over the last 3 releases0GitHub releasesYes
Homebrew installs on request over 365 daysNot measuredYes
Repology repository familiesNot measuredYes
Docker pull growth over 90 daysNot measuredYes
Docker pulls at the growth baselineNot measuredYes
Every version a prereleaseNot measuredYes
Every version 0.0.xNot measuredYes
Every version yankedNot measuredYes
Crate deleted from crates.ioNot measuredYes
Repository76 stars, 6 forks, 2 contributors, 140 commits. Stars alone never qualify a project.1 not measured
Repository measurements
SignalValueSourceFetchedCounts
GitHub stars76GitHub repositoryYes — one part of the repository route
GitHub forks6GitHub repositoryYes — one part of the repository route
Contributors with a GitHub account2GitHub contributorsYes — one part of the repository route
Commits on the default branch140GitHub repositoryNo
Repository's main crate left out of the entryNot measuredYes
Facts that never count
Facts that never count measurements
SignalValueSourceFetchedCounts
LicenseNot measuredNo
Runs on, from listed crates and their direct dependenciesNot measuredNo
What shows each backendNot measuredNo
Native code, from listed crates and their dependenciesNot measuredNo
Python bindings, from direct dependencies of listed cratesNot measuredNo
Crates that depend on a listed crate directlyNot measuredNo

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