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Announcing TensorFlow Lite

Tuesday, November 14, 2017
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Labels: TensorFlow , TensorFlow Lite , TFLite

16 comments :

  1. Eric MillerNovember 14, 2017 at 3:32 PM

    Thank you! re: "solution for mobile and embedded devices", can we expect to see early support for rpi & piZero-w? The process for getting TF on a piZero right now is pretty painful. Many of us who are using TF on rpis for research in the self driving car space would *really* make good use of TF on a pi zero-w due to the cost difference and wifi support .

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  2. nihuiNovember 14, 2017 at 4:43 PM

    Thank you! How about the inference speed compared to other mobile DL framework such as https://github.com/Tencent/ncnn ?

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  3. MastaramNovember 14, 2017 at 8:32 PM

    awesome idea thanks for this new soft.. https://mastaram.net what do you think

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  4. offbyeNovember 14, 2017 at 10:40 PM

    awesome !!!

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  5. Raflik-BlogNovember 14, 2017 at 11:54 PM

    Good news. Thank you.
    I got two questions.
    1. Is it possible to retrain the model using Tensorflow Lite direct on the Android device?
    2. Are you planning to support Tensorflow Lite on Raspberry Pi 3?

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    1. UnknownNovember 15, 2017 at 9:49 AM

      1. It is not yet possible to do training with TensorFlow lite on-device. That is an obvious avenue of future work that we are excited about.

      2. It should be pretty easy to build TensorFlow Lite on Raspberry PI. We plan to make sure this path works seamlessly soon, but for the initial release we have tested tflite on Android and iOS.

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    2. UnknownNovember 15, 2017 at 9:49 AM

      This comment has been removed by the author.

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  6. koxaxotiNovember 15, 2017 at 2:55 AM

    rfjhk,j

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  7. koxaxotiNovember 15, 2017 at 2:56 AM

    yuj;lo':/

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  8. koxaxotiNovember 15, 2017 at 2:56 AM

    www.sendcash9.com

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  9. koxaxotiNovember 15, 2017 at 2:57 AM

    i͓̽ q͓̽u͓̽i͓̽t͓̽ w͓̽o͓̽r͓̽k͓̽i͓̽n͓̽g͓̽ a͓̽t͓̽ s͓̽h͓̽o͓̽p͓̽r͓̽i͓̽t͓̽e͓̽ a͓̽n͓̽d͓̽ n͓̽o͓̽w͓̽ i͓̽ m͓̽a͓̽k͓̽e͓̽ $35h͓̽ - $80h͓̽...h͓̽o͓̽w͓̽? i͓̽'m͓̽ w͓̽o͓̽r͓̽k͓̽i͓̽n͓̽g͓̽ o͓̽n͓̽l͓̽i͓̽n͓̽e͓̽! m͓̽y͓̽ w͓̽o͓̽r͓̽k͓̽ d͓̽i͓̽d͓̽n͓̽'t͓̽ e͓̽x͓̽a͓̽c͓̽t͓̽l͓̽y͓̽ ★★ www.sendcash9.com 。

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  10. Ahmed Fawzy GadNovember 15, 2017 at 4:10 AM

    Wonderful

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  11. UnknownNovember 15, 2017 at 6:30 PM

    Good Job!

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  12. UnknownNovember 16, 2017 at 2:43 PM

    For TF-integrated solutions that run on mobile and desktop platforms, would you recommend migrating to TensorFlow Lite across all platforms, or is there a benefit to using TensorFlow Lite on mobile and "regular" TensorFlow on desktop?

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  13. Samuel GwokudaNovember 17, 2017 at 10:42 PM

    awesome. can't wait to start using the APIs

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  14. LBNovember 19, 2017 at 2:43 PM

    Can anyone please show an example of how to use this API on Android?
    Maybe, take a simple tick-tack-toe game, to show how it learns what to do

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