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fchollet's profile
François Chollet
François Chollet
François Chollet
Verified account
@fchollet

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François CholletVerified account

@fchollet

Deep learning @google. Creator of Keras. Author of 'Deep Learning with Python'. Opinions are my own.

United States
fchollet.com
Joined August 2009

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    François Chollet‏Verified account @fchollet 18 Aug 2020

    François Chollet Retweeted François Chollet

    In general, if you're not already training your models on TPU (at full utilization), you probably should. It's cheap and you will save a lot of time. TPU are fast.https://twitter.com/fchollet/status/1295829787164807168 …

    François Chollet added,

    François CholletVerified account @fchollet
    Tip: when running on TPU, you can significantly speed up your model by running *multiple steps of gradient descent in a single graph execution*. This helps get the device to 100% utilization (which, for a TPU, is huge). Just pass `experimental_steps_per_execution` to `compile`. pic.twitter.com/cwzk27z5Lo
    Show this thread
    2:14 PM - 18 Aug 2020
    • 13 Retweets
    • 92 Likes
    • Stephan Bisola Olasehinde Milad Aghajohari Swarup Ghosh Kevin Nelson Hesam Haddad ANIRUDHA AKELA el pepe heeiow
    2 replies 13 retweets 92 likes
      1. Hannes DM‏ @Hannes_Dm 18 Aug 2020
        Replying to @fchollet

        I don't because it's usually faster to run on GPU. However, I was unaware of this paramater. In which cases does changing the steps_per_execution actually help?

        0 replies 0 retweets 0 likes
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      1. Bisola Olasehinde‏ @BizzyVinci 21 Aug 2020
        Replying to @fchollet

        Hmm. Thanks for the insight

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