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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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    1. Evan Hennis‏ @TheNurl 10 Jan 2019

      @DynamicWebPaige I am testing the daily build of @TensorFlow 2.0 and it looks like tf.train.RMSPropOptimizer was removed. What is the best path to figure out where it went or why it was removed.

      1 reply 0 retweets 1 like
    2.  👩‍💻 Paige Bailey #BlackLivesMatter‏ @DynamicWebPaige 10 Jan 2019
      Replying to @TheNurl @TensorFlow

      I believe that tf.train.RMSPropOptimizer has been consolidated with tf.keras into tf.keras.optimizers.RMSprop - but will cc: @fchollet and @martin_wicke to keep me honest. 😊 📜 2.0 docs: https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/keras/optimizers/RMSprop …

      2 replies 1 retweet 1 like
    3. Andrew Mendez‏ @AndrewMendez19 10 Jan 2019
      Replying to @DynamicWebPaige @TheNurl and

      Is gradient clipping enabled to set in all tf.keras optimizers, or only RMSprop? I would like to implement WGAN using tf.keras optimizers and gradient clipping is needed.

      1 reply 0 retweets 0 likes
      François Chollet‏Verified account @fchollet 10 Jan 2019
      Replying to @AndrewMendez19 @DynamicWebPaige and

      Gradient clipping is available in all optimizers in 2.0.

      4:22 PM - 10 Jan 2019
      • 3 Likes
      • 👩‍💻 Paige Bailey #BlackLivesMatter Martin Wicke Mappu
      2 replies 0 retweets 3 likes
        1. Andrew Mendez‏ @AndrewMendez19 10 Jan 2019
          Replying to @fchollet @DynamicWebPaige and

          Heck Yes, I'll try it out!

          0 replies 0 retweets 2 likes
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        2. Andrew Mendez‏ @AndrewMendez19 11 Jan 2019
          Replying to @fchollet @DynamicWebPaige and

          What is the best way to apply clipping in 2.0? I checked the 2.0 documentation, and the optimizers do not have a parameter to set clip value to. What I am thinking is get the gradient, use the tf.keras.backend.clip(), then set the gradient values and backpropogate

          1 reply 0 retweets 1 like
        3. Andrew Mendez‏ @AndrewMendez19 11 Jan 2019
          Replying to @AndrewMendez19 @fchollet and

          Or does the tf.keras.optimizers implement the api functionality similar to keras, where clipnorm or clipvalue arguments can be used for all optimizers: https://keras.io/optimizers/  @martin_wicke

          1 reply 0 retweets 1 like
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