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In general, the TF team is quite large, with over 100 people (I think?), and none of them report to me. My scope is very narrow: looking at API changes within tf.keras, reviewing tf.keras code. That's really it.
One last misconception I see is that Keras is a TensorFlow wrapper library. In fact, Keras is an API standard for defining & training deep learning models, similar to what Gluon is to MXNet. Like Gluon, it's meant not to be tied to a specific implementation.
Keras has implementations in TensorFlow, MXNet, TypeScript, JavaScript, CNTK, Theano, PlaidML, Scala, CoreML, and others I think? But I have only been involved with tf.keras and the TensorFlow/Theano implementation.
Again, my scope when it comes to TensorFlow & Keras is very narrow. I’m just doing code review, looking at the tf.keras API. Sometimes I code. I do very little compared to everyone else, and hopefully I'll do even less in the future. I don’t enjoy the harassment on social media.
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