Understanding of version differences

Hi Tensorflow Experts,

I have been working on two codes, one in TF1, the other one in TF2. I did some research about the TensorFlow architecture the difference between these two, maybe you could check if my understanding is correct?

In version 1, graphs need to be created manually by the user. In version 2, the API has been made more user-friendly and the graph creation is now automated in Keras. Has Keras been created explicitly for TensorFlow 2, or does it exist independently from it?

The eager execution mode basically breaks the graph approach to create a more “classical” computation scheme. It is used per default in pure high-level TensorFlow, since here the computations have a smaller impact on performance. On the other hand, in Keras, eager mode is switched off and behaves more or less like TF1. Is this correct?

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