"tf.Keras which is Keras integrated as part of the TensorFlow core API. Keras continues as an independent open source project." Source-2
Keras is now a part of Tensorflow, no choice, no question of choice between tf.Keras and Tensorflow.
'No need for “Keras with TensorFlow as the backend” because Keras is now part of TensorFlow. You can continue to use Theano and CNTK etc. as Keras backend if you wish.' - Source-2
|Tensorflow 2.0 architecture, functions libraries Source-2|
Tensorflow Low Level API
Tensorflow in Different Languages
Deploy to mobile Android, iOS, mobile web, Raspberry Pi,
Training on CPU GPU TPU
Is TF.keras and stand-alone Keras the same?
The short answers is no. Tensorflow team has focused more on TF.keras, not all changes are ported over to Keras, which will have its own advocate and interest group. It is safe to say TF.keras is now a different flavor of Keras. The syntax remains similar between the two. Also Keras contains other libraries and modules and that are not to be integrated into Tensorflow. [Source 1: #AskTensorflow Youtube]
Lazy Evaluation to Eager Execution
Tensorflow 1.0 tf.layers went away in Tensorflow 2.0.