Is the statement true or false: The graph and session mechanism has been removed from TensorFlow 2.0?

The statement is true. In TensorFlow 2.0, the eager execution mode is enabled by default, which simplifies the development process by allowing operations to be executed immediately as they are called from Python. This change means that the graph and session mechanisms that were prevalent in TensorFlow 1.x have been removed or rendered unnecessary for most tasks. In TensorFlow 1.x, users had to construct a computational graph and then use a session to run that graph, which added complexity and required users to manage the lifecycle of both the graph and the session.

With TensorFlow 2.0, the focus is on building models in a more intuitive and straightforward manner, allowing for a more Pythonic programming style. This shift enhances usability and makes it easier for developers to prototype and experiment with machine learning models quickly. Additionally, while there are still ways to use graph functionalities for specific purposes, such as performance optimization, the core design of TensorFlow 2.0 moves away from the explicit graph/session structure that characterized previous versions.