The following is stated in the eager execution official documentation (https://www.tensorflow.org/guide/eager):
TensorFlow's eager execution is an imperative programming environment that evaluates operations immediately, without building graphs: operations return concrete values instead of constructing a computational graph to run later. This makes it easy to get started with TensorFlow and debug models, and it reduces boilerplate as well. To follow along with this guide, run the following code samples in an interactive Python interpreter.
Eager execution is a flexible machine learning platform for research and experimentation, providing the following:
- An intuitive interface: Structure your code naturally and use Python data structures. Quickly iterate on small models and small data.
- Easier debugging: Call ops directly to inspect running...
