Boosting TensorFlow Performance Without Losing Flexibility

This in-depth guide explains how to effectively use tf.function in TensorFlow 2 to convert Python code into performant, portable dataflow graphs. You’ll learn the differences between eager execution and graph mode, the rules of tracing, how to control retracing, and best practices like using input_signature, avoiding Python side effects, and leveraging reduce_retracing. With practical examples and performance insights, th