How does TensorFlow handle race conditions in data input pipelines?

Race conditions occur when multiple threads modify shared input state without synchronization.

In tf.data pipelines, parallel mapping and prefetching improve performance but can introduce race conditions if mutable state is shared across transformations. TensorFlow avoids this by encouraging functional transformations and immutable datasets, but custom Python operations can still introduce bugs.