Scaling Tensorflow data processing with tf.data (TF Dev Summit '20)

As model training becomes more distributed in nature, tf.data has evolved to be more distribution aware and performant. This talk presents tf.data tools for scaling TensorFlow data processing. In particular: tf.data service that allows your tf.data pipeline to run on a cluster of machines, and tf.data.snapshot that materializes the results to disk for reuses across multiple invocations. Speaker: Rohan Jain - Staff Software Engineer Resources: GitHub Distributed tf.data service → https://goo.gle/2VrYDi2 tf.data: Build TensorFlow input pipelines → https://goo.gle/2VTnnjk Better performance with the tf.data API → https://goo.gle/38wyKAy GitHub tf.data snapshot → https://goo.gle/2v42Ai8 Watch all TensorFlow Dev Summit 2020 sessions → https://goo.gle/TFDS20 Subscribe to the TensorFlow YouTube channel → https://goo.gle/TensorFlow