Prepare data for distributed training

This article describes two methods for preparing data for distributed training: Petastorm and TFRecords.


You can also use TFRecord format as the data source for distributed deep learning. TFRecord format is a simple record-oriented binary format that many TensorFlow applications use for training data. is the TensorFlow dataset, which is comprised of records from TFRecords files. For more details about how to consume TFRecord data, see the TensorFlow guide Consuming TFRecord data.

The following articles describe and illustrate the recommended ways to save your data to TFRecord files and load TFRecord files: