|TensorFlow 1 version||View source on GitHub|
Example is a mostly-normalized data format for storing data for training and inference.
Compat aliases for migration
See Migration guide for more details.
Used in the notebooks
|Used in the guide||Used in the tutorials|
It contains a key-value store
features where each key (string) maps to a
tf.train.Feature message. This flexible and compact format allows the
storage of large amounts of typed data, but requires that the data shape
and use be determined by the configuration files and parsers that are used to
read and write this format.
Examples are read in row-major
format, so any configuration that describes data with rank-2 or above
should keep this in mind. For example, to store an
M x N matrix of bytes,
tf.train.BytesList must contain M*N bytes, with
M rows of