An multi-worker tf.distribute strategy with parameter servers.

Inherits From: Strategy

Used in the notebooks

Used in the guide Used in the tutorials

Parameter server training is a common data-parallel method to scale up a machine learning model on multiple machines. A parameter server training cluster consists of workers and parameter servers. Variables are created on parameter servers and they are read and updated by workers in each step. By