Simplified distributed training with tf.distribute parameter servers

Learn about a new tf.distribute strategy, ParameterServerStrategy, which enables asynchronous distributed training in TensorFlow, along with its usage with Keras APIs and custom training loop. If you have models with large embeddings or an environment with preemptible machines, this approach lets you scale your training much more easily with minimum code changes. Resources: Distributed training with TensorFlow → https://goo.gle/3bli9n6 Parameter server training → https://goo.gle/2Zz3UrW Speaker: Yuefeng Zhou (Software Engineer) Watch all Google's Machine Learning Virtual Community Day sessions → https://goo.gle/mlcommunityday-all Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #MLCommunityDay product: TensorFlow - General; event: ML Community Day 2021; fullname: Yuefeng Zhou; re_ty: Publish;