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RELEASE.md
* Adds support for a new "distributed_epoch" processing mode. This processing mode distributes a dataset across all tf.data workers, instead of having each worker process the full dataset. See [the tf.data service docs](https://www.tensorflow.org/api_docs/python/tf/data/experimental/service#understand_processing_mode) to learn more.
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CITATION.cff
that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor Processing Units (TPUs). This architecture gives flexibility to the application developer, whereas in previous “parameter server” designs the management of shared state is built into the system, TensorFlow enables developers to experiment with novel optimizations...
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