TensorFlowOnSpark (homepage)

TensorFlowOnSpark brings TensorFlow programs onto Apache Spark clusters

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TensorFlowOnSpark enables distributed TensorFlow training and inference on Apache Spark clusters. It seeks to minimize the amount of code changes required to run existing TensorFlow programs on a shared grid. It supports all TensorFlow functionalities: synchronous/asynchronous training, model/data parallelism, server-to-server communications, inferencing and TensorBoard. TensorFlowOnSpark allows datasets on HDFS and other sources pushed by Spark or pulled by TensorFlow.

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This package doesn't have any releases published in the Spark Packages repo, or with maven coordinates supplied. You may have to build this package from source, or it may simply be a script. To use this Spark Package, please follow the instructions in the README.


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