TensorFlowOnSpark brings TensorFlow programs onto Apache Spark clusters
@yahoo / (0)
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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