add TFParallel.run() API #473
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... to simplify parallel execution use-cases, which now mirrors the
TFCluster.runAPI and map_fn signatures. This sets up the Spark executor environment for tensorflow execution (including GPU allocation), without setting up a TensorFlow cluster (via TF_CONFIG and/or cluster_spec). This does carry some basic knowledge about the rest of the executors/nodes (for data sharding) in theTFNodeContext. This API is an optional helper (specifically for GPU allocation). For CPU use-cases, users can still manually craft their own parallelRDD.mapPartitions()implementations as before.I confirm that this contribution is made under the terms of the license found in the root directory of this repository's source tree and that I have the authority necessary to make this contribution on behalf of its copyright owner.