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Returns a random PS task for op placement.
tf.contrib.training.RandomStrategy( num_ps_tasks, seed=0 )
This may perform better than the default round-robin placement if you have a large number of variables. Depending on your architecture and number of parameter servers, round-robin can lead to situations where all of one type of variable is placed on a single PS task, which may lead to contention issues.
This strategy uses a hash function on the name of each op for deterministic placement.
__call__( op )
Chooses a ps task index for the given