Class RandomStrategy
Defined in tensorflow/contrib/training/python/training/device_setter.py.
Returns a random PS task for op placement.
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.
__init__
__init__(
num_ps_tasks,
seed=0
)
Creates a new RandomStrategy.
Methods
tf.contrib.training.RandomStrategy.__call__
__call__(op)
Chooses a ps task index for the given Operation.