class_docstr: Abstract placement strategy for distributed training.
  
  Given a cluster of workers, the placement strategy determines which subgraph
  each worker constructs.
class_docstr_tok: ["Abstract","placement","strategy","for","distributed","training",".","Given","a","cluster","of","workers",",","the","placement","strategy","determines","which","subgraph","each","worker","constructs","."]
docstr: A context for assigning subnetwork ops to devices.
docstr_tok: ["A","context","for","assigning","subnetwork","ops","to","devices","."]
code: def subnetwork_devices(self, num_subnetworks, subnetwork_index):
      """A context for assigning subnetwork ops to devices."""
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import contextlib
  from absl import logging
  from adanet import tf_compat
  from adanet.distributed.devices import _OpNameHashStrategy
  import numpy
  import six
label_desc: Use image node_id 6 for calling the PlacementStrategy obj's underlying member method code with example usage: obj.subnetwork_devices(num_subnetworks, subnetwork_index) without return types