class_docstr: All-reduce cross device ops using collective ops.
  
  In the between-graph replicated training, it will still do all-reduces across
  all workers and then put results on the right destinations.
class_docstr_tok: ["All-reduce","cross","device","ops","using","collective","ops",".","In","the","between-graph","replicated","training",",","it","will","still","do","all-reduces","across","all","workers","and","then","put","results","on","the","right","destinations","."]
code: def _num_between_graph_workers(self):
      return self._num_workers
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import enum
  import six
  from tensorflow.python.client import device_lib
  from tensorflow.python.distribute import cross_device_utils
  from tensorflow.python.distribute import device_util
  from tensorflow.python.distribute import reduce_util
  from tensorflow.python.distribute import values
  from tensorflow.python.eager import context
  from tensorflow.python.framework import kernels
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util.tf_export import tf_export
  from tensorflow.tools.docs import doc_controls
  import tensorflow
  from tensorflow.python.distribute.cross_device_ops import CollectiveAllReduce
  import tensorflow.python.distribute.cross_device_ops
  from byteps.tensorflow.ops import broadcast, _push_pull
  from byteps.tensorflow import local_rank, size
label_desc: Use image node_id 2 for calling the MyCollectiveAllReduce obj's underlying member method code with example usage: obj._num_between_graph_workers() and returns: self