class_docstr: Internal class to create the op to initialize the clusters.
  
  The op performs this algorithm (see constructor args):
  
  num_remaining = num_clusters - length(cluster_centers)
  if num_remaining == 0:
    assert that cluster_centers_initialized is true
  else:
    assert that num_remaining > 0
    new_centers = choose up to num_remaining initial centers
    l2-normalize new_centers if using cosine distance
    all_centers = concat(cluster_centers, new_centers)
    cluster_centers := all_centers
    if there is a cluster_centers_updated variable:
      cluster_centers_updated := cluster_centers
    num_now_remaining = num_clusters - length(cluster_centers)
    if num_now_remaining == 0:
      cluster_centers_initialized := true
code: def _single_batch_sampler(self, sampler):
      # Enforce that there are at least as many data points as centers
      # remaining. This gives the provided sampler the chance to select all
      # remaining centers from a single batch.
      with ops.control_dependencies(
          [
              check_ops.assert_greater_equal(
                  self._num_data, self._num_remaining
              )
          ]
      ):
          return sampler()
  
imports: from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import random_seed
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import gen_clustering_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_impl
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import state_ops
  from tensorflow.python.ops import variable_v1
  from tensorflow.python.ops import while_loop
  from tensorflow.python.ops.embedding_ops import embedding_lookup
  from tensorflow.python.ops.gen_clustering_ops import *
label_desc: Use image node_id 6 for calling the _InitializeClustersOpFactory obj's underlying member method code with example usage: obj._single_batch_sampler(sampler) and returns: sampler