class_docstr: Creates the graph for k-means clustering.
class_docstr_tok: ["Creates","the","graph","for","k-means","clustering","."]
docstr: Normalized the input data.
docstr_tok: ["Normalized","the","input","data","."]
code: def _l2_normalize_data(cls, inputs):
      """Normalized the input data."""
      output = []
      for inp in inputs:
          with ops.colocate_with(inp, ignore_existing=True):
              output.append(nn_impl.l2_normalize(inp, dim=1))
      return output
  
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 8 for calling the KMeans obj's underlying member method code with example usage: obj._l2_normalize_data(cls, inputs) and returns: output