class_docstr: Optimizer that implements the FTRL algorithm.
  
  This version has support for both online L2 (McMahan et al., 2013) and
  shrinkage-type L2, which is the addition of an L2 penalty
  to the loss function.
  
  References:
    Ad-click prediction:
      [McMahan et al., 2013](https://dl.acm.org/citation.cfm?id=2488200)
      ([pdf](https://dl.acm.org/ft_gateway.cfm?id=2488200&ftid=1388399&dwn=1&CFID=32233078&CFTOKEN=d60fe57a294c056a-CB75C374-F915-E7A6-1573FBBC7BF7D526))
code: def _create_slots(self, var_list):
      # Create the "accum" and "linear" slots.
      def _accum_initializer(
          shape, dtype=dtypes.float32, partition_info=None
      ):
          del partition_info
          return (
              array_ops.ones(shape=shape, dtype=dtype)
              * self._initial_accumulator_value
          )
  
      for v in var_list:
          self._get_or_make_slot_with_initializer(
              v,
              _accum_initializer,
              v.shape,
              v.dtype,
              "accum",
              self._accum_name or self._name,
          )
          self._zeros_slot(v, "linear", self._linear_name or self._name)
  
file_path: tensorflow/tensorflow/python/training/ftrl.py
imports: from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_training_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.training import optimizer
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling the FtrlOptimizer obj's underlying member method code with example usage: obj._create_slots(var_list) and returns: unknown