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 _prepare(self):
      self._learning_rate_tensor = ops.convert_to_tensor(
          self._learning_rate, name="learning_rate"
      )
      self._l1_regularization_strength_tensor = ops.convert_to_tensor(
          self._l1_regularization_strength,
          name="l1_regularization_strength",
      )
      # L2 regularization strength with beta added in so that the underlying
      # TensorFlow ops do not need to include that parameter.
      self._adjusted_l2_regularization_strength_tensor = (
          ops.convert_to_tensor(
              self._l2_regularization_strength
              + self._beta
              / (2.0 * math_ops.maximum(self._learning_rate, 1e-36)),
              name="adjusted_l2_regularization_strength",
          )
      )
      assert (
          self._adjusted_l2_regularization_strength_tensor is not None
      )
      self._beta_tensor = ops.convert_to_tensor(self._beta, name="beta")
      self._l2_shrinkage_regularization_strength_tensor = (
          ops.convert_to_tensor(
              self._l2_shrinkage_regularization_strength,
              name="l2_shrinkage_regularization_strength",
          )
      )
      self._learning_rate_power_tensor = ops.convert_to_tensor(
          self._learning_rate_power, name="learning_rate_power"
      )
  
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 3 for calling the FtrlOptimizer obj's underlying member method code with example usage: obj._prepare() without return types