message: Improve Ftrl doc.
diff: @@ -26,13 +26,31 @@ from tensorflow.python.util.tf_export import keras_export
  @keras_export('keras.optimizers.Ftrl')
  class Ftrl(optimizer_v2.OptimizerV2):
  - """Optimizer that implements the FTRL algorithm.
  + r"""Optimizer that implements the FTRL algorithm.
  - See this [paper](
  + See Algorithm 1 of this [paper](
  https://www.eecs.tufts.edu/~dsculley/papers/ad-click-prediction.pdf).
  This version has support for both online L2 (the L2 penalty given in the paper
  above) and shrinkage-type L2 (which is the addition of an L2 penalty to the
  loss function).
  +
  + Initialization:
  + $t = 0$
  + $n_{0} = 0$
  + $\sigma_{0} = 0$
  + $z_{0} = 0$
  +
  + Update ($i$ is variable index):
  + $t = t + 1$
  + $n_{t,i} = n_{t-1,i} + g_{t,i}^{2}$
  + $\sigma_{t,i} = (\sqrt{n_{t,i}} - \sqrt{n_{t-1,i}}) / \alpha$
  + $z_{t,i} = z_{t-1,i} + g_{t,i} - \sigma_{t,i} * w_{t,i}$
  + $w_{t,i} = - ((\beta+\sqrt{n+{t}}) / \alpha + \lambda_{2})^{-1} * (z_{i} -
  + sgn(z_{i}) * \lambda_{1}) if \abs{z_{i}} > \lambda_{i} else 0$
  +
  + Check the documentation for the l2_shrinkage_regularization_strength
  + parameter for more details when shrinkage is enabled, where gradient is
  + replaced with gradient_with_shrinkage.
  """
  def __init__(self,
  