class_docstr: Optimizer that implements the Yogi algorithm in Keras.
  
  See Algorithm 2 of
  https://papers.nips.cc/paper/8186-adaptive-methods-for-nonconvex-optimization.pdf.
class_docstr_tok: ["Optimizer","that","implements","the","Yogi","algorithm","in","Keras",".","See","Algorithm","2","of","https",":","\/\/papers.nips.cc\/paper\/8186-adaptive-methods-for-nonconvex-optimization.pdf","."]
code: def get_config(self):
      config = super().get_config()
      config.update(
          {
              "learning_rate": self._serialize_hyperparameter(
                  "learning_rate"
              ),
              "decay": self._serialize_hyperparameter("decay"),
              "beta1": self._serialize_hyperparameter("beta_1"),
              "beta2": self._serialize_hyperparameter("beta_2"),
              "epsilon": self._serialize_hyperparameter("epsilon"),
              "l1_regularization_strength": self._serialize_hyperparameter(
                  "l1_regularization_strength"
              ),
              "l2_regularization_strength": self._serialize_hyperparameter(
                  "l2_regularization_strength"
              ),
              "activation": self._activation,
              "initial_accumulator_value": self._initial_accumulator_value,
          }
      )
      return config
  
file_path: addons/tensorflow_addons/optimizers/yogi.py
imports: import tensorflow
  from tensorflow_addons.utils.types import FloatTensorLike
  from tensorflow_addons.optimizers import KerasLegacyOptimizer
  from typeguard import typechecked
  from typing import Union, Callable
label_desc: Use image node_id 5 for calling the Yogi obj's underlying member method code with example usage: obj.get_config() and returns: config