class_docstr: Optimizer that implements the LAMBOptimizer as tf.train.Optimizer.
code: def _get_beta_accumulators(self):
      with ops.init_scope():
          if context.executing_eagerly():
              graph = None
          else:
              graph = ops.get_default_graph()
          return (
              self._get_non_slot_variable("beta1_power", graph=graph),
              self._get_non_slot_variable("beta2_power", graph=graph),
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import re
  import tensorflow.compat.v1
  from tensorflow.python.eager import context
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import linalg_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import state_ops
  from tensorflow.python.training import optimizer
label_desc: Use image node_id 2 for calling the LAMBOptimizer obj's underlying member method code with example usage: obj._get_beta_accumulators() and returns: self,  self