class_docstr: Optimizer that implements the LAMBOptimizer as tf.train.Optimizer.
code: def _prepare(self):
      lr = self._call_if_callable(self._lr)
      beta1 = self._call_if_callable(self._beta1)
      beta2 = self._call_if_callable(self._beta2)
      epsilon = self._call_if_callable(self._epsilon)
      weight_decay_rate = self._call_if_callable(
          self._weight_decay_rate
      )
  
      self._lr_t = ops.convert_to_tensor(lr, name="learning_rate")
      self._beta1_t = ops.convert_to_tensor(beta1, name="beta1")
      self._beta2_t = ops.convert_to_tensor(beta2, name="beta2")
      self._epsilon_t = ops.convert_to_tensor(epsilon, name="epsilon")
      self._weight_decay_rate_t = ops.convert_to_tensor(
          weight_decay_rate, name="weight_decay_rate"
      )
  
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 4 for calling the LAMBOptimizer obj's underlying member method code with example usage: obj._prepare() without return types