docstr: Initializes tensorflow optimizers.
docstr_tok: ["Initializes","tensorflow","optimizers","."]
code: def tensorflow_optimizers(self, method="adam"):
      """Initializes tensorflow optimizers."""
      if method == "adam":
          opt = tf.train.AdamOptimizer(
              self.learning_rate, name="myadam"
          )
          # opt = tf.contrib.optimizer_v2.AdamOptimizer(self.learning_rate)
      elif method == "rmsprop":
          opt = tf.train.RMSPropOptimizer(self.learning_rate)
  
      optim_step = opt.minimize(self.loss, var_list=self.cfs)
      return opt, optim_step
  
imports: import collections
  import copy
  import random
  import timeit
  import numpy
  import tensorflow
  from dice_ml import diverse_counterfactuals
  from dice_ml.counterfactual_explanations import CounterfactualExplanations
  from dice_ml.explainer_interfaces.explainer_base import ExplainerBase
label_desc: Use image node_id 13 for calling the DiceTensorFlow1 obj's underlying member method code with example usage: obj.tensorflow_optimizers(method) and returns: opt,  optim_step