code: def add_optimizer(self):
      if self.optimizer_type == "adam":
          self.optimizer = tf.train.AdamOptimizer(
              self.learning_rate,
              beta1=self.optimizer_beta1,
              beta2=self.optimizer_beta2,
              epsilon=self.epsilon,
          )
      else:
          raise ValueError("Optimizer type not recognized.")
  
      # Get train function
      self.train_op = self.optimizer.minimize(self.loss_op)
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import warnings
  import os
  import sys
  import numpy
  import tensorflow
  import sklearn.metrics
  import tempfile
  from deepchem.data import pad_features
  from deepchem.utils.save import log
  from deepchem.models import Model
  from deepchem.nn.copy import Input
  from deepchem.nn.copy import Dense
  from deepchem.nn import model_ops
  from deepchem.models.tf_new_models.graph_topology import merge_dicts
label_desc: Use image node_id 3 for calling the MultitaskGraphClassifier obj's underlying member method code with example usage: obj.add_optimizer() without return types