code: def __init__(
      self,
      model,
      n_tasks,
      n_feat,
      logdir=None,
      batch_size=50,
      final_loss="cross_entropy",
      learning_rate=0.001,
      optimizer_type="adam",
      learning_rate_decay_time=1000,
      beta1=0.9,
      beta2=0.999,
      pad_batches=True,
      verbose=True,
  ):
      warnings.warn(
          "MultitaskGraphClassifier is deprecated. "
          "Will be removed in DeepChem 1.4.",
          DeprecationWarning,
      )
      super(MultitaskGraphClassifier, self).__init__(
          model_dir=logdir, verbose=verbose
      )
      self.n_tasks = n_tasks
      self.final_loss = final_loss
      self.model = model
      self.sess = tf.Session(graph=self.model.graph)
  
      with self.model.graph.as_default():
          # Extract model info
          self.batch_size = batch_size
          self.pad_batches = pad_batches
          # Get graph topology for x
          self.graph_topology = self.model.get_graph_topology()
          self.feat_dim = n_feat
  
          # Raw logit outputs
          self.logits = self.build()
          self.loss_op = self.add_training_loss(
              self.final_loss, self.logits
          )
          self.outputs = self.add_softmax(self.logits)
  
          self.learning_rate = learning_rate
          self.T = learning_rate_decay_time
          self.optimizer_type = optimizer_type
  
          self.optimizer_beta1 = beta1
          self.optimizer_beta2 = beta2
  
          # Set epsilon
          self.epsilon = 1e-7
          self.add_optimizer()
  
          # Initialize
          self.init_fn = tf.global_variables_initializer()
          self.sess.run(self.init_fn)
  
          # Path to save checkpoint files, which matches the
          # replicated supervisor's default path.
          self._save_path = os.path.join(self.model_dir, "model.ckpt")
  
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 1 to create a new MultitaskGraphClassifier object from inherited base classes: Model with example: obj = MultitaskGraphClassifier(model, n_tasks, n_feat, logdir, batch_size, final_loss, learning_rate, optimizer_type, learning_rate_decay_time, beta1, beta2, pad_batches, verbose)