code: def build(self):
      # Create target inputs
      self.label_placeholder = tf.placeholder(
          dtype="bool",
          shape=(None, self.n_tasks),
          name="label_placeholder",
      )
      self.weight_placeholder = tf.placeholder(
          dtype="float32",
          shape=(None, self.n_tasks),
          name="weight_placholder",
      )
  
      feat = self.model.return_outputs()
      ################################################################ DEBUG
      # print("multitask classifier")
      # print("feat")
      # print(feat)
      ################################################################ DEBUG
      output = model_ops.multitask_logits(feat, self.n_tasks)
      return output
  
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 2 for calling the MultitaskGraphClassifier obj's underlying member method code with example usage: obj.build() and returns: output