docstr: Wraps predict_proba to set batch_size/padding.
docstr_tok: ["Wraps","predict_proba","to","set","batch_size\/padding","."]
code: def predict_proba(
      self, dataset, transformers=[], n_classes=2, **kwargs
  ):
      """Wraps predict_proba to set batch_size/padding."""
      return super(MultitaskGraphClassifier, self).predict_proba(
          dataset,
          transformers,
          n_classes=n_classes,
          batch_size=self.batch_size,
      )
  
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 10 for calling the MultitaskGraphClassifier obj's underlying member method code with example usage: obj.predict_proba(dataset, transformers, n_classes) and returns: super