4ab9064d3c9f549631e28cadeaeb0cb81e65d238,deepchem/models/tensorgraph/fcnet.py,MultitaskClassifier,default_generator,#MultitaskClassifier#Any#Any#Any#Any#Any#,136

Before Change

          batch_size=self.batch_size,
          deterministic=deterministic,
          pad_batches=pad_batches):
        feed_dict = dict()
        if y_b is not None and not predict:
          feed_dict[self.labels[0]] = to_one_hot(y_b.flatten(),
                                                 self.n_classes).reshape(
                                                     -1, self.n_tasks,
                                                     self.n_classes)
        if X_b is not None:
          feed_dict[self.features[0]] = X_b
        if w_b is not None and not predict:
          feed_dict[self.task_weights[0]] = w_b
        yield feed_dict

  def create_estimator_inputs(self, feature_columns, weight_column, features,
                              labels, mode):
    tensors = {}

After Change

        if y_b is not None:
          y_b = to_one_hot(y_b.flatten(), self.n_classes).reshape(
              -1, self.n_tasks, self.n_classes)
        yield ([X_b], [y_b], [w_b])


class MultitaskRegressor(KerasModel):

Instances