f41d084cb14a17bc71e5f71c0b9469fc35fc6de1,deepchem/splits/splitters.py,Splitter,k_fold_split,#Splitter#Any#Any#Any#,56

Before Change

      train_dataset = DiskDataset.merge(filter(lambda x: x is not None, [train_ds_base, cv_dataset]))
      train_datasets.append(train_dataset)
      train_ds_base = DiskDataset.merge(filter(lambda x: x is not None, [train_ds_base, cv_dataset]))
      cv_datasets.append(cv_dataset)
    return list(zip(train_datasets, cv_datasets))

  def train_valid_test_split(self,

After Change

      // Note starts as 1/k since fold starts at 0. Ends at 1 since fold goes up
      // to k-1.
      frac_fold = 1. / (k - fold)
      train_dir, cv_dir = directories[2 * fold], directories[2 * fold + 1]
      fold_inds, rem_inds, _ = self.split(
          rem_dataset,
          frac_train=frac_fold,
          frac_valid=1 - frac_fold,

Instances