code: def merge_fold_datasets(fold_datasets):
      """Merges fold datasets together.
  
      Assumes that fold_datasets were outputted from k_fold_split. Specifically,
      assumes that each dataset contains the same datapoints, listed in the same
      ordering.
      """
      if not len(fold_datasets):
          return None
  
      # All datasets share features and identifiers by assumption.
      X = fold_datasets[0].X
      ids = fold_datasets[0].ids
  
      ys, ws = [], []
      for fold_dataset in fold_datasets:
          ys.append(fold_dataset.y)
          ws.append(fold_dataset.w)
      y = np.concatenate(ys, axis=1)
      w = np.concatenate(ws, axis=1)
      return NumpyDataset(X, y, w, ids)
  
file_path: deepchem/deepchem/splits/task_splitter.py
imports: import numpy
  from deepchem.data import NumpyDataset
  from deepchem.splits import Splitter
label_desc: Use image node_id 1 for calling a global function with example usage: merge_fold_datasets(fold_datasets) and returns: NumpyDataset, None