code: def load_dataset(dataset, group_all=False):
      ret = get_loader(dataset)()
  
      if group_all and len(ret) > 2 and ret[2] is not None:
          X_tr, y_tr, X_te, y_te = ret
  
          if hasattr(X_tr, "tocsr"):
              data = sp.vstack((X_tr, X_te)).tocsr()
          else:
              data = np.vstack((X_tr, X_te))
          target = np.concatenate((y_tr, y_te))
  
          return (data, target)
      else:
          return ret[:2]
  
imports: import os
  import numpy
  import scipy.sparse
  from sklearn.datasets.base import get_data_home
  from sklearn.utils import check_random_state
label_desc: Use image node_id 35 for calling a global function with example usage: load_dataset(dataset, group_all) and returns: data,  target, ret