def L1_senstivity(query, n_entries = 1000):
  db, pdbs = create_db_and_paralleldbs(n_entries)
  maximum_distance = 0
  total_result = query(db)
  for pdb in pdbs:
    current_result = query(pdb)
    current_distance = torch.abs(current_result - total_result)
    if(current_distance > maximum_distance):
      maximum_distance = current_distance
  return maximum_distance

def mean_query(db):
  return db.float().mean()
def sum_query(db):
  return db.sum()