code: def next_batch(self, batch_size):
      if self._next_id >= self.n and self.enable_shuffle:
          self.shuffle()
  
      cur_id = self._next_id
      cur_batch_size = min(batch_size, self.n - self._next_id)
      self._next_id += cur_batch_size
  
      data_map = dict()
      for key in self.data_map:
          data_map[key] = self.data_map[key][
              cur_id : cur_id + cur_batch_size
          ]
      return data_map
  
file_path: baselines/baselines/common/dataset.py
imports: import numpy
label_desc: Use image node_id 3 for calling the Dataset obj's underlying member method code with example usage: obj.next_batch(batch_size) and returns: data_map