class_docstr: A sliceable version of :class:`chainer.datasets.ConcatenatedDataset`.
  
  Here is an example.
  
  >>> dataset_a = TupleDataset([0, 1, 2], [0, 1, 4])
  >>> dataset_b = TupleDataset([3, 4, 5], [9, 16, 25])
  >>>
  >>> dataset = ConcatenatedDataset(dataset_a, dataset_b)
  >>> dataset.slice[:, 0][:]  # [0, 1, 2, 3, 4, 5]
  
  Args:
      datasets: The underlying datasets.
          Each dataset should inherit
          :class:`~chainercv.chainer_experimental.datasets.sliceable.Sliceabledataset`
          and should have the same keys.
code: def __len__(self):
      return sum(len(dataset) for dataset in self._datasets)
  
imports: from chainercv.chainer_experimental.datasets.sliceable import SliceableDataset
label_desc: Use image node_id 2 for calling the ConcatenatedDataset obj's underlying member method code with example usage: obj.__len__() and returns: sum