class_docstr: Dataset of tuples from multiple equal-length datasets.
  
  A ``TupleDataset`` combines multiple equal-length datasets into a single
  dataset of tuples. The ``i``-th tuple contains the ``i``-th example from
  each of the argument datasets, in the same order that they were supplied.
  
  Recall that in Chainer, a dataset is defined as an iterable that supports
  both ``__getitem__`` and ``__len__``. The ``__getitem__`` method should
  support indexing by both an integer and a slice.
  
  As an example, consider creating a ``TupleDataset`` from two argument
  datasets ``d1 = [8, 0, 5, 1]`` and ``d2 = [3, 1, 7, 4]`` as
  ``tuple_dataset = TupleDataset(d1, d2)``. The ``tuple_dataset`` will
  then contain the examples ``(8, 3), (0, 1), (5, 7), (1, 4)``. Note that
  this behavior is similar to that of the built-in :func:`zip` function.
  
  Args:
      datasets: Underlying datasets that will be aggregated. Each dataset
          must be an iterable that implements ``__getitem__`` and
          ``__len__``. The ``j``-th dataset will be used for the ``j``-th
          item of each example tuple. All datasets must have the same length.
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code: def __len__(self):
      return self._length
  
imports: import six
label_desc: Use image node_id 3 for calling the TupleDataset obj's underlying member method code with example usage: obj.__len__() and returns: self