class_docstr: Base class for all data iterator classes to inherit. A data iterator
  is a wrapper of :tf_main:`tf.data.Iterator <data/Iterator>`, and can
  switch between and iterate through **multiple** datasets.
  
  Args:
      datasets: Datasets to iterates through. This can be:
  
          - A single instance of :tf_main:`tf.data.Dataset <data/Dataset>`             or instance of subclass of :class:`~texar.tf.data.DataBase`.
          - A `dict` that maps dataset name to             instance of :tf_main:`tf.data.Dataset <data/Dataset>` or             subclass of :class:`~texar.tf.data.DataBase`.
          - A `list` of instances of subclasses of             :class:`texar.tf.data.DataBase`. The name of instances             (:attr:`texar.tf.data.DataBase.name`) must be unique.
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docstr: Number of datasets.
          
docstr_tok: ["Number","of","datasets","."]
code: def num_datasets(self):
      """Number of datasets."""
      return len(self._datasets)
  
imports: import tensorflow
  from texar.tf.data.data.data_base import DataBase
  from texar.tf.utils.variables import get_unique_named_variable_scope
label_desc: Use image node_id 2 for calling the DataIteratorBase obj's underlying member method code with example usage: obj.num_datasets() and returns: len