class_docstr: Extends the base HDF5Iterator class for an autoencoder model.
  Returns the input data as the target.
docstr: Defines a generator that can be used to iterate over this dataset.
  
  Yields:
      tuple: The next minibatch containing the inputs and the targets (here target=inputs)
docstr_tok: ["Defines","a","generator","that","can","be","used","to","iterate","over","this","dataset",".","Yields",":","tuple",":","The","next","minibatch","containing","the","inputs","and","the","targets","(","here","target=inputs",")"]
code: def __iter__(self):
      """
      Defines a generator that can be used to iterate over this dataset.
  
      Yields:
          tuple: The next minibatch containing the inputs and the targets (here target=inputs)
      """
      for x, t in super(HDF5IteratorAutoencoder, self).__iter__():
          yield (x, x)
  
imports: import os
  import h5py
  import logging
  import numpy
  from neon.data import ArrayIterator
label_desc: Use image node_id 1 for calling the HDF5IteratorAutoencoder obj's underlying member method code with example usage: obj.__iter__() without return types