class_docstr: Wraps an iterator to provide async prefetching.
  
  DEPRECATION WARNING:
  TensorFlow datasets no longer require manual prefetching.
  
  Previously this class was used to make data loading using TensorFlow datasets
  more efficient. Now TF data handles prefetching with NumPy iterators
  correctly.
  
  Example::
  
    tf_iter = dataset.as_numpy_iterator()  # only loads data while calling next
    tf_iter = PrefetchIterator(tf_iter)  # prefetches data in the background
code: def __next__(self):
      with self._cond:
          self._cond.wait_for(lambda: self._buffer or not self._active)
          if self._buffer:
              item = self._buffer.pop(0)
              self._cond.notify_all()
              return item
          if self._error:
              raise self._error  # pylint: disable=raising-bad-type
          assert not self._active
          raise StopIteration()
  
imports: import threading
  import warnings
label_desc: Use image node_id 3 for calling the PrefetchIterator obj's underlying member method code with example usage: obj.__next__() and returns: item