docstr: Returns an iterator of deserialized batches (iterable) of objects from the input stream.
  If the serializer does not operate on batches the default implementation returns an
  iterator of single element lists.
docstr_tok: ["Returns","an","iterator","of","deserialized","batches","(","iterable",")","of","objects","from","the","input","stream",".","If","the","serializer","does","not","operate","on","batches","the","default","implementation","returns","an","iterator","of","single","element","lists","."]
code: def _load_from_stream_without_unbatching(self, stream: BytesIO):
      """
      Returns an iterator of deserialized batches (iterable) of objects from the input stream.
      If the serializer does not operate on batches the default implementation returns an
      iterator of single element lists.
      """
      return map(lambda x: [x], self.deserialize(stream))
  
imports: import pickle
  import struct
  from abc import abstractmethod
  from io import BytesIO
  from itertools import chain
  from typing import TypeVar, Iterable
  from pyflink.common.serializer import TypeSerializer
label_desc: Use image node_id 1 for calling the IterableSerializer obj's underlying member method code with example usage: obj._load_from_stream_without_unbatching(stream) and returns: map