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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _GetTfRecordEntries(self, path, max_entries, is_sequence, iterator_options):
 """Extracts TFRecord examples into a dictionary of feature values. Args: path: The path to the TFRecord file(s). max_entries: The maximum number of examples to load. is_sequence: True if the input data from 'path' are tf.SequenceExamples, False if tf.Examples. Defaults to false. iterator_options: Options to pass to the iterator that reads the examples. Defaults to None. Returns: A tuple with two elements: - A dictionary of all features parsed thus far and arrays of their values. - The number of examples parsed. """

    return self._GetEntries([path], max_entries,
                            partial(
                                tf.python_io.tf_record_iterator,
                                options=iterator_options), is_sequence)