class_docstr: CombineFn to create query examples for each query id.
  
  Note that this assumes the number of examples for each query ID is small
  enough to fit in memory.
code: def __init__(self, prediction_key: str):
      if not prediction_key:
          # If prediction key is set to the empty string, the user is telling us
          # that their Estimator returns a predictions Tensor rather than a
          # dictionary. Set the key to the magic key we use in that case.
          self._prediction_key = eval_saved_model_util.default_dict_key(
              eval_saved_model_constants.PREDICTIONS_NAME
          )
      else:
          self._prediction_key = prediction_key
  
imports: from typing import Any, Dict, Iterable, Iterator, List, Optional, Tuple
  import apache_beam
  import numpy
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.eval_saved_model import constants
  from tensorflow_model_analysis.eval_saved_model import encoding
  from tensorflow_model_analysis.eval_saved_model import util
  from tensorflow_model_analysis.evaluators import evaluator
  from tensorflow_model_analysis.evaluators.query_metrics import query_types
  from tensorflow_model_analysis.extractors import extractor
  from tensorflow_model_analysis.extractors import slice_key_extractor
label_desc: Use image node_id 1 to create a new CreateQueryExamples object from inherited base classes: beam with example: obj = CreateQueryExamples(prediction_key)