class_docstr: Represents a bounded value for a metric for the TFMA unit test.
class_docstr_tok: ["Represents","a","bounded","value","for","a","metric","for","the","TFMA","unit","test","."]
code: def __init__(
      self,
      lower_bound: float = float("-inf"),
      upper_bound: float = float("inf"),
  ):
      self.lower_bound = lower_bound
      self.upper_bound = upper_bound
  
imports: from typing import Any, Dict, List, Optional
  import apache_beam
  from apache_beam.testing import util
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import model_eval_lib
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.eval_saved_model import load
  from tensorflow_model_analysis.eval_saved_model import testutil
  from tensorflow_model_analysis.evaluators import legacy_metrics_and_plots_evaluator
  from tensorflow_model_analysis.extractors import extractor
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.slicer import slicer_lib
  from tfx_bsl.tfxio import raw_tf_record
label_desc: Use image node_id 1 to create a new BoundedValue object  with example: obj = BoundedValue(lower_bound, upper_bound)