class_docstr: A DoFn that extracts the FPL from the examples.
class_docstr_tok: ["A","DoFn","that","extracts","the","FPL","from","the","examples","."]
code: def finish_bundle(self):
      # Must update distribution in finish_bundle instead of setup
      # because Beam metrics are not supported in setup.
      if self._model_load_seconds is not None:
          self._model_load_seconds_distribution.update(
              self._model_load_seconds
          )
          self._model_load_seconds = None
  
imports: import copy
  import datetime
  from typing import Generator, List, Optional
  import apache_beam
  from apache_beam.utils import shared
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.eval_metrics_graph import eval_metrics_graph
  from tensorflow_model_analysis.extractors import extractor
  from tensorflow_model_analysis.model_agnostic_eval import model_agnostic_predict
label_desc: Use image node_id 5 for calling the _ModelAgnosticExtractDoFn obj's underlying member method code with example usage: obj.finish_bundle() without return types