class_docstr: A DoFn that extracts the FPL from the examples.
class_docstr_tok: ["A","DoFn","that","extracts","the","FPL","from","the","examples","."]
docstr: Returns construct func for Shared for constructing ModelAgnosticEval.
docstr_tok: ["Returns","construct","func","for","Shared","for","constructing","ModelAgnosticEval","."]
code: def _make_construct_fn(  # pylint: disable=invalid-name
      self, model_agnostic_config: agnostic_predict.ModelAgnosticConfig
  ):
      """Returns construct func for Shared for constructing ModelAgnosticEval."""
  
      def construct():  # pylint: disable=invalid-name
          """Function for constructing a EvalSavedModel."""
          start_time = datetime.datetime.now()
          model_agnostic_wrapper = (
              agnostic_predict.ModelAgnosticPredict(
                  model_agnostic_config
              )
          )
          end_time = datetime.datetime.now()
          self._model_load_seconds = int(
              (end_time - start_time).total_seconds()
          )
          return model_agnostic_wrapper
  
      return construct
  
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 2 for calling the _ModelAgnosticExtractDoFn obj's underlying member method code with example usage: obj._make_construct_fn(model_agnostic_config) and returns: construct, model_agnostic_wrapper