class_docstr: Test class that extends tf.test.TestCase with extra functionality.
code: def createTestEvalSharedModel(
      self,
      eval_saved_model_path: Optional[str] = None,
      add_metrics_callbacks: Optional[
          List[types.AddMetricsCallbackType]
      ] = None,
      include_default_metrics: Optional[bool] = True,
      example_weight_key: Optional[Union[str, Dict[str, str]]] = None,
      additional_fetches: Optional[List[str]] = None,
      tags: Optional[str] = None,
      model_type: Optional[str] = None,
      model_name: str = "",
      rubber_stamp: Optional[bool] = False,
      is_baseline: Optional[bool] = False,
  ) -> types.EvalSharedModel:
      if not model_type:
          model_type = model_util.get_model_type(
              None, eval_saved_model_path, tags
          )
      if not tags:
          if model_type in (constants.TF_GENERIC, constants.TFMA_EVAL):
              # model_type = constants.TF_ESTIMATOR
              model_type = constants.TFMA_EVAL
              tags = [eval_constants.EVAL_TAG]
          else:
              tags = [tf.saved_model.SERVING]
  
      return types.EvalSharedModel(
          model_name=model_name,
          model_type=model_type,
          model_path=eval_saved_model_path,
          add_metrics_callbacks=add_metrics_callbacks,
          example_weight_key=example_weight_key,
          rubber_stamp=rubber_stamp,
          is_baseline=is_baseline,
          model_loader=types.ModelLoader(
              tags=tags,
              construct_fn=model_util.model_construct_fn(
                  eval_saved_model_path=eval_saved_model_path,
                  model_type=model_type,
                  add_metrics_callbacks=add_metrics_callbacks,
                  include_default_metrics=include_default_metrics,
                  additional_fetches=additional_fetches,
                  tags=tags,
              ),
          ),
      )
  
imports: import math
  import tempfile
  from typing import Dict, Iterable, List, Optional, Sequence, Tuple, Union
  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 load
  from tensorflow_model_analysis.eval_saved_model import util
  from tensorflow_model_analysis.utils import model_util
label_desc: Use image node_id 11 for calling the TensorflowModelAnalysisTest obj's underlying member method code with example usage: obj.createTestEvalSharedModel(eval_saved_model_path, add_metrics_callbacks, include_default_metrics, example_weight_key, additional_fetches, tags, model_type, model_name, rubber_stamp, is_baseline) and returns: types