def load_eval_results(output_paths: List[Text], mode: Text, model_name: Optional[Text]=None) -> EvalResults:
    'Run model analysis for a single model on multiple data sets.\n\n  Args:\n    output_paths: A list of output paths of completed tfma runs.\n    mode: The mode of the evaluation. Currently, tfma.DATA_CENTRIC_MODE and\n      tfma.MODEL_CENTRIC_MODE are supported.\n    model_name: The name of the model if multiple models are evaluated together.\n\n  Returns:\n    An EvalResults containing the evaluation results serialized at output_paths.\n    This can be used to construct a time series view.\n  '
    results = [load_eval_result(output_path, model_name=model_name) for output_path in output_paths]
    return make_eval_results(results, mode)
Run model analysis for a single model on multiple data sets.

Args:
  output_paths: A list of output paths of completed tfma runs.
  mode: The mode of the evaluation. Currently, tfma.DATA_CENTRIC_MODE and
    tfma.MODEL_CENTRIC_MODE are supported.
  model_name: The name of the model if multiple models are evaluated together.

Returns:
  An EvalResults containing the evaluation results serialized at output_paths.
  This can be used to construct a time series view.
def load_eval_results(output_paths: List[Text], mode: Text, model_name: Optional[Text]=None) -> EvalResults:
    'Run model analysis for a single model on multiple data sets.\n\n  Args:\n    output_paths: A list of output paths of completed tfma runs.\n    mode: The mode of the evaluation. Currently, tfma.DATA_CENTRIC_MODE and\n      tfma.MODEL_CENTRIC_MODE are supported.\n    model_name: The name of the model if multiple models are evaluated together.\n\n  Returns:\n    An EvalResults containing the evaluation results serialized at output_paths.\n    This can be used to construct a time series view.\n  '
    results = [load_eval_result(output_path, model_name=model_name) for output_path in output_paths]
    return make_eval_results(results, mode)