class_docstr: The [`Evaluator`] class is the class from which all evaluators inherit. Refer to this class for methods shared across
  different evaluators.
  Base class implementing evaluator operations.
class_docstr_tok: ["The","[","`","Evaluator","`","]","class","is","the","class","from","which","all","evaluators","inherit",".","Refer","to","this","class","for","methods","shared","across","different","evaluators",".","Base","class","implementing","evaluator","operations","."]
code: def call_pipeline(self, pipe, *args, **kwargs):
      start_time = perf_counter()
      pipe_output = pipe(*args, **kwargs, **self.PIPELINE_KWARGS)
      end_time = perf_counter()
      return pipe_output, self._compute_time_perf(
          start_time, end_time, len(pipe_output)
      )
  
imports: from abc import ABC, abstractmethod
  from numbers import Number
  from typing import Any, Callable, Dict, List, Optional, Union
  from datasets import Dataset, load_dataset
  from evaluate.evaluator.utils import choose_split
  from time import perf_counter
  from typing_extensions import Literal
  from ..loading import load
  from ..module import EvaluationModule
  from ..utils.logging import get_logger
  from .utils import DatasetColumn
label_desc: Use image node_id 14 for calling the Evaluator obj's underlying member method code with example usage: obj.call_pipeline(pipe) and returns: pipe_output,  self