code: def _evaluate(
      loop: "EvaluationLoop",
      batch_size: int,
      use_tqdm: bool,
      tqdm_kwargs: OptionalKwargs,
      **kwargs,
  ) -> MetricResults:
      """
      Run the evaluation loop for a given batch size.
  
      .. note::
          this method is wrapped into a `MemoryUtilizationMaximizer` instance to automatically tune the `batch_size`.
  
      :param loop:
          the evaluation loop instance.
      :param batch_size:
          the batch size
      :param use_tqdm:
          whether to use tqdm progress bar
      :param tqdm_kwargs:
          additional keyword-based parameters for the progress bar
      :param kwargs:
          additional keyword-based parameters passed to :meth:`EvaluationLoop.get_loader`
  
      :return:
          the evaluation results
      """
      loop.model.eval()
      loader = loop.get_loader(batch_size=batch_size, **kwargs)
      total = len(loader)
      if use_tqdm:
          loader = tqdm(
              loader,
              desc="evaluation",
              total=total,
              unit="batch",
              unit_scale=True,
              **(tqdm_kwargs or {}),
          )
      for batch in loader:
          loop.process_batch(batch=batch)
      return loop.evaluator.finalize()
  
imports: import dataclasses
  import logging
  from abc import abstractmethod
  from collections import defaultdict
  from typing import Any, Collection, DefaultDict, Generic, Iterable, List, Mapping, Optional, Tuple, TypeVar, Union, cast
  import numpy
  import pandas
  import torch
  from class_resolver import HintOrType, OptionalKwargs
  from torch.utils.data import Dataset
  from torch.utils.data.dataloader import DataLoader
  from torch_max_mem import maximize_memory_utilization
  from tqdm.auto import tqdm
  from typing_extensions import TypeAlias
  from .evaluator import Evaluator, MetricResults, filter_scores_
  from ..constants import COLUMN_LABELS, TARGET_TO_INDEX
  from ..models import Model
  from ..triples import CoreTriplesFactory, get_mapped_triples
  from ..typing import LABEL_HEAD, LABEL_TAIL, InductiveMode, MappedTriples, OneOrSequence, Target
  from ..utils import upgrade_to_sequence
label_desc: Use image node_id 2 for calling a global function with example usage: _evaluate(loop, batch_size, use_tqdm, tqdm_kwargs) and returns: loop