class_docstr: Top-level loop where validation/testing starts.
docstr: The max number of batches to run per dataloader.
docstr_tok: ["The","max","number","of","batches","to","run","per","dataloader","."]
code: def max_batches(self) -> List[Union[int, float]]:
      """The max number of batches to run per dataloader."""
      max_batches = self._max_batches
      if not self.trainer.sanity_checking:
          return max_batches
      return [
          min(self.trainer.num_sanity_val_steps, batches)
          for batches in max_batches
      ]
  
imports: import os
  import shutil
  import sys
  from collections import ChainMap, OrderedDict, defaultdict
  from typing import Any, DefaultDict, Iterable, Iterator, List, Optional, Tuple, Union
  from lightning_utilities.core.apply_func import apply_to_collection
  from torch import Tensor
  import lightning.pytorch
  from lightning.fabric.utilities.data import _set_sampler_epoch
  from lightning.pytorch.callbacks.progress.rich_progress import _RICH_AVAILABLE
  from lightning.pytorch.loops.fetchers import _DataFetcher, _DataLoaderIterDataFetcher
  from lightning.pytorch.loops.loop import _Loop
  from lightning.pytorch.loops.progress import _BatchProgress
  from lightning.pytorch.loops.utilities import _no_grad_context, _select_data_fetcher, _verify_dataloader_idx_requirement
  from lightning.pytorch.trainer import call
  from lightning.pytorch.trainer.connectors.data_connector import _check_dataloader_iterable, _DataLoaderSource, _parse_num_batches, _process_dataloader, _request_dataloader, _resolve_overfit_batches
  from lightning.pytorch.trainer.connectors.logger_connector.result import _OUT_DICT, _ResultCollection
  from lightning.pytorch.trainer.states import RunningStage, TrainerFn
  from lightning.pytorch.utilities.combined_loader import CombinedLoader
  from lightning.pytorch.utilities.data import has_len_all_ranks
  from lightning.pytorch.utilities.exceptions import SIGTERMException
  from lightning.pytorch.utilities.model_helpers import _ModuleMode, is_overridden
  from lightning.pytorch.utilities.signature_utils import is_param_in_hook_signature
label_desc: Use image node_id 3 for calling the _EvaluationLoop obj's underlying member method code with example usage: obj.max_batches() and returns: unknown, max_batches