class_docstr: Top-level loop where validation/testing starts.
docstr: Helper method to build args for `test_step` or `validation_step`.
docstr_tok: ["Helper","method","to","build","args","for","`","test_step","`","or","`","validation_step","`","."]
code: def _build_step_args_from_hook_kwargs(
      self, hook_kwargs: OrderedDict, step_hook_name: str
  ) -> tuple:
      """Helper method to build args for `test_step` or `validation_step`."""
      kwargs = hook_kwargs.copy()
      step_hook_fx = getattr(
          self.trainer.lightning_module, step_hook_name
      )
      if not is_param_in_hook_signature(
          step_hook_fx, "batch_idx", min_args=2
      ):
          kwargs.pop("batch_idx", None)
      return tuple(kwargs.values())
  
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 24 for calling the _EvaluationLoop obj's underlying member method code with example usage: obj._build_step_args_from_hook_kwargs(hook_kwargs, step_hook_name) and returns: tuple