code: def _get_mask_strategy(strategy):
      """Return the mask computing method based on a provided strategy."""
      if strategy == "background":
          return masking.compute_multi_background_mask
      elif strategy == "epi":
          return masking.compute_multi_epi_mask
      elif strategy == "whole-brain-template":
          return partial(
              masking.compute_multi_brain_mask, mask_type="whole-brain"
          )
      elif strategy == "gm-template":
          return partial(
              masking.compute_multi_brain_mask, mask_type="gm"
          )
      elif strategy == "wm-template":
          return partial(
              masking.compute_multi_brain_mask, mask_type="wm"
          )
      elif strategy == "template":
          warnings.warn(
              "Masking strategy 'template' is deprecated. "
              "Please use 'whole-brain-template' instead."
          )
          return partial(
              masking.compute_multi_brain_mask, mask_type="whole-brain"
          )
      else:
          raise ValueError(
              f"Unknown value of mask_strategy '{strategy}'. "
              "Acceptable values are 'background', "
              "'epi', 'whole-brain-template', "
              "'gm-template', and 'wm-template'."
          )
  
file_path: nilearn/nilearn/maskers/multi_nifti_masker.py
imports: import collections.abc
  import itertools
  import warnings
  from functools import partial
  from joblib import Memory, Parallel, delayed
  from nilearn import _utils, image, masking
  from nilearn.maskers._utils import compute_middle_image
  from nilearn.maskers.nifti_masker import NiftiMasker, _filter_and_mask
label_desc: Use image node_id 1 for calling a global function with example usage: _get_mask_strategy(strategy) and returns: masking, masking, partial, partial, partial, partial