code: def _labels_masker_extraction(img, masker, confound):
      """Parallelize NiftiLabelsMasker extractor on list of Nifti images.
  
      Parameters
      ----------
      img : 4D Nifti image like object
          Image to process.
  
      masker : instance of NiftiLabelsMasker
          Used for extracting signals with fit_transform.
  
      confound : csv file, numpy ndarray or pandas DataFrame
          Confound used for signal cleaning while extraction.
          Passed to signal.clean.
  
      Returns
      -------
      signals : numpy array
          Signals extracted on given img.
  
      """
      masker = clone(masker)
      signals = masker.fit_transform(img, confounds=confound)
      return signals
  
imports: import warnings
  import numpy
  from joblib import Memory, Parallel, delayed
  from sklearn.base import clone
  from sklearn.feature_extraction import image
  from nilearn.maskers import NiftiLabelsMasker
  from .._utils import fill_doc, stringify_path
  from .._utils.niimg import safe_get_data
  from .._utils.niimg_conversions import iter_check_niimg
  from ..decomposition._multi_pca import _MultiPCA
  from .hierarchical_kmeans_clustering import HierarchicalKMeans
  from .rena_clustering import ReNA
label_desc: Use image node_id 3 for calling a global function with example usage: _labels_masker_extraction(img, masker, confound) and returns: signals