code: def _get_masks_from_nan(X):
      masks = []
      for i in range(len(X)):
          masks.append(_get_mask_from_nan(X[i]))
      return masks
  
imports: from copy import deepcopy
  import numpy
  import warnings
  from .ajd import ajd_pham
  from .base import sqrtm, invsqrtm, logm, expm, powm
  from .distance import distance_riemann
  from .geodesic import geodesic_riemann
  from .utils import check_weights
label_desc: Use image node_id 16 for calling a global function with example usage: _get_masks_from_nan(X) and returns: masks