code: def _convert_delta_mask_to_full(masks, full_masks):
      """This converts a delta masking array to a full bool masking array."""
  
      i = -1
      masks_pos = 0
      while masks_pos < len(masks):
          i += 1
  
          if i > 0:
              full_masks[i] = full_masks[i - 1]
  
          while masks[masks_pos] < 0:
              full_masks[i, -masks[masks_pos] - 1] = ~full_masks[
                  i, -masks[masks_pos] - 1
              ]  # -value - 1 is the original index that needs flipped
              masks_pos += 1
  
          if masks[masks_pos] != MaskedModel.delta_mask_noop_value:
              full_masks[i, masks[masks_pos]] = ~full_masks[
                  i, masks[masks_pos]
              ]
          masks_pos += 1
  
imports: import copy
  import numpy
  import scipy.sparse
  from numba import njit
  from ..None import links
label_desc: Use image node_id 2 for calling a global function with example usage: _convert_delta_mask_to_full(masks, full_masks) without return types