code: def sparse_minkowski(ind1, data1, ind2, data2, p=2.0):
      aux_inds, aux_data = sparse_diff(ind1, data1, ind2, data2)
      result = 0.0
      for i in range(aux_data.shape[0]):
          result += np.abs(aux_data[i]) ** p
      return result ** (1.0 / p)
  
imports: from __future__ import print_function
  import locale
  import numba
  import numpy
  from umap.utils import norm
label_desc: Use image node_id 12 for calling a global function with example usage: sparse_minkowski(ind1, data1, ind2, data2, p) and returns: unknown