code: def sparse_cosine(ind1, data1, ind2, data2):
      aux_inds, aux_data = sparse_mul(ind1, data1, ind2, data2)
      result = 0.0
      norm1 = norm(data1)
      norm2 = norm(data2)
  
      for i in range(aux_data.shape[0]):
          result += aux_data[i]
  
      if norm1 == 0.0 and norm2 == 0.0:
          return 0.0
      elif norm1 == 0.0 or norm2 == 0.0:
          return 1.0
      else:
          return 1.0 - (result / (norm1 * norm2))
  
imports: from __future__ import print_function
  import locale
  import numba
  import numpy
  from umap.utils import norm
label_desc: Use image node_id 24 for calling a global function with example usage: sparse_cosine(ind1, data1, ind2, data2) and returns: int, int, unknown