code: def get_subset_sum_kernel(dtype_out, dtype_subset, dtype_in):
      if dtype_out is None:
          dtype_out = dtype_in
  
      return ReductionKernel(
          dtype_out,
          "0",
          "a+b",
          map_expr="in[lookup_tbl[i]]",
          arguments="const %(tp_lut)s *lookup_tbl, const %(tp)s *in"
          % {
              "tp": dtype_to_ctype(dtype_in),
              "tp_lut": dtype_to_ctype(dtype_subset),
          },
      )
  
file_path: pycuda/pycuda/reduction.py
imports: from pycuda.tools import context_dependent_memoize
  from pycuda.tools import dtype_to_ctype
  import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: get_subset_sum_kernel(dtype_out, dtype_subset, dtype_in) and returns: ReductionKernel