code: def multiple_ins_run_gpu(out0, in0, in1, in2):
      tx, ty = cuda.grid(2)
      x_s, y_s = cuda.gridsize(2)
  
      for y in range(ty, out0.shape[0], y_s):
          for x in range(tx, out0.shape[1], x_s):
              out0[y][x][0] = in0[y][x]
              out0[y][x][1] = in1[y][x]
              out0[y][x][2] = in2[y][x]
  
imports: import numpy
  import os
  from nvidia.dali import pipeline_def
  import nvidia.dali
  import nvidia.dali.fn
  import nvidia.dali.types
  from nose import with_setup
  from test_utils import get_dali_extra_path, to_array, check_numba_compatibility_cpu, check_numba_compatibility_gpu
  from nvidia.dali.plugin.numba.fn.experimental import numba_function
  from numba import cuda
label_desc: Use image node_id 39 for calling a global function with example usage: multiple_ins_run_gpu(out0, in0, in1, in2) without return types