code: def cupy_kernel_square_diff(in1, in2):
      fin1 = [arr.astype(cupy.float32) for arr in in1]
      fin2 = [arr.astype(cupy.float32) for arr in in2]
      out1, out2 = [
          square_diff_kernel(fin1[i], fin2[i])
          for i in range(BATCH_SIZE)
      ], in2
      return out1, out2
  
imports: import numpy
  import nvidia.dali.ops
  import nvidia.dali.types
  import os
  import random
  from functools import partial
  from nvidia.dali.pipeline import Pipeline
  from nvidia.dali import fn, pipeline_def
  from nvidia.dali.python_function_plugin import current_dali_stream
label_desc: Use image node_id 28 for calling a global function with example usage: cupy_kernel_square_diff(in1, in2) and returns: out1,  out2