code: def dali_frame_splicing_graph(
      x, nfeatures, x_len, stacking=1, subsampling=1
  ):
      if stacking > 1:
          seq = [x]
          for n in range(1, stacking):
              f = fn.slice(
                  x,
                  n,
                  x_len,
                  axes=(1,),
                  out_of_bounds_policy="pad",
                  fill_values=0,
              )
              seq.append(f)
          x = fn.cat(*seq, axis=0)
          nfeatures = nfeatures * stacking
      if subsampling > 1:
          out_len = (x_len + subsampling - 1) // subsampling
          m = fn.transforms.scale(
              scale=[subsampling, 1], center=[0.5, 0]
          )
          x = fn.reshape(
              x, rel_shape=[1, 1, -1], layout="HWC"
          )  # Layout required by WarpAffine
          size = fn.stack(nfeatures, out_len)
          x = fn.warp_affine(
              x, matrix=m, size=size, interp_type=types.INTERP_NN
          )
          x = fn.reshape(x, rel_shape=[1, 1], layout="ft")
      return x
  
imports: import nose_utils
  import nvidia.dali.fn
  from nvidia.dali import pipeline_def
  import nvidia.dali.types
  from test_utils import get_files, to_array
  import numpy
  import librosa
  import torch
  import math
  import random
  import os
  from nose.tools import nottest
label_desc: Use image node_id 11 for calling a global function with example usage: dali_frame_splicing_graph(x, nfeatures, x_len, stacking, subsampling) and returns: x