code: def torch_preemphasis(x, preemph, device="cpu"):
      x = torch.tensor(x, dtype=torch.float32)
      if device == "gpu":
          x = x.cuda()
      y = torch.cat(
          (x[0].unsqueeze(0), x[1:] - preemph * x[:-1]), dim=0
      )
      y = y.cpu().numpy()
      return y
  
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 8 for calling a global function with example usage: torch_preemphasis(x, preemph, device) and returns: y