code: def torch_reflect_pad(x, pad_amount, device="cpu"):
      x = torch.tensor(x, dtype=torch.float32).unsqueeze(0)
      if device == "gpu":
          x = x.cuda()
      x = torch.nn.functional.pad(
          x.unsqueeze(1), (pad_amount, pad_amount), "reflect"
      ).squeeze(1)
      x = x.cpu().numpy().squeeze(0)
      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 12 for calling a global function with example usage: torch_reflect_pad(x, pad_amount, device) and returns: x