code: def get_pad_layer_1d(pad_type):
      if pad_type in ["refl", "reflect"]:
          PadLayer = nn.ReflectionPad1d
      elif pad_type in ["repl", "replicate"]:
          PadLayer = nn.ReplicationPad1d
      elif pad_type == "zero":
          PadLayer = nn.ZeroPad1d
      else:
          print("Pad type [%s] not recognized" % pad_type)
      return PadLayer
  
file_path: antialiased-cnns/antialiased_cnns/blurpool.py
imports: import torch
  import torch.nn.parallel
  import numpy
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling a global function with example usage: get_pad_layer_1d(pad_type) and returns: PadLayer