code: def unique1d(tensor):
      if tensor.size()[0] == 0 or tensor.size()[0] == 1:
          return tensor
      tensor = tensor.sort()[0]
      unique_bool = tensor[1:] != tensor[:-1]
      first_element = Variable(
          torch.ByteTensor([True]), requires_grad=False
      )
      if tensor.is_cuda:
          first_element = first_element.cuda()
      unique_bool = torch.cat((first_element, unique_bool), dim=0)
      return tensor[unique_bool.data]
  
imports: import numpy
  import scipy.misc
  import scipy.ndimage
  import torch
  from torch.autograd import Variable
  import torch.nn
label_desc: Use image node_id 19 for calling a global function with example usage: unique1d(tensor) and returns: tensor, tensor