code: def collate_fn(data):
      positive_sample = torch.stack([_[0] for _ in data], dim=0)
      negative_sample = torch.stack([_[1] for _ in data], dim=0)
      mode = data[0][2]
  
      return positive_sample, negative_sample, mode
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import torch
  from torch.utils.data import Dataset
label_desc: Use image node_id 4 for calling the TestDataset obj's underlying member method code with example usage: obj.collate_fn(data) and returns: positive_sample,  negative_sample,  mode