class_docstr: Test the PipelineHelper class.
class_docstr_tok: ["Test","the","PipelineHelper","class","."]
code: def test_split_emptydict(self):
      # test a horrible edge case where d is an empty dict, and we need to
      # return a BUNCH of empty dicts
      t = torch.randn(32, 5)
      d = {}
      tup = (t, d)
      items = PipelineHelper.split(tup, 8)
      assert len(items) == 4
      for item in items:
          assert isinstance(item, tuple)
          a, b = item
          assert isinstance(a, torch.Tensor)
          assert a.shape == (8, 5)
          assert isinstance(b, dict)
          assert b == {}
  
imports: import torch
  import numpy
  import unittest
  from parlai.utils.torch import padded_tensor, argsort, PipelineHelper, neginf, IdentityLayer, trainable_parameters, total_parameters
label_desc: Use image node_id 6 for calling the TestPipelineHelper obj's underlying member method code with example usage: obj.test_split_emptydict() without return types