code: def test_unflatten(self):
      unflatten = layers.UnFlatten()
  
      # Test 2 dim to 3 dim
      input_tensor = torch.randn(5, 60)
      expected_size = torch.Size((5, 6, 10))
      actual_size = unflatten(input_tensor, sizes=[6, 10]).size()
      self.assertEqual(actual_size, expected_size)
  
      # Test 1 dim
      input_tensor = torch.randn(5)
      expected_size = torch.Size((5,))
      actual_size = unflatten(input_tensor, sizes=[]).size()
      self.assertEqual(expected_size, actual_size)
  
file_path: mmf/tests/modules/test_layers.py
imports: import functools
  import operator
  import random
  import unittest
  import mmf.modules.layers
  import numpy
  import torch
  from omegaconf import OmegaConf
label_desc: Use image node_id 4 for calling the TestModuleLayers obj's underlying member method code with example usage: obj.test_unflatten() without return types