code: def test_mmf_dict_loss(self):
      mse_mae_loss = losses.MMFLoss("mse_mae")
      torch.manual_seed(1234)
      random_tensor = torch.rand((1, 768))
  
      sample_list = SampleList()
      sample_list.dataset_type = "val"
      sample_list.dataset_name = "vqa2"
      sample_list["targets"] = random_tensor
      model_output = {"scores": random_tensor}
  
      output = mse_mae_loss(sample_list, model_output)
  
      self.assertEqual(output["val/vqa2/mse_mae/mse"].item(), 0.0)
      self.assertEqual(output["val/vqa2/mse_mae/mae"].item(), 0.0)
  
imports: import collections
  import unittest
  from unittest.mock import MagicMock
  import mmf.modules.losses
  import torch
  import torch.nn
  import torch.nn.functional
  from mmf.common.registry import registry
  from mmf.common.sample import SampleList
label_desc: Use image node_id 4 for calling the TestModuleLosses obj's underlying member method code with example usage: obj.test_mmf_dict_loss() without return types