code: def setUp(self):
      self.config = OmegaConf.create(
          {
              "type": "mlm",
              "freeze": False,
              "vocab_size": 1000,
              "hidden_size": 768,
          }
      )
      hidden_size = 768
      sample_list = Sample()
      sample_list["targets"] = torch.rand((1, 2))
      sample_list["dataset_type"] = "test"
      sample_list["dataset_name"] = "test_dataset"
      sample_list["is_correct"] = torch.ones((1,), dtype=torch.long)
      self.sample_list = sample_list
      self.model_output = torch.rand(size=(1, 1, hidden_size))
      self.losses = {"test_cls": MMFLoss("logit_bce")}
  
file_path: mmf/tests/models/transformers/test_heads_dict.py
imports: import unittest
  import torch
  from mmf.common.sample import Sample
  from mmf.models.transformers.heads.utils import build_heads_dict, HeadsDict
  from mmf.modules.losses import MMFLoss
  from omegaconf import OmegaConf
label_desc: Use image node_id 1 for calling the TestHeadsDict obj's underlying member method code with example usage: obj.setUp() without return types