code: def test_bert_classifier_head(self):
      config = {}
      config["hidden_size"] = 768
      config["hidden_act"] = "gelu"
      config["layer_norm_eps"] = 1e-12
      config["hidden_dropout_prob"] = 0.1
      config = OmegaConf.create(config)
      clf = layers.ClassifierLayer("bert", 768, 1, config=config)
      self.assertEqual(len(list(clf.module.children())), 3)
      self.assertEqual(len(list(clf.parameters())), 6)
  
      inp = torch.rand(3, 768)
  
      output = clf(inp)
      self.assertEqual(output.size(), torch.Size((3, 1)))
      np.testing.assert_almost_equal(
          output.squeeze().tolist(),
          [0.5452202, -0.0437842, -0.377468],
          decimal=3,
      )
  
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 6 for calling the TestModuleLayers obj's underlying member method code with example usage: obj.test_bert_classifier_head() without return types