code: def test_conv_net(self):
      conv_net = layers.ConvNet(150, 75, 3)
  
      input_tensor = torch.randn(4, 150, 64, 64)
      output = conv_net(input_tensor)
      expected_size = torch.Size((4, 75, 32, 32))
      self.assertEqual(output.size(), expected_size)
      # Since seed is fix we can check some of tensor values
      np.testing.assert_almost_equal(
          output[0][0][0][0].item(), 0.149190, decimal=5
      )
      np.testing.assert_almost_equal(
          output[3][74][31][31].item(), -0.25199, decimal=5
      )
  
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 2 for calling the TestModuleLayers obj's underlying member method code with example usage: obj.test_conv_net() without return types