code: def __init__(self):
      super().__init__()
      self.linear = nn.Linear(300, 300, bias=False)
      self.mod = TestModule()
      self.conv = TestConvModule()
      # we should be able to pick up user defined parameters as well
      self.extra_params = nn.Parameter(torch.randn(10, 10))
      # we shouldn't count flops for an unused layer
      self.unused_linear = nn.Linear(2, 2, bias=False)
  
imports: import unittest
  import torch
  import torch.nn
  from classy_vision.generic.profiler import compute_activations, compute_flops, count_params, get_shape
  from classy_vision.models import build_model
  from test.generic.config_utils import get_test_model_configs
label_desc: Use image node_id 1 to create a new TestModel object from inherited base classes: nn with example: obj = TestModel()