def METHOD_NAME(self, model, input_param, input_shape):
    example = torch.randn(input_shape).to(device)
    with skip_if_downloading_fails():
        net = model(**input_param).to(device)
    with eval_mode(net):
        result = net.features.forward(example)
    torchvision_net = torchvision.models.densenet121(pretrained=True).to(device)
    with eval_mode(torchvision_net):
        expected_result = torchvision_net.features.forward(example)
    self.assertTrue(torch.all(result == expected_result))