def test_ppo_dual_clip() -> None:
    """
    **Overview**:
        This function tests the ppo_dual_clip function. It generates some sample data, calculates the
        policy loss using the ppo_dual_clip function, and checks if the returned value is a scalar.
    """
    # Generate random data for testing. The batch size is 6.
    B = 6
    logp_new = torch.randn(B)
    logp_old = torch.randn(B)
    adv = torch.randn(B)
    # Calculate policy loss using the ppo_dual_clip function.
    policy_loss = ppo_dual_clip(logp_new, logp_old, adv, 0.2, 3.)
    # Assert that the returned policy loss is a scalar (i.e., its shape is an empty tuple).
    assert policy_loss.shape == torch.Size([])

    **Overview**:
        This function tests the ppo_dual_clip function. It generates some sample data, calculates the
        policy loss using the ppo_dual_clip function, and checks if the returned value is a scalar.
    
chapter7_tricks/dual_clip.py