How to use the arms.two_link.arm_python.Arm function in arms

def test_plant():
    """Example of a network using a dynamic plant as the output layer."""

    eps = 1e-6  # value to use for finite differences computations
    dt = 1e-2  # size of time step
    sig_len = 40  # how many time steps to train over
    batch_size = 32  # how many updates to perform with static input
    num_batches = 20000  # how many batches to run total

    import sys
    # NOTE: Change to wherever you keep your arm models
    sys.path.append("../../../studywolf_control/studywolf_control/")
    from arms.two_link.arm_python import Arm as Arm
    print('Plant is: %s' % str(Arm))
    arm = Arm(dt=dt)

    num_states = arm.DOF * 2  # are states are [positions, velocities]
    targets = gen_targets(arm=arm, sig_len=sig_len)  # target joint angles
    init_state = np.zeros((len(targets), num_states), dtype=np.float32)
    init_state[:, :arm.DOF] = arm.init_q  # set up the initial joint angles
    plant = PlantArm(arm=arm, targets=targets,
                     init_state=init_state, eps=eps)

    # open up weights folder and checked for saved weights
    import glob
    folder = 'weights'
    files = sorted(glob.glob('%s/rnn*' % folder))
    if len(files) > 0:
        # if weights found, load them up and keep going from last trial
        W = np.load(files[-1])['arr_0']

def test_plant():
    """Example of a network using a dynamic plant as the output layer."""

    eps = 1e-6  # value to use for finite differences computations
    dt = 1e-2  # size of time step
    sig_len = 40  # how many time steps to train over
    batch_size = 32  # how many updates to perform with static input
    num_batches = 20000  # how many batches to run total

    import sys
    # NOTE: Change to wherever you keep your arm models
    sys.path.append("../../../studywolf_control/studywolf_control/")
    from arms.two_link.arm_python import Arm as Arm
    print('Plant is: %s' % str(Arm))
    arm = Arm(dt=dt)

    num_states = arm.DOF * 2  # are states are [positions, velocities]
    targets = gen_targets(arm=arm, sig_len=sig_len)  # target joint angles
    init_state = np.zeros((len(targets), num_states), dtype=np.float32)
    init_state[:, :arm.DOF] = arm.init_q  # set up the initial joint angles
    plant = PlantArm(arm=arm, targets=targets,
                     init_state=init_state, eps=eps)

    # open up weights folder and checked for saved weights
    import glob
    folder = 'weights'
    files = sorted(glob.glob('%s/rnn*' % folder))
    if len(files) > 0:
        # if weights found, load them up and keep going from last trial
        W = np.load(files[-1])['arr_0']
        print('loading from %s' % files[-1])