def METHOD_NAME(inputs, m=7, n=6):
    LFR_inputs = []
    T = inputs.shape[0]
    T_lfr = int(np.ceil(T / n))
    left_padding = np.tile(inputs[0], ((m - 1) // 2, 1))
    inputs = np.vstack((left_padding, inputs))
    T = T + (m - 1) // 2
    for i in range(T_lfr):
        if m <= T - i * n:
            LFR_inputs.append(np.hstack(inputs[i * n:i * n + m]))
        else:
            num_padding = m - (T - i * n)
            frame = np.hstack(inputs[i * n:])
            for _ in range(num_padding):
                frame = np.hstack((frame, inputs[-1]))
            LFR_inputs.append(frame)
    return np.vstack(LFR_inputs)