How to use the dpgen.auto_test.lib.vasp.get_poscar_types function in dpgen

task_poscar = os.path.join(task_path, 'POSCAR')
    cwd = os.getcwd()
    os.chdir(task_path)
    if os.path.isfile('POSCAR') :
        os.remove('POSCAR')
    os.symlink(os.path.relpath(conf_poscar), 'POSCAR')
    os.chdir(cwd)    
    with open(task_poscar,'r') as fp :
        lines = fp.read().split('\n')
        ele_list = lines[5].split()
    
    print(task_path)
    # make conf.lmp  
    conf_file = os.path.join(task_path, 'conf.lmp')
    lammps.cvt_lammps_conf(task_poscar, os.path.relpath(conf_file))
    ptypes = vasp.get_poscar_types(task_poscar)
    lammps.apply_type_map(conf_file, type_map, ptypes) 
    # make lammps.in
    ntypes=len(ele_list)
    unitcell=get_structure_from_poscar(task_poscar)
    if task_type=='deepmd':
        fc = lammps.make_lammps_phonon('conf.lmp', 
                                    unitcell.masses, 
                                    lammps.inter_deepmd,
                                    model_name)
    if task_type=='meam':
        fc = lammps.make_lammps_phonon('conf.lmp', 
                                    unitcell.masses, 
                                    lammps.inter_meam,
                                    model_param)      
    f_lammps_in = os.path.join(task_path, 'lammps.in')
    with open(f_lammps_in, 'w') as fp :

os.makedirs(frame_path, exist_ok=True)
            os.chdir(frame_path)
            # clear dir
            for jj in ['conf.lmp'] :
                if os.path.isfile(jj):
                    os.remove(jj)
            for jj in ['lammps.in'] + model_name :
                if os.path.islink(jj):
                    os.unlink(jj)
            # link lammps in
            os.symlink(os.path.relpath('../lammps.in'), 'lammps.in')
            # make conf
            with open('POSCAR', 'w') as fp :
                fp.write('\n'.join(xdat_lines[ii*xdat_secsize:(ii+1)*xdat_secsize]))
            lammps.cvt_lammps_conf('POSCAR', 'conf.lmp')
            ptypes = vasp.get_poscar_types('POSCAR')
            lammps.apply_type_map('conf.lmp', type_map, ptypes)
            # link models
            for (kk,ll) in zip(share_models, model_name) :
                os.symlink(os.path.relpath(kk), ll)
            os.chdir(ls)
        os.chdir(cwd)

def comput_e_shift(poscar, task_name) :
    a_types = vasp.get_poscar_types(poscar)
    a_natoms = vasp.get_poscar_natoms(poscar)
    ener_shift = 0
    if len(a_types) > 1 :
        if not os.path.isdir('stables') :
            raise RuntimeError('no dir "stable". Stable energy and volume of components should be computed before calculating formation energy of an alloy')
        for ii in range(len(a_types)) :
            ref_e_file = a_types[ii] + '.' + task_name + '.e'
            ref_e_file = os.path.join('stables', ref_e_file)
            ener = float(open(ref_e_file).read())
            ener_shift += a_natoms[ii] * ener
    return ener_shift

share_models = glob.glob(os.path.join(task_path, '*pb'))
    else:
        share_models = models

    for ii in range(n_dfm) :
        # make dir
        dfm_path = os.path.join(task_path, 'dfm-%03d' % ii)
        os.makedirs(dfm_path, exist_ok=True)
        os.chdir(dfm_path)
        for jj in ['conf.lmp', 'lammps.in'] + model_name :
            if os.path.isfile(jj):
                os.remove(jj)
        # make conf
        deformed_structures[ii].to('POSCAR', 'POSCAR')
        lammps.cvt_lammps_conf('POSCAR', 'conf.lmp')
        ptypes = vasp.get_poscar_types('POSCAR')
        lammps.apply_type_map('conf.lmp', type_map, ptypes)    
        # record strain
        strain = Strain.from_deformation(deformations[ii])
        np.savetxt('strain.out', strain)
        # link lammps.in
        os.symlink(os.path.relpath(f_lammps_in), 'lammps.in')
        # link models
        for (ii,jj) in zip(share_models, model_name) :
            os.symlink(os.path.relpath(ii), jj)
    cwd = os.getcwd()

from_poscar = os.path.join(conf_path, 'POSCAR')
    to_poscar = os.path.join(equi_path, 'POSCAR')
    if os.path.exists(to_poscar) :
        assert(filecmp.cmp(from_poscar, to_poscar))
    else :
        os.chdir(equi_path)
        os.symlink(os.path.relpath(from_poscar), 'POSCAR')
        os.chdir(cwd)
    # lmp path
    lmp_path = os.path.join(equi_path, task_type)
    os.makedirs(lmp_path, exist_ok = True)    
    print(lmp_path)
    # lmp conf
    conf_file = os.path.join(lmp_path, 'conf.lmp')
    lammps.cvt_lammps_conf(to_poscar, os.path.relpath(conf_file))
    ptypes = vasp.get_poscar_types(to_poscar)
    lammps.apply_type_map(conf_file, type_map, ptypes)    
    # lmp input
    if task_type=='deepmd':
        fc = lammps.make_lammps_equi(os.path.basename(conf_file), 
                                 ntypes, 
                                 lammps.inter_deepmd, 
                                 model_name)
    elif task_type=='meam':
        fc = lammps.make_lammps_equi(os.path.basename(conf_file), 
                                 ntypes, 
                                 lammps.inter_meam, 
                                 model_param)
    with open(os.path.join(lmp_path, 'lammps.in'), 'w') as fp :
        fp.write(fc)
    # link models
    os.chdir(lmp_path)

vol_path = os.path.join(lmp_path, 'vol-%.2f' % vol)        
        print('# generate %s' % (vol_path))
        os.makedirs(vol_path, exist_ok = True)
        os.chdir(vol_path)
        #print(vol_path)
        for ii in ['conf.lmp', 'conf.lmp'] + model_name :
            if os.path.exists(ii) :
                os.remove(ii)                
        # # link conf
        # os.symlink(os.path.relpath(conf_file), 'conf.lmp')
        # make conf
        scale_ss = ss.copy()
        scale_ss.scale_lattice(vol * natoms)
        scale_ss.to('POSCAR', 'POSCAR')
        lammps.cvt_lammps_conf('POSCAR', 'conf.lmp')
        ptypes = vasp.get_poscar_types('POSCAR')
        lammps.apply_type_map('conf.lmp', type_map, ptypes)
        # link models
        for (ii,jj) in zip(share_models, model_name) :
            os.symlink(os.path.relpath(ii), jj)
        # make lammps input
        scale = (vol / vpa) ** (1./3.)
        if task_type=='deepmd':
            fc = lammps.make_lammps_press_relax('conf.lmp', ntypes, scale,lammps.inter_deepmd, model_name)
        elif task_type =='meam':
            fc = lammps.make_lammps_press_relax('conf.lmp', ntypes, scale,lammps.inter_meam, model_param)    
        with open(os.path.join(vol_path, 'lammps.in'), 'w') as fp :
            fp.write(fc)
        os.chdir(cwd)

for (ii,jj) in zip(models, model_name) :
        os.symlink(os.path.relpath(ii), jj)
    share_models = [os.path.join(task_path,ii) for ii in model_name]

    for ii in range(n_dfm) :
        # make dir
        dfm_path = os.path.join(task_path, 'dfm-%03d' % ii)
        os.makedirs(dfm_path, exist_ok=True)
        os.chdir(dfm_path)
        for jj in ['conf.lmp', 'lammps.in'] + model_name :
            if os.path.isfile(jj):
                os.remove(jj)
        # make conf
        dfm_ss.deformed_structures[ii].to('POSCAR', 'POSCAR')
        lammps.cvt_lammps_conf('POSCAR', 'conf.lmp')
        ptypes = vasp.get_poscar_types('POSCAR')
        lammps.apply_type_map('conf.lmp', type_map, ptypes)    
        # record strain
        strain = Strain.from_deformation(dfm_ss.deformations[ii])
        np.savetxt('strain.out', strain)
        # link lammps.in
        os.symlink(os.path.relpath(f_lammps_in), 'lammps.in')
        # link models
        for (ii,jj) in zip(share_models, model_name) :
            os.symlink(os.path.relpath(ii), jj)
    cwd = os.getcwd()