How to use the dpgen.dispatcher.Dispatcher.make_dispatcher function in dpgen

else:
            models = [os.path.join(model_dir,ii) for ii in model_name]
        forward_files = ['conf.lmp', 'lammps.in']+model_name
        backward_files = ['log.lammps',task_type+'.out']
        common_files=['lammps.in']+model_name

        if len(model_name)>1 and task_type == 'deepmd':
            backward_files = backward_files + ['model_devi.out']

    else:
        raise RuntimeError ("unknow task %s, something wrong" % task_type)

    run_tasks = util.collect_task(all_task,task_type)
    if len(run_tasks)==0: return
    machine,resources,command,group_size=util.get_machine_info(mdata,task_type)
    disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size)
    disp.run_jobs(resources,
                  command,
                  work_path,
                  run_tasks,
                  group_size,
                  common_files,
                  forward_files,
                  backward_files,
                  outlog=task_type+'.out',
                  errlog=task_type+'.err')

run_tasks.append(os.path.basename(jj))
            disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size)
            disp.run_jobs(resources,
                          command,
                          ii,
                          run_tasks,
                          group_size,
                          common_files,
                          forward_files,
                          backward_files,
                          outlog=task_type+'.out',
                          errlog=task_type+'.err')
    else:
        run_tasks = util.collect_task(all_task,task_type)
        if len(run_tasks)==0: return
        disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size)
        disp.run_jobs(resources,
                      command,
                      work_path,
                      run_tasks,
                      group_size,
                      common_files,
                      forward_files,
                      backward_files,
                      outlog=task_type+'.out',
                      errlog=task_type+'.err')

else:
            models = [os.path.join(model_dir,ii) for ii in model_name]
        forward_files = ['conf.lmp', 'lammps.in','strain.out']+model_name
        backward_files = ['log.lammps', task_type+'.out']
        common_files=['lammps.in']+model_name

        if len(model_name)>1 and task_type == 'deepmd':
            backward_files = backward_files + ['model_devi.out']

    else:
        raise RuntimeError ("unknow task %s, something wrong" % task_type)

    run_tasks = util.collect_task(all_task,task_type)
    if len(run_tasks)==0: return
    machine,resources,command,group_size=util.get_machine_info(mdata,task_type)
    disp = make_dispatcher(machine, resources, work_path, run_tasks, group_size)
    disp.run_jobs(resources,
                  command,
                  work_path,
                  run_tasks,
                  group_size,
                  common_files,
                  forward_files,
                  backward_files,
                  outlog=task_type+'.out',
                  errlog=task_type+'.err')

for single_sys in os.listdir(os.path.join(ii)):
                trans_comm_data += glob.glob(os.path.join(ii, single_sys, 'set.*'))
                trans_comm_data += glob.glob(os.path.join(ii, single_sys, 'type*.raw'))
                trans_comm_data += glob.glob(os.path.join(ii, single_sys, 'nopbc'))
        else:
            trans_comm_data += glob.glob(os.path.join(ii, 'set.*'))
            trans_comm_data += glob.glob(os.path.join(ii, 'type*.raw'))
            trans_comm_data += glob.glob(os.path.join(ii, 'nopbc'))
    os.chdir(cwd)

    try:
        train_group_size = mdata['train_group_size']
    except:
        train_group_size = 1

    dispatcher = make_dispatcher(mdata['train_machine'], mdata['train_resources'], work_path, run_tasks, train_group_size)
    dispatcher.run_jobs(mdata['train_resources'],
                        commands,
                        work_path,
                        run_tasks,
                        train_group_size,
                        trans_comm_data,
                        forward_files,
                        backward_files,
                        outlog = 'train.log',
                        errlog = 'train.log')

for line in frec:
                iter_rec = int(line.strip())
        dlog.info("continue from task %02d" % iter_rec)
    for ii in range(numb_task):
        sepline(str(ii), '-')
        if ii <= iter_rec:
            continue
        elif ii == 0:
            link_reaxff(jdata)
        elif ii == 1:
            dispatcher = make_dispatcher(mdata["reaxff_machine"])
            run_reaxff(jdata, mdata, dispatcher)
        elif ii == 2:
            link_trj(jdata)
        elif ii == 3:
            dispatcher = make_dispatcher(mdata["build_machine"])
            run_build_dataset(jdata, mdata, dispatcher)
        elif ii == 4:
            link_fp_input()
        elif ii == 5:
            dispatcher = make_dispatcher(mdata["fp_machine"])
            run_fp(jdata, mdata, dispatcher)
        elif ii == 6:
            convert_data(jdata)
        with open(record, "a") as frec:
            frec.write(str(ii)+'\n')

if ii <= iter_rec:
            continue
        elif ii == 0:
            link_reaxff(jdata)
        elif ii == 1:
            dispatcher = make_dispatcher(mdata["reaxff_machine"])
            run_reaxff(jdata, mdata, dispatcher)
        elif ii == 2:
            link_trj(jdata)
        elif ii == 3:
            dispatcher = make_dispatcher(mdata["build_machine"])
            run_build_dataset(jdata, mdata, dispatcher)
        elif ii == 4:
            link_fp_input()
        elif ii == 5:
            dispatcher = make_dispatcher(mdata["fp_machine"])
            run_fp(jdata, mdata, dispatcher)
        elif ii == 6:
            convert_data(jdata)
        with open(record, "a") as frec:
            frec.write(str(ii)+'\n')

from monty.serialization import loadfn,dumpfn
       warnings.simplefilter('ignore', ruamel.yaml.error.MantissaNoDotYAML1_1Warning)
       jdata=loadfn(args.PARAM)
       if args.MACHINE is not None:
          mdata=loadfn(args.MACHINE)
    except:
       with open (args.PARAM, 'r') as fp :
           jdata = json.load (fp)
       if args.MACHINE is not None:
          with open (args.MACHINE, "r") as fp:
              mdata = json.load(fp)

    if args.MACHINE is not None:
       # Selecting a proper machine
       mdata = decide_fp_machine(mdata)
       disp = make_dispatcher(mdata["fp_machine"])

    # Decide work path
    out_dir = out_dir_name(jdata)
    jdata['out_dir'] = out_dir
    dlog.info ("# working dir %s" % out_dir)
    # Decide whether to use a given poscar
    from_poscar = False 
    if 'from_poscar' in jdata :
        from_poscar = jdata['from_poscar']
    # Verify md_nstep
    md_nstep_jdata = jdata["md_nstep"]
    try:
        md_incar = jdata['md_incar']
        if os.path.isfile(md_incar):
            with open(md_incar , "r") as fr:
                md_incar_lines = fr.readlines()

run_tasks = [os.path.basename(ii) for ii in run_tasks_]
    #dlog.info("all_task is ", all_task)
    #dlog.info("run_tasks in run_model_deviation",run_tasks_)
    all_models = glob.glob(os.path.join(work_path, 'graph*pb'))
    model_names = [os.path.basename(ii) for ii in all_models]
    forward_files = ['conf.lmp', 'input.lammps', 'traj']
    backward_files = ['model_devi.out', 'model_devi.log', 'traj']
    if use_plm:
        forward_files += ['input.plumed']
       # backward_files += ['output.plumed']
        backward_files += ['output.plumed','COLVAR','dump.0.xyz']
        if use_plm_path:
            forward_files += ['plmpath.pdb']

    cwd = os.getcwd()
    dispatcher = make_dispatcher(mdata['model_devi_machine'], mdata['model_devi_resources'], work_path, run_tasks, model_devi_group_size)
    dispatcher.run_jobs(mdata['model_devi_resources'],
                        commands,
                        work_path,
                        run_tasks,
                        model_devi_group_size,
                        model_names,
                        forward_files,
                        backward_files,
                        outlog = 'model_devi.log',
                        errlog = 'model_devi.log')