from pathlib import Path
import sys,os,torch
import torch.distributed as dist
R=Path(__file__).resolve().parents[1];sys.path.insert(0,str(R));from model.pysteps import *
c=cfg(R);rank=int(os.getenv('RANK',0));world=int(os.getenv('WORLD_SIZE',1));ddp=world>1
if ddp:dist.init_process_group('gloo')
m=STEPS(**c['model']);p=R/c['paths']['checkpoint']
if rank==0:p.parent.mkdir(parents=True,exist_ok=True);torch.save({'model':m.state_dict(),'model_config':c['model']},p);write(R/c['paths']['training_metrics'],{'online_parameter_estimation':True,'world_size':world});print(p)
if ddp:dist.destroy_process_group()