import torch.distributed as c10d
import torch
import argparse
import os
import logging
logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', level=logging.INFO)

if __name__ == "__main__":
    parser = argparse.ArgumentParser(
        description='Simple script to simulate NCCL errors. The script is '
        'supposed to be run on multiple different nodes simultaneously with '
        'appropriate rank and world_size. The script run an allreduce() on '
        'the rank 0 node and aborts all the other nodes to simulate an error '
        'in NCCL')
    parser.add_argument('addr', help='address of the master node to connect to.')
    parser.add_argument('port', help='port of the master node to connect to.')
    parser.add_argument('rank', help='rank of this node')
    parser.add_argument('world_size', help='number of nodes in process group')
    args = parser.parse_args()
    rank = int(args.rank)
    world_size = int(args.world_size)
    port = int(args.port)

    store = c10d.TCPStore(args.addr, port, world_size, rank == 0)
    process_group = c10d.ProcessGroupNCCL(store, rank, world_size)
    logging.info('Running first allreduce')
    process_group.allreduce(torch.rand(10).cuda(rank)).wait()
    if rank == 0:
        logging.info('Running second allreduce only on rank 0')
        work = process_group.allreduce(torch.rand(10).cuda(rank))
        logging.info('Waiting for allreduce to complete...')
        work.wait()
        logging.info('Second allreduce successful: %s', work.is_success())
    else:
        logging.info('Aborting all other ranks.')
        os.abort()