无法检索（XX.XX.XX.XX， 8214）的 IPv6 网络地址（gai 错误：-2 - 名称或服务未知）

我就是我 2024-05-05 22:24 8阅读 0赞

#### 文章目录 ####

*   *  一、问题描述
     *  二、问题解答

### 一、问题描述 ###

当我按照说明操作时，我遇到了一个问题，我的步骤如下：

*  连接到我的网络
 *  构建 conda
 *  conda create -n OFA
 *  conda 激活 OFA
 *  cd/ OFA-main
 *  `pip install -r requirements.txt`
 *  `bash train_vqa_distributed.sh`

我得到：

无法检索 （XX.XX.XX.XX， 8214） 的 IPv6 网络地址（gai 错误：-2 - 名称或服务未知）

ERROR：torch.distributed.elastic.multiprocessing.api：failed （exitcode： 255） local_rank： 0

因为我不熟悉设置分发环境，也许这是因为参数不对…

在这里：

2022-12-03 15:04:01 - instantiator.py[line:21] - INFO: Created a temporary directory at /tmp/tmpm4mhx2jo
    2022-12-03 15:04:01 - instantiator.py[line:76] - INFO: Writing /tmp/tmpm4mhx2jo/_remote_module_non_scriptable.py
    2022-12-03 15:04:11 - utils.py[line:258] - INFO: distributed init (rank 0): env://
    2022-12-03 15:04:11 - utils.py[line:261] - INFO: Start init
    Retry: 1, with value error <class 'RuntimeError'>
    /scratch/yz7357/anaconda/envs/OFA/lib/python3.7/site-packages/torch/distributed/launch.py:188: FutureWarning: The module torch.distributed.launch is deprecated
    and will be removed in future. Use torchrun.
    Note that --use_env is set by default in torchrun.
    If your script expects `--local_rank` argument to be set, please
    change it to read from `os.environ['LOCAL_RANK']` instead. See 
    https://pytorch.org/docs/stable/distributed.html#launch-utility for 
    further instructions
    
    FutureWarning,
    ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 255) local_rank: 0 (pid: 1154670) of binary: /scratch/yz7357/anaconda/envs/OFA/bin/python3
    Traceback (most recent call last):
      File "/scratch/yz7357/anaconda/envs/OFA/lib/python3.7/runpy.py", line 193, in _run_module_as_main
        "__main__", mod_spec)
      File "/scratch/yz7357/anaconda/envs/OFA/lib/python3.7/runpy.py", line 85, in _run_code
        exec(code, run_globals)
      File "/scratch/yz7357/anaconda/envs/OFA/lib/python3.7/site-packages/torch/distributed/launch.py", line 195, in <module>
        main()
      File "/scratch/yz7357/anaconda/envs/OFA/lib/python3.7/site-packages/torch/distributed/launch.py", line 191, in main
        launch(args)
      File "/scratch/yz7357/anaconda/envs/OFA/lib/python3.7/site-packages/torch/distributed/launch.py", line 176, in launch
        run(args)
      File "/scratch/yz7357/anaconda/envs/OFA/lib/python3.7/site-packages/torch/distributed/run.py", line 756, in run
        )(*cmd_args)
      File "/scratch/yz7357/anaconda/envs/OFA/lib/python3.7/site-packages/torch/distributed/launcher/api.py", line 132, in __call__
        return launch_agent(self._config, self._entrypoint, list(args))
      File "/scratch/yz7357/anaconda/envs/OFA/lib/python3.7/site-packages/torch/distributed/launcher/api.py", line 248, in launch_agent
        failures=result.failures,
    torch.distributed.elastic.multiprocessing.errors.ChildFailedError:

报错信息如下：

../../train.py FAILED
    ------------------------------------------------------------
    Failures:
      <NO_OTHER_FAILURES>
    ------------------------------------------------------------
    Root Cause (first observed failure):
    [0]:
      time      : 2022-12-03_15:04:12
      host      : log-1.hpc.nyu.edu
      rank      : 0 (local_rank: 0)
      exitcode  : 255 (pid: 1154670)
      error_file: <N/A>
      traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
    ============================================================

### 二、问题解答 ###

更改了文件脚本的开头 - `train_vqa_distributed.sh`，并使用 bash 命令，这是您的代码：

# Number of GPUs per GPU worker
    GPUS_PER_NODE=8 
    # Number of GPU workers, for single-worker training, please set to 1
    WORKER_CNT=4 
    # The ip address of the rank-0 worker, for single-worker training, please set to localhost
    export MASTER_ADDR=XX.XX.XX.XX
    # The port for communication
    export MASTER_PORT=8214
    # The rank of this worker, should be in {0, ..., WORKER_CNT-1}, for single-worker training, please set to 0
    export RANK=0

这是我的更改：

# Number of GPUs per GPU worker
    GPUS_PER_NODE=1
    # Number of GPU workers, for single-worker training, please set to 1
    WORKER_CNT=1
    # The ip address of the rank-0 worker, for single-worker training, please set to localhost
    export MASTER_ADDR=localhost
    # The port for communication
    export MASTER_PORT=8214
    # The rank of this worker, should be in {0, ..., WORKER_CNT-1}, for single-worker training, please set to 0
    export RANK=0