pytorch bug: for step,data in enumerate(loader)+Connection reset by peer

单GPU跑的程序,而且是在docker中,迭代了几百步后,程序突然崩掉了,

程序停在了 for step,data in enumerate(loader),下面是部分bug信息

Traceback (most recent call last):
........
  File ".../torch/utils/data/dataloader.py", line 206, in __next__
    idx, batch = self.data_queue.get()
  File "/usr/lib/python2.7/multiprocessing/queues.py", line 378, in get
    return recv()
  File ".../torch/multiprocessing/queue.py", line 22, in recv
    return pickle.loads(buf)
  File "/usr/lib/python2.7/pickle.py", line 1388, in loads
    return Unpickler(file).load()
  File "/usr/lib/python2.7/pickle.py", line 864, in load
    dispatch[key](self)
  File "/usr/lib/python2.7/pickle.py", line 1139, in load_reduce
    value = func(*args)
  File ".../torch/multiprocessing/reductions.py", line 68, in rebuild_storage_fd
    fd = multiprocessing.reduction.rebuild_handle(df)
  File "/usr/lib/python2.7/multiprocessing/reduction.py", line 155, in rebuild_handle
    conn = Client(address, authkey=current_process().authkey)
  File "/usr/lib/python2.7/multiprocessing/connection.py", line 175, in Client
    answer_challenge(c, authkey)
  File "/usr/lib/python2.7/multiprocessing/connection.py", line 432, in answer_challenge
    message = connection.recv_bytes(256)         # reject large message
IOError: [Errno 104] Connection reset by peer

我以为是enumerate的问题,出现了脏数据,但细想不可能啊,都迭代了一个epoch了,

查看资料,追踪这个error,Connection reset by peer,网上说是https://github.com/pytorch/pytorch/issues/9127,

以前版本有bug,需要将新版本的 torch/_six.py and torch/utils/data/dataloader.py 替换以前的版本,

工作量大,被这个思路带着走,完全跑偏了。放弃了,

查询DataLoader的参数,有建议把batch_size调小,调到了1,

num_workers值也调到了1,还是报错,

DataLoader的函数定义如下:

DataLoader(dataset, batch_size=1, shuffle=False, sampler=None,
num_workers=0, collate_fn=default_collate, pin_memory=False,
drop_last=False)

1.  dataset:加载的数据集
2.  batch_size:batch size
3.  shuffle::是否将数据打乱
4.  sampler: 样本抽样
5.  num_workers:使用多进程加载的进程数,0代表不使用多进程
6.  collate_fn: 如何将多个样本数据拼接成一个batch,一般使用默认的拼接方式即可
7.  pin_memory:是否将数据保存在pin memory区,pin memory中的数据转到GPU会快一些
8.  drop_last:dataset中的数据个数可能不是batch_size的整数倍,drop_last为True会将多出来不足一个batch的数据丢弃

于是将num_workers参数值改成了默认值 0,不用多进程跑,程序可以运行了,激动万分,感激涕零啊

posted @ 2019-03-28 15:29  胡里糊涂  阅读(1541)  评论(0编辑  收藏