我已经通过hdfs fuse安装了hdfs驱动器，因此我可以通过路径/hdfs/xxx访问hdfs。
在用keras训练了一个模型之后，我想通过model.save("/hdfs/model.h5")将它保存到/hdfs/model.h5。
我得到以下错误：
2020-02-26T10:06:51.83869705Z File "h5py/_objects.pyx", line 193, in h5py._objects.ObjectID.__dealloc__
2020-02-26T10:06:51.838791107Z RuntimeError: Can't decrement id ref count (file write failed: time = Wed Feb 26 10:06:51 2020
2020-02-26T10:06:51.838796288Z , filename = '/hdfs/model.h5', file descriptor = 3, errno = 95, error message = 'Operation not supported', buf = 0x7f20d000ddc8, total write size = 512, bytes this sub-write = 512, bytes actually written = 18446744073709551615, offset = 298264)
2020-02-26T10:06:51.838802442Z Exception ignored in: 'h5py._objects.ObjectID.__dealloc__'
2020-02-26T10:06:51.838807122Z Traceback (most recent call last):
2020-02-26T10:06:51.838811833Z File "h5py/_objects.pyx", line 193, in h5py._objects.ObjectID.__dealloc__
2020-02-26T10:06:51.838816793Z RuntimeError: Can't decrement id ref count (file write failed: time = Wed Feb 26 10:06:51 2020
2020-02-26T10:06:51.838821942Z , filename = '/hdfs/model.h5', file descriptor = 3, errno = 95, error message = 'Operation not supported', buf = 0x7f20d000ddc8, total write size = 512, bytes this sub-write = 512, bytes actually written = 18446744073709551615, offset = 298264)
2020-02-26T10:06:51.838827917Z Traceback (most recent call last):
2020-02-26T10:06:51.838832755Z File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/saving/hdf5_format.py", line 117, in save_model_to_hdf5
2020-02-26T10:06:51.838838098Z f.flush()
2020-02-26T10:06:51.83885453Z File "/usr/local/lib/python3.6/dist-packages/h5py/_hl/files.py", line 452, in flush
2020-02-26T10:06:51.838859816Z h5f.flush(self.id)
2020-02-26T10:06:51.838864401Z File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
2020-02-26T10:06:51.838869302Z File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
2020-02-26T10:06:51.838874126Z File "h5py/h5f.pyx", line 146, in h5py.h5f.flush
2020-02-26T10:06:51.838879016Z RuntimeError: Can't flush cache (file write failed: time = Wed Feb 26 10:06:51 2020
2020-02-26T10:06:51.838885827Z , filename = '/hdfs/model.h5', file descriptor = 3, errno = 95, error message = 'Operation not supported', buf = 0x4e5b018, total write size = 4, bytes this sub-write = 4, bytes actually written = 18446744073709551615, offset = 34552)但我可以直接将文件写入同一路径
with open("/hdfs/a.txt") as f:
f.write("1")我还想出了一个棘手的变通办法，它的工作。..
model.save("temp.h5")
move("temp.h5", "/hdfs/model.h5")所以问题可能出在keras API上？它只能在本地保存模型，但不能保存到hdfs路径。
有什么办法解决这个问题吗？
2条答案
按热度按时间lymnna711#
我不认为
tensorflow承诺能够保存到hdfs-fuse。你的（最终）错误是“Can 't flush cache”不是，“Can 't decrease id ref count”，基本上意思是“Can 't保存straight to hdfs-fuse”。但是，说实话，它似乎固定给我，你的变通方法是好的。f4t66c6m2#
在我的特殊情况下，这个确切的错误来自一个完整的驱动器。后台备份用临时文件填满了硬盘。
在以前的生产系统中，对于持续生成文件的长时间运行的任务，我将每分钟监视空闲驱动器空间的数量。如果它变低了，它会发出警报，这样它就可以被修复，如果它变到1GB空闲，它就会退出。最好退出1GB的免费而不是0GB的免费，这真的可以打破系统上运行的所有其他东西。这是牺牲一个任务（无论如何都注定要退出）或整个系统之间的选择。