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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2018/12/27 08:03:47 UTC
[GitHub] MyYaYa opened a new issue #13734: gluon.utils.split_and_load cause
cuda initialization error
MyYaYa opened a new issue #13734: gluon.utils.split_and_load cause cuda initialization error
URL: https://github.com/apache/incubator-mxnet/issues/13734
Note: Providing complete information in the most concise form is the best way to get help. This issue template serves as the checklist for essential information to most of the technical issues and bug reports. For non-technical issues and feature requests, feel free to present the information in what you believe is the best form.
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## Description
I use gluon.utils.split_and_load for multi gpus data loading. and I get a CUDA ERROR.
## Environment info (Required)
```
What to do:
1. Download the diagnosis script from https://raw.githubusercontent.com/apache/incubator-mxnet/master/tools/diagnose.py
2. Run the script using `python diagnose.py` and paste its output here.
----------Python Info----------
Version : 3.6.7
Compiler : GCC 4.9.2
Build : ('default', 'Dec 8 2018 13:38:58')
Arch : ('64bit', 'ELF')
------------Pip Info-----------
Version : 18.1
Directory : /usr/local/lib/python3.6/site-packages/pip
----------MXNet Info-----------
Version : 1.3.1
Directory : /usr/local/lib/python3.6/site-packages/mxnet
Commit Hash : 19c501680183237d52a862e6ae1dc4ddc296305b
----------System Info----------
Platform : Linux-4.9.0-0.bpo.6-amd64-x86_64-with-debian-8.9
system : Linux
node : n22-146-038
release : 4.9.0-0.bpo.6-amd64
version : #1 SMP Debian 4.9.88-1+deb9u1~bpo8+1 (2018-05-13)
----------Hardware Info----------
machine : x86_64
processor :
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 64
On-line CPU(s) list: 0-63
Thread(s) per core: 2
Core(s) per socket: 16
Socket(s): 2
NUMA node(s): 2
Vendor ID: GenuineIntel
CPU family: 6
Model: 85
Model name: Intel(R) Xeon(R) Gold 6130 CPU @ 2.10GHz
Stepping: 4
CPU MHz: 2799.957
CPU max MHz: 3700.0000
CPU min MHz: 1000.0000
BogoMIPS: 4201.56
Virtualization: VT-x
L1d cache: 32K
L1i cache: 32K
L2 cache: 1024K
L3 cache: 22528K
NUMA node0 CPU(s): 0-15,32-47
NUMA node1 CPU(s): 16-31,48-63
----------Network Test----------
Setting timeout: 10
Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.1624 sec, LOAD: 1.1204 sec.
Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 1.2265 sec, LOAD: 3.4280 sec.
Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 1.6494 sec, LOAD: 4.4747 sec.
Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.1920 sec, LOAD: 2.4969 sec.
Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.1085 sec, LOAD: 4.3755 sec.
Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.4053 sec, LOAD: 3.9252 sec.
```
## Error Message:
src/engine/threaded_engine_perdevice.cc:99: Ignore CUDA Error [10:22:36] /root/mxnet-rdma/3rdparty/mshadow/mshadow/./tensor_gpu-inl.h:35: Check failed: e == cudaSuccess CUDA: initialization error
Stack trace returned 10 entries:
[bt] (0) /usr/local/lib/python3.6/site-packages/mxnet-1.3.1-py3.6.egg/mxnet/libmxnet.so(dmlc::StackTrace(unsigned long)+0x49) [0x7fb1a83a3e59]
[bt] (1) /usr/local/lib/python3.6/site-packages/mxnet-1.3.1-py3.6.egg/mxnet/libmxnet.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x1f) [0x7fb1a83a435f]
[bt] (2) /usr/local/lib/python3.6/site-packages/mxnet-1.3.1-py3.6.egg/mxnet/libmxnet.so(void mshadow::SetDevice<mshadow::gpu>(int)+0xa8) [0x7fb1ab741f98]
[bt] (3) /usr/local/lib/python3.6/site-packages/mxnet-1.3.1-py3.6.egg/mxnet/libmxnet.so(mxnet::engine::ThreadedEnginePerDevice::PushToExecute(mxnet::engine::OprBlock*, bool)+0x4d) [0x7fb1ab74a2ad]
[bt] (4) /usr/local/lib/python3.6/site-packages/mxnet-1.3.1-py3.6.egg/mxnet/libmxnet.so(mxnet::engine::ThreadedEngine::PushAsync(std::function<void (mxnet::RunContext, mxnet::engine::CallbackOnComplete)>, mxnet::Context, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, mxnet::FnProperty, int, char const*, bool)+0x17b) [0x7fb1ab73811b]
[bt] (5) /usr/local/lib/python3.6/site-packages/mxnet-1.3.1-py3.6.egg/mxnet/libmxnet.so(mxnet::engine::ThreadedEngine::DeleteVariable(std::function<void (mxnet::RunContext)>, mxnet::Context, mxnet::engine::Var*)+0x15f) [0x7fb1ab737e7f]
[bt] (6) /usr/local/lib/python3.6/site-packages/mxnet-1.3.1-py3.6.egg/mxnet/libmxnet.so(mxnet::NDArray::Chunk::~Chunk()+0x341) [0x7fb1ab1f8bb1]
[bt] (7) /usr/local/lib/python3.6/site-packages/mxnet-1.3.1-py3.6.egg/mxnet/libmxnet.so(std::_Sp_counted_base<(__gnu_cxx::_Lock_policy)2>::_M_release()+0x46) [0x7fb1a83a68b6]
[bt] (8) /usr/local/lib/python3.6/site-packages/mxnet-1.3.1-py3.6.egg/mxnet/libmxnet.so(MXNDArrayFree+0x54) [0x7fb1ab7b7074]
[bt] (9) /usr/local/lib/python3.6/lib-dynload/_ctypes.cpython-36m-x86_64-linux-gnu.so(ffi_call_unix64+0x4c) [0x7fb260d409e8]
## Minimum reproducible example
`
data = gluon.utils.split_and_load(data, context=[mx.gpu(0), mx.gpu(1), mx.gpu(2), mx.gpu(3)])
`
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