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. For Q & A and discussion, please start a discussion thread at https://discuss.mxnet.io ## 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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