kalpitdixit opened a new issue #15283: mxnet.ndarray.contrib.boolean_mask running on gpu arrays randomly throws an CUDA illegal memory accessed error URL: https://github.com/apache/incubator-mxnet/issues/15283 ## Description mxnet.ndarray.contrib.boolean_mask running on gpu arrays randomly throws an error after a few iterations. "Check failed: e == cudaSuccess: CUDA: an illegal memory access was encountered (Brief description of the problem in no more than 2 sentences.)" ## Environment info (Required) ----------Python Info---------- Version : 3.5.2 Compiler : GCC 5.4.0 20160609 Build : ('default', 'Nov 12 2018 13:43:14') Arch : ('64bit', 'ELF') ------------Pip Info----------- Version : 18.0 Directory : /usr/local/lib/python3.5/dist-packages/pip ----------MXNet Info----------- Version : 1.5.0 Directory : /usr/local/lib/python3.5/dist-packages/mxnet Commit Hash : c4ea674ed6b0508687e27106f0fd74a36879d816 ----------System Info---------- Platform : Linux-4.4.0-1074-aws-x86_64-with-Ubuntu-16.04-xenial system : Linux node : ip-172-31-89-232 release : 4.4.0-1074-aws version : #84-Ubuntu SMP Thu Dec 6 08:57:58 UTC 2018 ----------Hardware Info---------- machine : x86_64 processor : x86_64 Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian CPU(s): 8 On-line CPU(s) list: 0-7 Thread(s) per core: 2 Core(s) per socket: 4 Socket(s): 1 NUMA node(s): 1 Vendor ID: GenuineIntel CPU family: 6 Model: 79 Model name: Intel(R) Xeon(R) CPU E5-2686 v4 @ 2.30GHz Stepping: 1 CPU MHz: 2702.320 CPU max MHz: 3000.0000 CPU min MHz: 1200.0000 BogoMIPS: 4600.13 Hypervisor vendor: Xen Virtualization type: full L1d cache: 32K L1i cache: 32K L2 cache: 256K L3 cache: 46080K NUMA node0 CPU(s): 0-7 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc aperfmperf pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single kaiser fsgsbase bmi1 hle avx2 smep bmi2 erms invpcid rtm rdseed adx xsaveopt ----------Network Test---------- Setting timeout: 10 Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0020 sec, LOAD: 0.5351 sec. Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.0247 sec, LOAD: 0.1683 sec. Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 0.0564 sec, LOAD: 0.4622 sec. Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0030 sec, LOAD: 0.0563 sec. Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.0831 sec, LOAD: 0.4007 sec. Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0051 sec, LOAD: 0.0713 sec. Package used (Python/R/Scala/Julia): Python 3.5.2 ## Error Message: Traceback (most recent call last): File "train_span_based_ner_model.py", line 186, in <module> main() File "train_span_based_ner_model.py", line 131, in main config.context)) File "/efs/users/kddixit/code/ComprehendModelCommons_land/ComprehendMultiTask/src/comprehend_multi_task/model/span_based_ner_model.py", line 378, in forward cand_span_ex_num = boolean_mask(cand_span_ex_num, cand_span_valid) # [num_candidates_in_batch] # ncb File "<string>", line 51, in boolean_mask File "/usr/local/lib/python3.5/dist-packages/mxnet/_ctypes/ndarray.py", line 92, in _imperative_invoke ctypes.byref(out_stypes))) File "/usr/local/lib/python3.5/dist-packages/mxnet/base.py", line 253, in check_call raise MXNetError(py_str(_LIB.MXGetLastError())) mxnet.base.MXNetError: [23:27:27] /home/travis/build/dmlc/mxnet-distro/mxnet-build/3rdparty/mshadow/mshadow/./stream_gpu-inl.h:62: Check failed: e == cudaSuccess: CUDA: an illegal memory access was encountered Stack trace: [bt] (0) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x4ac86b) [0x7efe949ab86b] [bt] (1) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x25a7d72) [0x7efe96aa6d72] [bt] (2) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(mxnet::imperative::PushOperator(mxnet::OpStatePtr const&, nnvm::Op const*, nnvm::NodeAttrs const&, mxnet::Context const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::Resource, std::allocator<mxnet::Resource> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<unsigned int, std::allocator<unsigned int> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, mxnet::DispatchMode)::{lambda(mxnet::RunContext, mxnet::engine::CallbackOnComplete)#3}::operator()(mxnet::RunContext, mxnet::engine::CallbackOnComplete) const+0x816) [0x7efe96b5acc6] [bt] (3) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(std::_Function_handler<void (mxnet::RunContext), mxnet::imperative::PushOperator(mxnet::OpStatePtr const&, nnvm::Op const*, nnvm::NodeAttrs const&, mxnet::Context const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::Resource, std::allocator<mxnet::Resource> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<unsigned int, std::allocator<unsigned int> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, mxnet::DispatchMode)::{lambda(mxnet::RunContext)#4}>::_M_invoke(std::_Any_data const&, mxnet::RunContext)+0x5d) [0x7efe96b5ae6d] [bt] (4) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x25a6b74) [0x7efe96aa5b74] [bt] (5) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x25b4509) [0x7efe96ab3509] [bt] (6) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x25b7970) [0x7efe96ab6970] [bt] (7) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x25b7c06) [0x7efe96ab6c06] [bt] (8) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x25b2d14) [0x7efe96ab1d14] [23:27:28] src/resource.cc:279: Ignore CUDA Error [23:27:28] src/storage/./pooled_storage_manager.h:97: CUDA: an illegal memory access was encountered Stack trace: [bt] (0) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x4ac86b) [0x7efe949ab86b] [bt] (1) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x2e539f7) [0x7efe973529f7] [bt] (2) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x2e55b7b) [0x7efe97354b7b] [bt] (3) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x2e5cdc4) [0x7efe9735bdc4] [bt] (4) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x2e61808) [0x7efe97360808] [bt] (5) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x25a686b) [0x7efe96aa586b] [bt] (6) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x25b4509) [0x7efe96ab3509] [bt] (7) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x25bec2a) [0x7efe96abdc2a] [bt] (8) /usr/local/lib/python3.5/dist-packages/mxnet/libmxnet.so(+0x25a784e) [0x7efe96aa684e] ## Minimum reproducible example (If you are using your own code, please provide a short script that reproduces the error. Otherwise, please provide link to the existing example.) ## Steps to reproduce (Paste the commands you ran that produced the error.) 1. 2. ## What have you tried to solve it? 1. 2.
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