mxnet.ndarray.contrib.boolean_mask running on gpu arrays randomly throws an CUDA illegal memory accessed error

[kalpitdixit]

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 : c4ea674
----------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
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 "", 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::allocatormxnet::engine::Var* > const&, std::vector<mxnet::engine::Var*, std::allocatormxnet::engine::Var* > const&, std::vector<mxnet::Resource, std::allocatormxnet::Resource > const&, std::vector<mxnet::NDArray*, std::allocatormxnet::NDArray* > const&, std::vector<mxnet::NDArray*, std::allocatormxnet::NDArray* > const&, std::vector<unsigned int, std::allocator > const&, std::vector<mxnet::OpReqType, std::allocatormxnet::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::allocatormxnet::engine::Var* > const&, std::vector<mxnet::engine::Var*, std::allocatormxnet::engine::Var* > const&, std::vector<mxnet::Resource, std::allocatormxnet::Resource > const&, std::vector<mxnet::NDArray*, std::allocatormxnet::NDArray* > const&, std::vector<mxnet::NDArray*, std::allocatormxnet::NDArray* > const&, std::vector<unsigned int, std::allocator > const&, std::vector<mxnet::OpReqType, std::allocatormxnet::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.)

What have you tried to solve it?

[mxnet-label-bot]

Hey, this is the MXNet Label Bot.
Thank you for submitting the issue! I will try and suggest some labels so that the appropriate MXNet community members can help resolve it.
Here are my recommended labels: Cuda, Bug

[leleamol]

@mxnet-label-bot add [Cuda, Bug, NDArray]

[Jerryzcn]

hey could u provide the code to reproduce it?

[wkcn]

There was a bug in boolean_mask of MXNet 1.5. #15175
Could you please try the latest MXNet, such as MXNet 1.6?

If it does not work too, please provide a minimum reproduce example. Thank you!