GSanchis opened a new issue #10971: Segmentation fault with custom operator URL: https://github.com/apache/incubator-mxnet/issues/10971 ## Description Hi all. I've just recently stumbled into a segmentation fault, which I can't really explain. Creating a new operator (even the softmax in the example) leads to it. ## Environment info (Required) ``` ----------Python Info---------- Version : 3.5.2 Compiler : GCC 5.4.0 20160609 Build : ('default', 'Nov 17 2016 17:05:23') Arch : ('64bit', 'ELF') ------------Pip Info----------- Version : 9.0.3 Directory : /home/exx/.local/lib/python3.5/site-packages/pip ----------MXNet Info----------- Version : 1.2.0 Directory : /home/exx/.local/lib/python3.5/site-packages/mxnet Commit Hash : b2ccd34ad2801b6c87c957c28ad718562a4c5b6e ----------System Info---------- Platform : Linux-4.4.0-92-generic-x86_64-with-Ubuntu-16.04-xenial system : Linux node : tensorflow release : 4.4.0-92-generic version : #115-Ubuntu SMP Thu Aug 10 09:04:33 UTC 2017 ----------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): 32 On-line CPU(s) list: 0-31 Thread(s) per core: 2 Core(s) per socket: 8 Socket(s): 2 NUMA node(s): 2 Vendor ID: GenuineIntel CPU family: 6 Model: 79 Model name: Intel(R) Xeon(R) CPU E5-2620 v4 @ 2.10GHz Stepping: 1 CPU MHz: 1268.449 CPU max MHz: 3000.0000 CPU min MHz: 1200.0000 BogoMIPS: 4191.30 Virtualization: VT-x L1d cache: 32K L1i cache: 32K L2 cache: 256K L3 cache: 20480K NUMA node0 CPU(s): 0-7,16-23 NUMA node1 CPU(s): 8-15,24-31 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc aperfmperf eagerfpu pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch epb intel_pt tpr_shadow vnmi flexpriority ept vpid fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm rdseed adx smap xsaveopt cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts ----------Network Test---------- Setting timeout: 10 Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0764 sec, LOAD: 0.0217 sec. Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0028 sec, LOAD: 0.2659 sec. Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.0201 sec, LOAD: 0.3272 sec. Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 0.1216 sec, LOAD: 0.3743 sec. Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0022 sec, LOAD: 0.4305 sec. Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.2415 sec, LOAD: 0.3285 sec. ``` I'm using mxnet-cu80 for Python 3.5. ## Build info (Required if built from source) Downloaded via `pip install --user mxnet-cu80==1.2.0b20180516`. I was using mxnet-cu80-1.0.0, but ran into this same problem, and tried updating. ## Error Message: ``` Segmentation fault: 11 Stack trace returned 10 entries: [bt] (0) /home/exx/.local/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x331d6a) [0x7f3b7618fd6a] [bt] (1) /home/exx/.local/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x2968b06) [0x7f3b787c6b06] [bt] (2) /lib/x86_64-linux-gnu/libc.so.6(+0x354b0) [0x7f3be81064b0] [bt] (3) /home/exx/.local/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x4b7589) [0x7f3b76315589] [bt] (4) /home/exx/.local/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x4b8655) [0x7f3b76316655] [bt] (5) /home/exx/.local/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x684bf8a) [0x7f3b7c6a9f8a] [bt] (6) /home/exx/.local/lib/python3.5/site-packages/mxnet/libmxnet.so(MXSymbolCreateAtomicSymbol+0x6e1) [0x7f3b782e66a1] [bt] (7) /usr/lib/python3.5/lib-dynload/_ctypes.cpython-35m-x86_64-linux-gnu.so(ffi_call_unix64+0x4c) [0x7f3be6ef9e20] [bt] (8) /usr/lib/python3.5/lib-dynload/_ctypes.cpython-35m-x86_64-linux-gnu.so(ffi_call+0x2eb) [0x7f3be6ef988b] [bt] (9) /usr/lib/python3.5/lib-dynload/_ctypes.cpython-35m-x86_64-linux-gnu.so(_ctypes_callproc+0x49a) [0x7f3be6ef401a] ## Minimum reproducible example I believe this is the core of what is leading me to the error: ``` user_embed = mx.symbol.Embedding(name="user_embed", data=user, input_dim=max_users, output_dim=embed_size) item_embed = mx.symbol.Embedding(name="item_embed", data=item, input_dim=max_items, output_dim=embed_size) user = mx.symbol.L2Normalization(user_embed) item = mx.symbol.L2Normalization(item_embed) dot = user * item dot = mx.symbol.sum_axis(dot, axis=1) cosine = mx.symbol.Flatten(dot) pred = mx.symbol.Custom(data=cosine, label=[score], name='ce', op_type='softmax') ``` The `softmax` operator is implemented as in the example (copy-paste).
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