lostella opened a new issue #17868: Cholesky factorization crashes on MXNet 1.6.0 on Linux URL: https://github.com/apache/incubator-mxnet/issues/17868 ## Description Cholesky factorization crashes on MXNet 1.6.0 on Linux, instead of raising an exception like it does on macOS. ### Error Message ``` terminate called after throwing an instance of 'dmlc::Error' what(): [14:01:07] src/operator/tensor/./../linalg_impl.h:691: Check failed: ret == 0 (2 vs. 0) : spotrf failed in lapack on cpu. This may happen when the input matrix is either not symmetric or not positive definite. Stack trace: [bt] (0) /usr/local/lib/python3.7/site-packages/mxnet/libmxnet.so(+0x307d3b) [0x7f78ae7a5d3b] [bt] (1) /usr/local/lib/python3.7/site-packages/mxnet/libmxnet.so(+0x314ad0b) [0x7f78b15e8d0b] Aborted ``` ## To Reproduce ```python import mxnet as mx import numpy as np A = mx.nd.array( [[[1, 0], [0, -2]], [[1, 0], [0, 4]]], ctx=mx.cpu(), dtype=np.float32 ) try: L = mx.nd.linalg.potrf(A) print(L) except mx.MXNetError as err: print("maybe matrix is not symmetric and positive definite?") ``` ## Environment ``` ----------Python Info---------- Version : 3.7.4 Compiler : GCC 8.3.0 Build : ('default', 'Aug 14 2019 12:09:51') Arch : ('64bit', 'ELF') ------------Pip Info----------- Version : 20.0.2 Directory : /usr/local/lib/python3.7/site-packages/pip ----------MXNet Info----------- Version : 1.6.0 Directory : /usr/local/lib/python3.7/site-packages/mxnet Num GPUs : 0 Commit Hash : 6eec9da55c5096079355d1f1a5fa58dcf35d6752 ----------System Info---------- Platform : Linux-4.9.184-linuxkit-x86_64-with-debian-10.0 system : Linux node : e5d687384f3d release : 4.9.184-linuxkit version : #1 SMP Tue Jul 2 22:58:16 UTC 2019 ----------Hardware Info---------- machine : x86_64 processor : Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian Address sizes: 39 bits physical, 48 bits virtual CPU(s): 2 On-line CPU(s) list: 0,1 Thread(s) per core: 1 Core(s) per socket: 1 Socket(s): 2 Vendor ID: GenuineIntel CPU family: 6 Model: 142 Model name: Intel(R) Core(TM) i7-7660U CPU @ 2.50GHz Stepping: 9 CPU MHz: 2500.000 BogoMIPS: 4992.00 L1d cache: 32K L1i cache: 32K L2 cache: 256K L3 cache: 4096K Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht pbe syscall nx pdpe1gb lm constant_tsc rep_good nopl xtopology nonstop_tsc pni pclmulqdq dtes64 ds_cpl ssse3 sdbg fma cx16 xtpr pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch kaiser fsgsbase bmi1 hle avx2 bmi2 erms rtm xsaveopt arat ----------Network Test---------- Setting timeout: 10 Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0633 sec, LOAD: 1.5485 sec. Timing for GluonNLP GitHub: https://github.com/dmlc/gluon-nlp, DNS: 0.0040 sec, LOAD: 0.8173 sec. Timing for GluonNLP: http://gluon-nlp.mxnet.io, DNS: 1.0898 sec, LOAD: 0.8475 sec. Timing for D2L: http://d2l.ai, DNS: 0.0738 sec, LOAD: 1.3540 sec. Timing for D2L (zh-cn): http://zh.d2l.ai, DNS: 0.0777 sec, LOAD: 0.5348 sec. Timing for FashionMNIST: https://repo.mxnet.io/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.1271 sec, LOAD: 1.5946 sec. Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0576 sec, LOAD: 1.1366 sec. Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0450 sec, LOAD: 0.2497 sec. ```
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