Sampling fails on mxnet==1.5.0 on Linux?

[lostella]

Description

Some random sampling functions seem not to be working on mxnet version 1.5.0 on Linux.

Environment info (Required)

----------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      : 19.2.3
Directory    : /usr/local/lib/python3.7/site-packages/pip
----------MXNet Info-----------
Version      : 1.5.0
Directory    : /usr/local/lib/python3.7/site-packages/mxnet
Commit Hash   : 75a9e187d00a8b7ebc71412a02ed0e3ae489d91f
Library      : ['/usr/local/lib/python3.7/site-packages/mxnet/libmxnet.so']
Build features:
✖ CUDA
✖ CUDNN
✖ NCCL
✖ CUDA_RTC
✖ TENSORRT
✔ CPU_SSE
✔ CPU_SSE2
✔ CPU_SSE3
✔ CPU_SSE4_1
✔ CPU_SSE4_2
✖ CPU_SSE4A
✔ CPU_AVX
✖ CPU_AVX2
✖ OPENMP
✖ SSE
✔ F16C
✖ JEMALLOC
✖ BLAS_OPEN
✖ BLAS_ATLAS
✖ BLAS_MKL
✖ BLAS_APPLE
✔ LAPACK
✖ MKLDNN
✔ OPENCV
✖ CAFFE
✖ PROFILER
✔ DIST_KVSTORE
✖ CXX14
✖ INT64_TENSOR_SIZE
✔ SIGNAL_HANDLER
✖ DEBUG
----------System Info----------
Platform     : Linux-4.9.184-linuxkit-x86_64-with-debian-10.0
system       : Linux
node         : 393443f5954f
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: 0.0416 sec, LOAD: 0.6791 sec.
Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.0579 sec, LOAD: 1.1694 sec.
Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 0.0602 sec, LOAD: 0.8697 sec.
Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.0628 sec, LOAD: 1.0556 sec.
Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0343 sec, LOAD: 0.8659 sec.
Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0030 sec, LOAD: 0.1486 sec.
----------Environment----------

I'm using Python, pip-freeze gives:

certifi==2019.6.16
chardet==3.0.4
graphviz==0.8.4
idna==2.8
mxnet==1.5.0
numpy==1.17.2
requests==2.22.0
urllib3==1.25.3

Error Message:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<string>", line 68, in sample_normal
  File "/usr/local/lib/python3.7/site-packages/mxnet/_ctypes/ndarray.py", line 92, in _imperative_invoke
    ctypes.byref(out_stypes)))
  File "/usr/local/lib/python3.7/site-packages/mxnet/base.py", line 253, in check_call
    raise MXNetError(py_str(_LIB.MXGetLastError()))
mxnet.base.MXNetError: vector::_M_range_insert

Minimum reproducible example

import mxnet as mx
s = mx.nd.sample_normal(mu=mx.nd.array([10.0]), sigma=mx.nd.array([0.5]))

Edit: the problem seems to occur on vanilla mxnet==1.5.0 as well; edited the issue description above.

[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 label(s): Build

[lostella]

This did not occur in mxnet_mkl-1.4.1, and appears to be still occurring in mxnet_mkl-1.6.0b20190909

[ChaiBapchya]

@mxnet-label-bot add [Operator, Bug]

[ChaiBapchya]

Thanks for pointing out.
I was able to reproduce this issue for pip install mxnet==1.5.0, pip install mxnet==1.6.0

No error for pip install mxnet==1.4.0
So likely introduced in patch release 1.4.1

[lostella]

No error for pip install mxnet==1.4.0
So likely introduced in patch release 1.4.1

I was not able to reproduce on 1.4.1, so probably introduced in 1.5.0

[reminisce]

Fixed in #16139.

[lostella]

@reminisce does the fix also fix sampling other than sample_normal? All other sampling functions also raise the same error on 1.5.0:

• s = mx.nd.sample_uniform(low=mx.nd.array([10.0]), high=mx.nd.array([11.5]))
• s = mx.nd.sample_negative_binomial(k=mx.nd.array([3]), p=mx.nd.array([0.5]))
• s = mx.nd.sample_poisson(lam=mx.nd.array([1.5]))
• ...

[asmushetzel]

The fix provided does fix all the samplers (i.e. for all distributions).