Certain libraries' method invocations result in `Illegal Instruction (core dumped)` #8373

1kastner · 2019-03-04T21:33:16Z

Current Behavior

When using several libraries, certain operations like some method invocations result in Illegal Instruction (core dumped). Then python immediately closes without any error trace. The only way how to avoid this has been to use old conda packages instead of the new ones.
Definitely problematic are matplotib and scikit-learn but I bet more libraries could create issues in my context.
The issue only happens on our local cluster, not when running the identical code on e.g. a Windows machine.

Steps to Reproduce

One of the issues is:

import matplotlib.pyplot as plt
import numpy as np
t = np.arange(0.0, 2.0, 0.01)
s = 1 + np.sin(2*np.pi*t)
plt.plot(t, s)

That was discussed at matplotlib/matplotlib#13458 and later at jupyter/docker-stacks#811 .
The problem is not matplotlib but which binary version in the end is executed on my computer.

Expected Behavior

Not crash.

Environment Information

See the docker image jupyter/scipy-notebook described at https://github.com/jupyter/docker-stacks/blob/master/scipy-notebook/Dockerfile and its parents.

If it is of interest, tomorrow I can add the details listed below.

`conda info`

     active environment : None
       user config file : /home/jovyan/.condarc
 populated config files : /opt/conda/.condarc
          conda version : 4.6.2
    conda-build version : not installed
         python version : 3.6.8.final.0
       base environment : /opt/conda  (writable)
           channel URLs : https://conda.anaconda.org/conda-forge/linux-64
                          https://conda.anaconda.org/conda-forge/noarch
                          https://repo.anaconda.com/pkgs/main/linux-64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/free/linux-64
                          https://repo.anaconda.com/pkgs/free/noarch
                          https://repo.anaconda.com/pkgs/r/linux-64
                          https://repo.anaconda.com/pkgs/r/noarch
          package cache : /opt/conda/pkgs
                          /home/jovyan/.conda/pkgs
       envs directories : /opt/conda/envs
                          /home/jovyan/.conda/envs
               platform : linux-64
             user-agent : conda/4.6.2 requests/2.21.0 CPython/3.6.8 Linux/4.9.125-linuxkit ubuntu/18.04.1 glibc/2.27
                UID:GID : 1000:100
             netrc file : None
           offline mode : False

`conda config --show-sources`

==> /opt/conda/.condarc <==
auto_update_conda: False
channels:
  - conda-forge
  - defaults
show_channel_urls: True

`conda list --show-channel-urls`

# packages in environment at /opt/conda:
#
# Name                    Version                   Build  Channel
alembic                   0.9.9                      py_0    conda-forge
asn1crypto                0.24.0                py36_1003    conda-forge
async_generator           1.10                       py_0    conda-forge
attrs                     18.2.0                     py_0    conda-forge
backcall                  0.1.0                      py_0    conda-forge
beautifulsoup4            4.6.3                 py36_1000    conda-forge
blas                      1.1                    openblas    conda-forge
bokeh                     0.13.0                py36_1000    conda-forge
bzip2                     1.0.6                h470a237_2    conda-forge
ca-certificates           2018.11.29           ha4d7672_0    conda-forge
certifi                   2018.11.29            py36_1000    conda-forge
cffi                      1.11.5          py36h9745a5d_1001    conda-forge
chardet                   3.0.4                 py36_1003    conda-forge
cloudpickle               0.5.6                      py_0    conda-forge
conda                     4.6.2                    py36_0    conda-forge
conda-env                 2.6.0                         1    conda-forge
configurable-http-proxy   3.1.0                   node8_1    conda-forge
cryptography              2.4.2            py36h1ba5d50_0    defaults
cycler                    0.10.0                     py_1    conda-forge
cython                    0.28.5          py36hf484d3e_1000    conda-forge
cytoolz                   0.9.0.1         py36h14c3975_1001    conda-forge
dask-core                 1.1.1                      py_0    conda-forge
dbus                      1.13.2               h714fa37_1    defaults
decorator                 4.3.0                      py_0    conda-forge
dill                      0.2.9                    py36_0    conda-forge
entrypoints               0.3                   py36_1000    conda-forge
expat                     2.2.5             hf484d3e_1002    conda-forge
fastcache                 1.0.2           py36h14c3975_1001    conda-forge
fontconfig                2.13.1            h2176d3f_1000    conda-forge
freetype                  2.9.1             h94bbf69_1005    conda-forge
gettext                   0.19.8.1          h9745a5d_1001    conda-forge
glib                      2.56.2            had28632_1001    conda-forge
gmp                       6.1.2                hfc679d8_0    conda-forge
gmpy2                     2.0.8           py36hb20f59a_1002    conda-forge
gst-plugins-base          1.14.0               hbbd80ab_1    defaults
gstreamer                 1.14.0               hb453b48_1    defaults
h5py                      2.7.1                    py36_3    conda-forge
hdf5                      1.10.1                        2    conda-forge
icu                       58.2              hf484d3e_1000    conda-forge
idna                      2.8                   py36_1000    conda-forge
imageio                   2.4.1                 py36_1000    conda-forge
ipykernel                 5.1.0           py36h24bf2e0_1002    conda-forge
ipython                   7.2.0           py36h24bf2e0_1000    conda-forge
ipython_genutils          0.2.0                      py_1    conda-forge
ipywidgets                7.4.2                      py_0    conda-forge
jedi                      0.13.2                py36_1000    conda-forge
jinja2                    2.10                       py_1    conda-forge
jpeg                      9c                h14c3975_1001    conda-forge
jsonschema                3.0.0a3               py36_1000    conda-forge
jupyter_client            5.2.4                      py_0    conda-forge
jupyter_core              4.4.0                      py_0    conda-forge
jupyterhub                0.9.4                 py36_1000    conda-forge
jupyterlab                0.35.4                   py36_0    conda-forge
jupyterlab_server         0.2.0                      py_0    conda-forge
kiwisolver                1.0.1           py36h6bb024c_1002    conda-forge
krb5                      1.16.1               h173b8e3_7    defaults
libcurl                   7.63.0            h20c2e04_1000    defaults
libedit                   3.1.20170329         haf1bffa_1    conda-forge
libffi                    3.2.1                hfc679d8_5    conda-forge
libgcc                    7.2.0                h69d50b8_2    conda-forge
libgcc-ng                 7.3.0                hdf63c60_0    conda-forge
libgfortran               3.0.0                         1    conda-forge
libgfortran-ng            7.2.0                hdf63c60_3    conda-forge
libiconv                  1.15              h14c3975_1004    conda-forge
libpng                    1.6.36            h84994c4_1000    conda-forge
libprotobuf               3.6.1             hdbcaa40_1000    conda-forge
libsodium                 1.0.16               h470a237_1    conda-forge
libssh2                   1.8.0                         1    conda-forge
libstdcxx-ng              7.3.0                hdf63c60_0    conda-forge
libtiff                   4.0.10            h648cc4a_1001    conda-forge
libuuid                   2.32.1            h14c3975_1000    conda-forge
libxcb                    1.13              h14c3975_1002    conda-forge
libxml2                   2.9.8             h143f9aa_1005    conda-forge
llvmlite                  0.23.0                   py36_1    conda-forge
mako                      1.0.7                      py_1    conda-forge
markupsafe                1.1.0           py36h14c3975_1000    conda-forge
matplotlib                2.2.3            py36h8a2030e_1    conda-forge
matplotlib-base           2.2.3            py36h60b886d_1    conda-forge
mistune                   0.8.4           py36h14c3975_1000    conda-forge
mpc                       1.1.0             hb20f59a_1006    conda-forge
mpfr                      4.0.1             ha14ba45_1000    conda-forge
mpmath                    1.1.0                      py_0    conda-forge
nbconvert                 5.3.1                      py_1    conda-forge
nbformat                  4.4.0                      py_1    conda-forge
ncurses                   6.1                  hfc679d8_2    conda-forge
networkx                  2.2                        py_1    conda-forge
nodejs                    8.10.0                        0    conda-forge
notebook                  5.7.2                 py36_1000    conda-forge
numba                     0.38.1                   py36_0    conda-forge
numexpr                   2.6.9           py36h637b7d7_1000    conda-forge
numpy                     1.13.3          py36_blas_openblash1522bff_1201  [blas_openblas]  conda-forge
olefile                   0.46                       py_0    conda-forge
openblas                  0.3.3             h9ac9557_1001    conda-forge
openssl                   1.1.1a            h14c3975_1000    conda-forge
packaging                 19.0                       py_0    conda-forge
pamela                    0.3.0                   py_1001    conda-forge
pandas                    0.23.4          py36h637b7d7_1000    conda-forge
pandoc                    2.5                           0    conda-forge
pandocfilters             1.4.2                      py_1    conda-forge
parso                     0.3.1                      py_0    conda-forge
patsy                     0.5.1                      py_0    conda-forge
pcre                      8.42                 h439df22_0    defaults
pexpect                   4.6.0                 py36_1000    conda-forge
pickleshare               0.7.5                 py36_1000    conda-forge
pillow                    5.4.1           py36h00a061d_1000    conda-forge
pip                       19.0.1                   py36_0    conda-forge
prometheus_client         0.5.0                      py_0    conda-forge
prompt_toolkit            2.0.7                      py_0    conda-forge
protobuf                  3.6.1           py36hf484d3e_1001    conda-forge
pthread-stubs             0.4               h14c3975_1001    conda-forge
ptyprocess                0.6.0                 py36_1000    conda-forge
pycosat                   0.6.3           py36h14c3975_1001    conda-forge
pycparser                 2.19                       py_0    conda-forge
pycurl                    7.43.0.2         py36h1ba5d50_0    defaults
pygments                  2.3.1                      py_0    conda-forge
pyopenssl                 19.0.0                   py36_0    conda-forge
pyparsing                 2.3.1                      py_0    conda-forge
pyrsistent                0.14.9          py36h14c3975_1000    conda-forge
pysocks                   1.6.8                 py36_1002    conda-forge
python                    3.6.8                h0371630_0    defaults
python-dateutil           2.7.5                      py_0    conda-forge
python-editor             1.0.3                      py_0    conda-forge
python-oauth2             1.0.1                    py36_0    conda-forge
pytz                      2018.9                     py_0    conda-forge
pywavelets                1.0.1           py36h3010b51_1000    conda-forge
pyyaml                    3.13            py36h14c3975_1001    conda-forge
pyzmq                     17.1.2          py36h6afc9c9_1001    conda-forge
readline                  7.0                  haf1bffa_1    conda-forge
requests                  2.21.0                py36_1000    conda-forge
ruamel_yaml               0.15.71         py36h14c3975_1000    conda-forge
scikit-image              0.14.2           py36hf484d3e_1    conda-forge
scikit-learn              0.20.2          py36_blas_openblashebff5e3_1400  [blas_openblas]  conda-forge
scipy                     1.1.0           py36_blas_openblash1522bff_1202  [blas_openblas]  conda-forge
seaborn                   0.9.0                      py_0    conda-forge
send2trash                1.5.0                      py_0    conda-forge
setuptools                40.7.1                   py36_0    conda-forge
sip                       4.18.1          py36hf484d3e_1000    conda-forge
six                       1.12.0                py36_1000    conda-forge
sqlalchemy                1.2.17           py36h14c3975_0    conda-forge
sqlite                    3.26.0               hb1c47c0_0    conda-forge
statsmodels               0.9.0           py36h3010b51_1000    conda-forge
sympy                     1.1.1                    py36_0    conda-forge
terminado                 0.8.1                 py36_1001    conda-forge
testpath                  0.4.2                 py36_1000    conda-forge
tini                      0.18.0               h470a237_1    conda-forge
tk                        8.6.9                ha92aebf_0    conda-forge
toolz                     0.9.0                      py_1    conda-forge
tornado                   5.1.1           py36h14c3975_1000    conda-forge
traitlets                 4.3.2                 py36_1000    conda-forge
urllib3                   1.24.1                py36_1000    conda-forge
vincent                   0.4.4                      py_1    conda-forge
wcwidth                   0.1.7                      py_1    conda-forge
webencodings              0.5.1                      py_1    conda-forge
wheel                     0.32.3                   py36_0    conda-forge
widgetsnbextension        3.4.2                 py36_1000    conda-forge
xlrd                      1.2.0                      py_0    conda-forge
xorg-libxau               1.0.8             h14c3975_1006    conda-forge
xorg-libxdmcp             1.1.2             h14c3975_1007    conda-forge
xz                        5.2.4                h470a237_1    conda-forge
yaml                      0.1.7                h470a237_1    conda-forge
zeromq                    4.2.5                hfc679d8_6    conda-forge
zlib                      1.2.11               h470a237_3    conda-forge

The text was updated successfully, but these errors were encountered:

mingwandroid · 2019-03-05T08:55:54Z

I believe this is because you are using Docker?

Within your docker, please issue cat /proc/cpu and paste the results here.

mingwandroid · 2019-03-05T12:13:49Z

I cannot reproduce this, can you give exact steps? Do I need to do some X11 forwarding in Docker somehow? Please assume I've only ever used Docker from the commandline.

I get:

---------------------------------------------------------------------------
TclError                                  Traceback (most recent call last)
<ipython-input-1-f8d1fb1b46c3> in <module>
      3 t = np.arange(0.0, 2.0, 0.01)
      4 s = 1 + np.sin(2*np.pi*t)
----> 5 plt.plot(t, s)

/opt/conda/lib/python3.6/site-packages/matplotlib/pyplot.py in plot(*args, **kwargs)
   3350 @_autogen_docstring(Axes.plot)
   3351 def plot(*args, **kwargs):
-> 3352     ax = gca()
   3353     # Deprecated: allow callers to override the hold state
   3354     # by passing hold=True|False

/opt/conda/lib/python3.6/site-packages/matplotlib/pyplot.py in gca(**kwargs)
    967     matplotlib.figure.Figure.gca : The figure's gca method.
    968     """
--> 969     return gcf().gca(**kwargs)
    970 
    971 # More ways of creating axes:

/opt/conda/lib/python3.6/site-packages/matplotlib/pyplot.py in gcf()
    584         return figManager.canvas.figure
    585     else:
--> 586         return figure()
    587 
    588 

/opt/conda/lib/python3.6/site-packages/matplotlib/pyplot.py in figure(num, figsize, dpi, facecolor, edgecolor, frameon, FigureClass, clear, **kwargs)
    531                                         frameon=frameon,
    532                                         FigureClass=FigureClass,
--> 533                                         **kwargs)
    534 
    535         if figLabel:

/opt/conda/lib/python3.6/site-packages/matplotlib/backend_bases.py in new_figure_manager(cls, num, *args, **kwargs)
    159         fig_cls = kwargs.pop('FigureClass', Figure)
    160         fig = fig_cls(*args, **kwargs)
--> 161         return cls.new_figure_manager_given_figure(num, fig)
    162 
    163     @classmethod

/opt/conda/lib/python3.6/site-packages/matplotlib/backends/_backend_tk.py in new_figure_manager_given_figure(cls, num, figure)
   1044         """
   1045         _focus = windowing.FocusManager()
-> 1046         window = Tk.Tk(className="matplotlib")
   1047         window.withdraw()
   1048 

/opt/conda/lib/python3.6/tkinter/__init__.py in __init__(self, screenName, baseName, className, useTk, sync, use)
   2021                 baseName = baseName + ext
   2022         interactive = 0
-> 2023         self.tk = _tkinter.create(screenName, baseName, className, interactive, wantobjects, useTk, sync, use)
   2024         if useTk:
   2025             self._loadtk()

TclError: no display name and no $DISPLAY environment variable

In [2]:                                                                                                                                                                                                                                       ```

1kastner · 2019-03-05T12:17:06Z

I believe this is because you are using Docker?

Within your docker, please issue cat /proc/cpu and paste the results here.

That results in cat: /proc/cpu: No such file or directory both when I run in in my docker container and when I run it on the virtual machine at my hand.

My problematic nesting is:
Some (protected) institutional cluster => Virtual Machine (which I have access to) => Docker

In other circumstances the same image works.

1kastner · 2019-03-05T12:21:05Z

I cannot reproduce this, can you give exact steps? Do I need to do some X11 forwarding in Docker somehow? Please assume I've only ever used Docker from the commandline.

I guess the simplest way of how to reproduce it is to run the following command:
docker run -p 8888:8888 jupyter/scipy-notebook
Then on the command line instructions show up of how to connect to the running instance.
Then you can create a new Jupyter Notebook and paste the commands I provided.
That should definitely work because then you have a matplotlib backend.

mingwandroid · 2019-03-05T12:31:17Z

We require SSE2 on Linux x86-64, I guess you don't have that? We cannot support really old CPUs, sorry. Here is my output from cat /proc/cpuinfo where everything works just fine:

processor	: 5
vendor_id	: GenuineIntel
cpu family	: 6
model		: 158
model name	: Intel(R) Core(TM) i9-8950HK CPU @ 2.90GHz
stepping	: 10
cpu MHz		: 2900.000
cache size	: 12288 KB
physical id	: 5
siblings	: 1
core id		: 0
cpu cores	: 1
apicid		: 5
initial apicid	: 5
fpu		: yes
fpu_exception	: yes
cpuid level	: 22
wp		: yes
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
bugs		: cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf
bogomips	: 5755.38
clflush size	: 64
cache_alignment	: 64
address sizes	: 39 bits physical, 48 bits virtual
power management:

1kastner · 2019-03-05T12:42:42Z

Ah, cpuinfo, I just blindly typed cpu. Here we go:

processor       : 0
vendor_id       : GenuineIntel
cpu family      : 6
model           : 85
model name      : Intel(R) Xeon(R) Gold 5118 CPU @ 2.30GHz
stepping        : 4
microcode       : 0x2000050
cpu MHz         : 2294.609
cache size      : 16896 KB
physical id     : 0
siblings        : 1
core id         : 0
cpu cores       : 1
apicid          : 0
initial apicid  : 0
fpu             : yes
fpu_exception   : yes
cpuid level     : 13
wp              : yes
flags           : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts mmx fxsr sse sse2 sssyscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts nopl xtopology tsc_reliable nonstop_tsc 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 ssbd ibrs ibpb stibp kaiser fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 invpcid rtm rdseed adx smapxsaveopt arat flush_l1d arch_capabilities
bugs            : cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf
bogomips        : 4589.21
clflush size    : 64
cache_alignment : 64
address sizes   : 42 bits physical, 48 bits virtual
power management:

processor       : 1
vendor_id       : GenuineIntel
cpu family      : 6
model           : 85
model name      : Intel(R) Xeon(R) Gold 5118 CPU @ 2.30GHz
stepping        : 4
microcode       : 0x2000050
cpu MHz         : 2294.609
cache size      : 16896 KB
physical id     : 2
siblings        : 1
core id         : 0
cpu cores       : 1
apicid          : 2
initial apicid  : 2
fpu             : yes
fpu_exception   : yes
cpuid level     : 13
wp              : yes
flags           : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts mmx fxsr sse sse2 sssyscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts nopl xtopology tsc_reliable nonstop_tsc 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 ssbd ibrs ibpb stibp kaiser fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 invpcid rtm rdseed adx smapxsaveopt arat flush_l1d arch_capabilities
bugs            : cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf
bogomips        : 4589.21
clflush size    : 64
cache_alignment : 64
address sizes   : 42 bits physical, 48 bits virtual
power management:

processor       : 2
vendor_id       : GenuineIntel
cpu family      : 6
model           : 85
model name      : Intel(R) Xeon(R) Gold 5118 CPU @ 2.30GHz
stepping        : 4
microcode       : 0x2000050
cpu MHz         : 2294.609
cache size      : 16896 KB
physical id     : 4
siblings        : 1
core id         : 0
cpu cores       : 1
apicid          : 4
initial apicid  : 4
fpu             : yes
fpu_exception   : yes
cpuid level     : 13
wp              : yes
flags           : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts mmx fxsr sse sse2 sssyscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts nopl xtopology tsc_reliable nonstop_tsc 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 ssbd ibrs ibpb stibp kaiser fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 invpcid rtm rdseed adx smapxsaveopt arat flush_l1d arch_capabilities
bugs            : cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf
bogomips        : 4589.21
clflush size    : 64
cache_alignment : 64
address sizes   : 42 bits physical, 48 bits virtual
power management:

processor       : 3
vendor_id       : GenuineIntel
cpu family      : 6
model           : 85
model name      : Intel(R) Xeon(R) Gold 5118 CPU @ 2.30GHz
stepping        : 4
microcode       : 0x2000050
cpu MHz         : 2294.609
cache size      : 16896 KB
physical id     : 6
siblings        : 1
core id         : 0
cpu cores       : 1
apicid          : 6
initial apicid  : 6
fpu             : yes
fpu_exception   : yes
cpuid level     : 13
wp              : yes
flags           : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts mmx fxsr sse sse2 sssyscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts nopl xtopology tsc_reliable nonstop_tsc 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 ssbd ibrs ibpb stibp kaiser fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 invpcid rtm rdseed adx smapxsaveopt arat flush_l1d arch_capabilities
bugs            : cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf
bogomips        : 4589.21
clflush size    : 64
cache_alignment : 64
address sizes   : 42 bits physical, 48 bits virtual
power management:

1kastner · 2019-03-05T12:58:40Z

jovyan@742a0164afd5:~$ cat /etc/*-release
DISTRIB_ID=Ubuntu
DISTRIB_RELEASE=18.04
DISTRIB_CODENAME=bionic
DISTRIB_DESCRIPTION="Ubuntu 18.04.1 LTS"
NAME="Ubuntu"
VERSION="18.04.1 LTS (Bionic Beaver)"
ID=ubuntu
ID_LIKE=debian
PRETTY_NAME="Ubuntu 18.04.1 LTS"
VERSION_ID="18.04"
HOME_URL="https://www.ubuntu.com/"
SUPPORT_URL="https://help.ubuntu.com/"
BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
VERSION_CODENAME=bionic
UBUNTU_CODENAME=bionic

jovyan@742a0164afd5:~$ uname -a
Linux 742a0164afd5 4.4.0-142-generic #168-Ubuntu SMP Wed Jan 16 21:00:45 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

mingwandroid · 2019-03-05T14:29:03Z

OK, so I wanted to see that from within your Docker. It doesn't really matter though, AFAICT you have a misconfigured Docker setup here.

1kastner · 2019-03-05T15:34:13Z

OK, so I wanted to see that from within your Docker. It doesn't really matter though, AFAICT you have a misconfigured Docker setup here.

Thank you very much so far!
It is the result from within the docker setup.
Could you give me a hint how the docker setup is misconfigured?

mingwandroid · 2019-03-05T18:12:10Z

No, please ask on a Docker support forum.

github-actions · 2021-09-02T06:01:36Z

Hi there, thank you for your contribution to Conda!

This issue has been automatically locked since it has not had recent activity after it was closed.

Please open a new issue if needed.

mingwandroid closed this as completed Mar 5, 2019

1kastner mentioned this issue Mar 7, 2019

Invokation of certain methods result in an immediate crash of the python interpreter: Illegal instruction (core dumped) jupyter/docker-stacks#811

Closed

1kastner mentioned this issue Mar 21, 2019

Error: Detection of CPU type fails OpenMathLib/OpenBLAS#2067

Closed

juliotux mentioned this issue Mar 15, 2020

Core Dump juliotux/astrometry-conda#2

Closed

github-actions bot added the locked [bot] locked due to inactivity label Sep 2, 2021

github-actions bot locked as resolved and limited conversation to collaborators Sep 2, 2021

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Certain libraries' method invocations result in `Illegal Instruction (core dumped)` #8373

Certain libraries' method invocations result in `Illegal Instruction (core dumped)` #8373

1kastner commented Mar 4, 2019 •

edited

mingwandroid commented Mar 5, 2019

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1kastner commented Mar 5, 2019 •

edited

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mingwandroid commented Mar 5, 2019

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github-actions bot commented Sep 2, 2021

Certain libraries' method invocations result in Illegal Instruction (core dumped) #8373

Certain libraries' method invocations result in Illegal Instruction (core dumped) #8373

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1kastner commented Mar 4, 2019 • edited

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Expected Behavior

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mingwandroid commented Mar 5, 2019

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1kastner commented Mar 5, 2019 • edited

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mingwandroid commented Mar 5, 2019

1kastner commented Mar 5, 2019

1kastner commented Mar 5, 2019 • edited

mingwandroid commented Mar 5, 2019

1kastner commented Mar 5, 2019 • edited

mingwandroid commented Mar 5, 2019

github-actions bot commented Sep 2, 2021

Certain libraries' method invocations result in `Illegal Instruction (core dumped)` #8373

Certain libraries' method invocations result in `Illegal Instruction (core dumped)` #8373

1kastner commented Mar 4, 2019 •

edited

1kastner commented Mar 5, 2019 •

edited

1kastner commented Mar 5, 2019 •

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1kastner commented Mar 5, 2019 •

edited