Platform:
OS:uname:Darwin 19.0.0 Darwin Kernel Version 19.0.0: Wed Sep 25 20:18:50 PDT 2019; root:xnu-6153.11.26~2/RELEASE_X86_64 x86_64
Architecture:
x86_64
After upgrade to os X 10.15 Catalina, previously working program failed with SIGSEGV.
How to reproduce:
create a basic maven project with 2 dependencies:
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-core</artifactId>
<version>1.0.0-beta4</version>
</dependency>
<dependency>
<groupId>org.nd4j</groupId>
<artifactId>nd4j-native-platform</artifactId>
<version>1.0.0-beta4</version>
</dependency>
and one class:
public class Main{
public static void main( String[] args ){
INDArray s = Nd4j.zeros(1, 1);
System.out.println( s.isMatrix() );
}
}
.
Under Os X 10.15 Catalina, expected result:
false
Process finished with exit code 0
Actual result:
#
# A fatal error has been detected by the Java Runtime Environment:
#
# SIGSEGV (0xb) at pc=0x00007fff666980b4, pid=31244, tid=10243
#
# JRE version: OpenJDK Runtime Environment (11.0.4+11) (build 11.0.4+11)
# Java VM: OpenJDK 64-Bit Server VM (11.0.4+11, mixed mode, tiered, compressed oops, g1 gc, bsd-amd64)
# Problematic frame:
# C [libc++abi.dylib+0x30b4] __cxxabiv1::__si_class_type_info::has_unambiguous_public_base(__cxxabiv1::__dynamic_cast_info*, void*, int) const+0x4
#
# No core dump will be written. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before starting Java again
#
# An error report file with more information is saved as:
# /Users/ivanpetrychenko/src/testAdotOpenJdk/hs_err_pid31244.log
#
# If you would like to submit a bug report, please visit:
# https://github.com/AdoptOpenJDK/openjdk-build/issues
# The crash happened outside the Java Virtual Machine in native code.
# See problematic frame for where to report the bug.
#
Process finished with exit code 134 (interrupted by signal 6: SIGABRT)
you have two libstdc++ loaded into memory, are you sure it's ok to do so ?
0x00007fff6860a000 /usr/lib/libstdc++.6.dylib
0x00000001351d8000 /Users/ivanpetrychenko/.javacpp/cache/mkl-dnn-0.18.1-1.5-macosx-x86_64.jar/org/bytedeco/mkldnn/macosx-x86_64/libstdc++.6.dylib
I'm not sure if it is normal or not, I'm not the author of this library.
But as this code works for Oracle JDK, and for AdoptOpenJDK before update to Catalina, it seems it is acceptable.
The same bug is reported to deeplearning4j: https://github.com/eclipse/deeplearning4j/issues/8156 .
I am having exactly the same issue since upgrading to Catalina yesterday, adding my specs in case it can be useful. Haven't tried with Oracle JDK.
08:59:16.436 INFO o.n.linalg.factory.Nd4jBackend - Loaded [CpuBackend] backend
#
# A fatal error has been detected by the Java Runtime Environment:
#
# SIGSEGV (0xb) at pc=0x00007fff6e8160b4, pid=8675, tid=35587
#
# JRE version: OpenJDK Runtime Environment (11.0.4+11) (build 11.0.4+11)
# Java VM: OpenJDK 64-Bit Server VM (11.0.4+11, mixed mode, tiered, compressed oops, g1 gc, bsd-amd64)
# Problematic frame:
# C [libc++abi.dylib+0x30b4] __cxxabiv1::__si_class_type_info::has_unambiguous_public_base(__cxxabiv1::__dynamic_cast_info*, void*, int) const+0x4
#
# No core dump will be written. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before starting Java again
#
# An error report file with more information is saved as:
# /Users/fabiotiriticco/Development/programming/ticofab-rep/experiments/deeplearning/planes/hs_err_pid8675.log
#
# If you would like to submit a bug report, please visit:
# https://github.com/AdoptOpenJDK/openjdk-build/issues
# The crash happened outside the Java Virtual Machine in native code.
# See problematic frame for where to report the bug.
#
MBP 15 in ch 2019, processor 2,3 GHz 8-Core Intel Core i9
Same error for me, using Oracle JDK (also happened with OpenJDK); macOS 10.15 on a 2018 MBP 15", 2.6 GHz 6-core i7:
#
# A fatal error has been detected by the Java Runtime Environment:
#
# SIGSEGV (0xb) at pc=0x00007fff6b0d40b4, pid=56262, tid=28679
#
# JRE version: Java(TM) SE Runtime Environment (10.0.2+13) (build 10.0.2+13)
# Java VM: Java HotSpot(TM) 64-Bit Server VM (10.0.2+13, mixed mode, tiered, compressed oops, g1 gc, bsd-amd64)
# Problematic frame:
# C [libc++abi.dylib+0x30b4] __cxxabiv1::__si_class_type_info::has_unambiguous_public_base(__cxxabiv1::__dynamic_cast_info*, void*, int) const+0x4
#
# No core dump will be written. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before starting Java again
#
# An error report file with more information is saved as:
# /Users/tylucaskelley/Code/topos/GeoGulp/bin/hs_err_pid56262.log
#
# If you would like to submit a bug report, please visit:
# http://bugreport.java.com/bugreport/crash.jsp
# The crash happened outside the Java Virtual Machine in native code.
# See problematic frame for where to report the bug.
Same error for me for macOS 10.15 on a 2015 MBP 13" i5
Adding log:
hs_err_pid1656.log
Still an issue: macOS 10.15 (19A602) Darwin 19.0.0
14:33:15.855 [main] INFO o.n.l.f.Nd4jBackend - Loaded [CpuBackend] backend
#
# A fatal error has been detected by the Java Runtime Environment:
#
# SIGSEGV (0xb) at pc=0x00007fff686400b4, pid=14351, tid=0x0000000000000e03
#
# JRE version: Java(TM) SE Runtime Environment (8.0_181-b13) (build 1.8.0_181-b13)
# Java VM: Java HotSpot(TM) 64-Bit Server VM (25.181-b13 mixed mode bsd-amd64 compressed oops)
# Problematic frame:
# C [libc++abi.dylib+0x30b4] _ZNK10__cxxabiv120__si_class_type_info27has_unambiguous_public_baseEPNS_19__dynamic_cast_infoEPvi+0x4
#
# Failed to write core dump. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before starting Java again
#
Same error here. I tried
Same here
Can folks try the latest builds that came out this week?
https://adoptopenjdk.net/releases.html?variant=openjdk8&jvmVariant=hotspot#x64_mac
https://adoptopenjdk.net/releases.html?variant=openjdk11&jvmVariant=hotspot#x64_mac
@karianna Just tried it with OpenJDK11: Still the same. Not surprised though as this really seems to be a problem in the deeplearning4j library.
Still the same, and still works under Orcale JDK
393 [main] INFO o.n.l.f.Nd4jBackend - Loaded [CpuBackend] backend
A fatal error has been detected by the Java Runtime Environment:
SIGSEGV (0xb) at pc=0x00007fff686c10b4, pid=95582, tid=9987
JRE version: OpenJDK Runtime Environment (11.0.5+10) (build 11.0.5+10)
Java VM: OpenJDK 64-Bit Server VM (11.0.5+10, mixed mode, tiered, compressed oops, g1 gc, bsd-amd64)
Problematic frame:
C [libc++abi.dylib+0x30b4] __cxxabiv1::__si_class_type_info::has_unambiguous_public_base(__cxxabiv1::__dynamic_cast_info, void, int) const+0x4
Just tried the quickstart with the latest version of AdoptOperJDK 11:
hs_err_pid15516.log
Same here.
I tried AdoptOpenJDK 8, 11, 13
Catalina 10.15
might be solved as mentioned here: https://github.com/eclipse/deeplearning4j/issues/8156
I would guess that the suggested solution is to upgrade to a newer version
of DL4J.
Maybe the bug still occurs in newer versions? I haven't worked with this in
a while so I can't be of much help I'm afraid.
Good luck!
On Sun, Aug 23, 2020, 00:46 rgampa notifications@github.com wrote:
@ticofab https://github.com/ticofab Can you point me to the solution in
thread eclipse/deeplearning4j#8156
https://github.com/eclipse/deeplearning4j/issues/8156.After upgrading to MacOs Catalina tomcat (8.5.43 and 8.5.57) is crashing
with below error,#
A fatal error has been detected by the Java Runtime Environment:
#
SIGSEGV (0xb) at pc=0x00007fff67945aa8, pid=3209, tid=0x0000000000009903
#
JRE version: Java(TM) SE Runtime Environment (8.0_221-b11) (build 1.8.0_221-b11)
Java VM: Java HotSpot(TM) 64-Bit Server VM (25.221-b11 mixed mode bsd-amd64 compressed oops)
Problematic frame:
C [libc++abi.dylib+0x10aa8] _ZNK10__cxxabiv120__si_class_type_info27has_unambiguous_public_baseEPNS_19__dynamic_cast_infoEPvi+0x4
#
Failed to write core dump. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before starting Java again
#
If you would like to submit a bug report, please visit:
http://bugreport.java.com/bugreport/crash.jsp
The crash happened outside the Java Virtual Machine in native code.
See problematic frame for where to report the bug.
#
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Most helpful comment
might be solved as mentioned here: https://github.com/eclipse/deeplearning4j/issues/8156