<86>Nov 25 12:33:42 userdel[2886898]: delete user 'rooter' <86>Nov 25 12:33:42 userdel[2886898]: removed group 'rooter' owned by 'rooter' <86>Nov 25 12:33:42 userdel[2886898]: removed shadow group 'rooter' owned by 'rooter' <86>Nov 25 12:33:42 groupadd[2886924]: group added to /etc/group: name=rooter, GID=633 <86>Nov 25 12:33:42 groupadd[2886924]: group added to /etc/gshadow: name=rooter <86>Nov 25 12:33:42 groupadd[2886924]: new group: name=rooter, GID=633 <86>Nov 25 12:33:42 useradd[2886971]: new user: name=rooter, UID=633, GID=633, home=/root, shell=/bin/bash <86>Nov 25 12:33:42 userdel[2887019]: delete user 'builder' <86>Nov 25 12:33:42 userdel[2887019]: removed group 'builder' owned by 'builder' <86>Nov 25 12:33:42 userdel[2887019]: removed shadow group 'builder' owned by 'builder' <86>Nov 25 12:33:42 groupadd[2887037]: group added to /etc/group: name=builder, GID=634 <86>Nov 25 12:33:42 groupadd[2887037]: group added to /etc/gshadow: name=builder <86>Nov 25 12:33:42 groupadd[2887037]: new group: name=builder, GID=634 <86>Nov 25 12:33:42 useradd[2887052]: new user: name=builder, UID=634, GID=634, home=/usr/src, shell=/bin/bash <13>Nov 25 12:33:44 rpmi: libruby-2.7.2-alt1 sisyphus+261875.40.2.1 1605716658 installed <13>Nov 25 12:33:44 rpmi: libgdbm-1.8.3-alt10 1454943334 installed <13>Nov 25 12:33:44 rpmi: libyaml2-0.2.5-alt1 sisyphus+253672.100.1.1 1592583137 installed <13>Nov 25 12:33:44 rpmi: gem-minitest-5.14.1-alt0.1 sisyphus+249637.100.1.1 1586421683 installed <13>Nov 25 12:33:44 rpmi: ruby-net-telnet-0.2.0-alt1 sisyphus+219345.2700.8.1 1547631566 installed <13>Nov 25 12:33:44 rpmi: gem-rake-13.0.1-alt1 sisyphus+248971.320.47.1 1586259947 installed <13>Nov 25 12:33:44 rpmi: ruby-xmlrpc-0.3.0-alt1 sisyphus+219345.3300.8.1 1547631818 installed <13>Nov 25 12:33:44 rpmi: gem-2:3.1.2-alt1 sisyphus+261875.40.2.1 1605716587 installed <13>Nov 25 12:33:44 rpmi: ri-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed <13>Nov 25 12:33:44 rpmi: rdoc-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed <13>Nov 25 12:33:44 rpmi: ruby-rdoc-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed <13>Nov 25 12:33:44 rpmi: rake-13.0.1-alt1 sisyphus+248971.320.47.1 1586259947 installed <13>Nov 25 12:33:44 rpmi: erb-0:2.7.2-alt1 sisyphus+261875.40.2.1 1605716587 installed <13>Nov 25 12:33:44 rpmi: irb-2.7.2-alt1 sisyphus+261875.40.2.1 1605716587 installed <13>Nov 25 12:33:44 rpmi: gem-test-unit-3.3.5-alt1 sisyphus+248971.620.47.1 1586260035 installed <13>Nov 25 12:33:44 rpmi: gem-power-assert-1.1.7-alt1 sisyphus+248971.220.47.1 1586259894 installed <13>Nov 25 12:33:44 rpmi: bundle-2.1.4-alt1 sisyphus+247301.1100.3.2 1583840910 installed <13>Nov 25 12:33:45 rpmi: gem-bundler-2.1.4-alt1 sisyphus+247301.1100.3.2 1583840910 installed <13>Nov 25 12:33:45 rpmi: ruby-2.7.2-alt1 sisyphus+261875.40.2.1 1605716658 installed <13>Nov 25 12:33:46 rpmi: ruby-stdlibs-2.7.2-alt1 sisyphus+261875.40.2.1 1605716658 installed Building target platforms: i586 Building for target i586 Wrote: /usr/src/in/nosrpm/auto-nng-1.7-alt2_3.1.nosrc.rpm Installing auto-nng-1.7-alt2_3.1.src.rpm Building target platforms: i586 Building for target i586 Executing(%prep): /bin/sh -e /usr/src/tmp/rpm-tmp.27919 + umask 022 + /bin/mkdir -p /usr/src/RPM/BUILD + cd /usr/src/RPM/BUILD + cd /usr/src/RPM/BUILD + rm -rf auto-nng.v1.7 + echo 'Source #0 (auto-nng.v1.7.tar.gz):' Source #0 (auto-nng.v1.7.tar.gz): + /bin/gzip -dc /usr/src/RPM/SOURCES/auto-nng.v1.7.tar.gz + /bin/tar -xf - + cd auto-nng.v1.7 + /bin/chmod -c -Rf u+rwX,go-w . + echo 'Patch #0 (auto-nng-cflags.patch):' Patch #0 (auto-nng-cflags.patch): + /usr/bin/patch -p1 -b --suffix .cflags patching file Makefile + exit 0 Executing(%build): /bin/sh -e /usr/src/tmp/rpm-tmp.17501 + umask 022 + /bin/mkdir -p /usr/src/RPM/BUILD + cd /usr/src/RPM/BUILD + cd auto-nng.v1.7 + make -j8 'CFLAGS=-pipe -frecord-gcc-switches -Wall -g -O2 -march=i586 -mtune=generic' make: Entering directory '/usr/src/RPM/BUILD/auto-nng.v1.7' cc -pipe -frecord-gcc-switches -Wall -g -O2 -march=i586 -mtune=generic -o auto-nng auto-nng.c -lm auto-nng.c: In function 'main_generate': auto-nng.c:681:54: warning: 'continuous_input_stddevs' may be used uninitialized in this function [-Wmaybe-uninitialized] 681 | for (i = 0; i < continuous_input_count; i++) printf("%f, %f\n", continuous_input_averages[i], continuous_input_stddevs[i]); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ auto-nng.c:681:54: warning: 'continuous_input_averages' may be used uninitialized in this function [-Wmaybe-uninitialized] auto-nng.c:686:11: warning: 'continuous_output_stddevs' may be used uninitialized in this function [-Wmaybe-uninitialized] 686 | printf(DOUBLE_FORMAT ", " DOUBLE_FORMAT "\n", continuous_output_averages[i], continuous_output_stddevs[i]); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ auto-nng.c:686:11: warning: 'continuous_output_averages' may be used uninitialized in this function [-Wmaybe-uninitialized] auto-nng.c: In function 'main_run': auto-nng.c:771:11: warning: 'continuous_input_stats' may be used uninitialized in this function [-Wmaybe-uninitialized] 771 | double *continuous_input_stats; | ^~~~~~~~~~~~~~~~~~~~~~ auto-nng.c:910:140: warning: 'continuous_output_stats' may be used uninitialized in this function [-Wmaybe-uninitialized] 910 | printf(DOUBLE_FORMAT, read_indicators(low_indicator, high_indicator) * continuous_output_stats[2*j+1] + continuous_output_stats[2*j]); | ^ auto-nng.c:904:37: warning: 'continuous_output_cols' may be used uninitialized in this function [-Wmaybe-uninitialized] 904 | if (continuous_output_cols[j] == i) { | ~~~~~~~~~~~~~~~~~~~~~~^~~ auto-nng.c:897:33: warning: 'binary_output_cols' may be used uninitialized in this function [-Wmaybe-uninitialized] 897 | if (binary_output_cols[j] == i) { | ~~~~~~~~~~~~~~~~~~^~~ auto-nng.c:890:36: warning: 'continuous_input_cols' may be used uninitialized in this function [-Wmaybe-uninitialized] 890 | if (continuous_input_cols[j] == i) { | ~~~~~~~~~~~~~~~~~~~~~^~~ auto-nng.c:883:32: warning: 'binary_input_cols' may be used uninitialized in this function [-Wmaybe-uninitialized] 883 | if (binary_input_cols[j] == i) { | ~~~~~~~~~~~~~~~~~^~~ make: Leaving directory '/usr/src/RPM/BUILD/auto-nng.v1.7' + exit 0 Executing(%install): /bin/sh -e /usr/src/tmp/rpm-tmp.36760 + umask 022 + /bin/mkdir -p /usr/src/RPM/BUILD + cd /usr/src/RPM/BUILD + /bin/chmod -Rf u+rwX -- /usr/src/tmp/auto-nng-buildroot + : + /bin/rm -rf -- /usr/src/tmp/auto-nng-buildroot + cd auto-nng.v1.7 + mkdir -p /usr/src/tmp/auto-nng-buildroot//usr/bin/ + install auto-nng /usr/src/tmp/auto-nng-buildroot//usr/bin/ + /usr/lib/rpm/brp-alt Cleaning files in /usr/src/tmp/auto-nng-buildroot (auto) Verifying and fixing files in /usr/src/tmp/auto-nng-buildroot (binconfig,pkgconfig,libtool,desktop) Checking contents of files in /usr/src/tmp/auto-nng-buildroot/ (default) Compressing files in /usr/src/tmp/auto-nng-buildroot (auto) Verifying ELF objects in /usr/src/tmp/auto-nng-buildroot (arch=normal,fhs=normal,lfs=relaxed,lint=relaxed,rpath=normal,stack=normal,textrel=normal,unresolved=normal) verify-elf: WARNING: ./usr/bin/auto-nng: uses non-LFS functions: fopen Hardlinking identical .pyc and .pyo files Executing(%check): /bin/sh -e /usr/src/tmp/rpm-tmp.36760 + umask 022 + /bin/mkdir -p /usr/src/RPM/BUILD + cd /usr/src/RPM/BUILD + cd auto-nng.v1.7 + make test make: Entering directory '/usr/src/RPM/BUILD/auto-nng.v1.7' ruby auto-nng-test.rb ================================================== auto-nng v1.7 Copyright (c) 2011 Public Software Group e. V. This software is EXPERIMENTAL and comes with ABSOLUTELY NO WARRANTY. web: http://www.public-software-group.org/ ================================================== Training error: 0.991401 / Test error: 0.989840 / Layer sizes: 10 3 1 Training error: 0.982648 / Test error: 0.979534 / Layer sizes: 10 7 1 Training error: 0.976688 / Test error: 0.972043 / Layer sizes: 10 3 3 1 Training error: 0.971656 / Test error: 0.965921 / Layer sizes: 10 3 3 1 Training error: 0.972718 / Test error: 0.961513 / Layer sizes: 10 1 Training error: 0.963873 / Test error: 0.956442 / Layer sizes: 10 10 10 1 Training error: 0.957394 / Test error: 0.948532 / Layer sizes: 10 3 3 1 Training error: 0.948403 / Test error: 0.939126 / Layer sizes: 10 10 1 Training error: 0.905353 / Test error: 0.890545 / Layer sizes: 10 1 Training error: 0.896478 / Test error: 0.886738 / Layer sizes: 10 1 Training error: 0.850313 / Test error: 0.858226 / Layer sizes: 10 1 Training error: 0.834684 / Test error: 0.848459 / Layer sizes: 10 1 Training error: 0.828133 / Test error: 0.839889 / Layer sizes: 10 1 Training error: 0.800492 / Test error: 0.810455 / Layer sizes: 10 1 Training error: 0.787295 / Test error: 0.784648 / Layer sizes: 10 1 Training error: 0.777372 / Test error: 0.767878 / Layer sizes: 10 1 Training error: 0.772429 / Test error: 0.757181 / Layer sizes: 10 1 Training error: 0.737866 / Test error: 0.728933 / Layer sizes: 10 1 Training error: 0.721507 / Test error: 0.707011 / Layer sizes: 10 1 Training error: 0.692485 / Test error: 0.682630 / Layer sizes: 10 1 Training error: 0.676886 / Test error: 0.677365 / Layer sizes: 10 1 Training error: 0.667009 / Test error: 0.673755 / Layer sizes: 10 1 Training error: 0.660942 / Test error: 0.667290 / Layer sizes: 10 1 Training error: 0.654635 / Test error: 0.658065 / Layer sizes: 10 1 Training error: 0.650866 / Test error: 0.654476 / Layer sizes: 10 1 Training error: 0.637504 / Test error: 0.654201 / Layer sizes: 10 1 Training error: 0.609177 / Test error: 0.618699 / Layer sizes: 10 1 Training error: 0.588761 / Test error: 0.616019 / Layer sizes: 10 1 Training error: 0.580141 / Test error: 0.604041 / Layer sizes: 10 1 Training error: 0.568978 / Test error: 0.589799 / Layer sizes: 10 1 Training error: 0.550400 / Test error: 0.573385 / Layer sizes: 10 1 Training error: 0.548081 / Test error: 0.567988 / Layer sizes: 10 1 Training error: 0.531770 / Test error: 0.565743 / Layer sizes: 10 1 Training error: 0.520558 / Test error: 0.549412 / Layer sizes: 10 1 Training error: 0.519473 / Test error: 0.549238 / Layer sizes: 10 1 Training error: 0.501891 / Test error: 0.542595 / Layer sizes: 10 1 Training error: 0.499396 / Test error: 0.538655 / Layer sizes: 10 1 Training error: 0.497900 / Test error: 0.538630 / Layer sizes: 10 1 Training error: 0.490938 / Test error: 0.528317 / Layer sizes: 10 1 Training error: 0.476444 / Test error: 0.522152 / Layer sizes: 10 1 Training error: 0.474791 / Test error: 0.510288 / Layer sizes: 10 1 Training error: 0.459407 / Test error: 0.504775 / Layer sizes: 10 1 Training error: 0.443474 / Test error: 0.485175 / Layer sizes: 10 10 1 Training error: 0.419521 / Test error: 0.476666 / Layer sizes: 10 10 1 Training error: 0.408317 / Test error: 0.474998 / Layer sizes: 10 10 1 Training error: 0.406810 / Test error: 0.468566 / Layer sizes: 10 10 1 Training error: 0.404329 / Test error: 0.460393 / Layer sizes: 10 10 1 Training error: 0.397216 / Test error: 0.460170 / Layer sizes: 10 10 1 Training error: 0.387485 / Test error: 0.451148 / Layer sizes: 10 10 1 Training error: 0.385216 / Test error: 0.445587 / Layer sizes: 10 10 1 Training error: 0.367837 / Test error: 0.428996 / Layer sizes: 10 10 1 Training error: 0.367703 / Test error: 0.405797 / Layer sizes: 10 10 1 Training error: 0.360947 / Test error: 0.397455 / Layer sizes: 10 10 1 Training error: 0.352223 / Test error: 0.395810 / Layer sizes: 10 10 1 Training error: 0.340993 / Test error: 0.387445 / Layer sizes: 10 10 1 Training error: 0.334977 / Test error: 0.376463 / Layer sizes: 10 10 1 Training error: 0.330034 / Test error: 0.369503 / Layer sizes: 10 10 1 Training error: 0.286617 / Test error: 0.365772 / Layer sizes: 10 10 1 Training error: 0.278416 / Test error: 0.353982 / Layer sizes: 10 10 1 Training error: 0.273365 / Test error: 0.353302 / Layer sizes: 10 10 1 Training error: 0.271003 / Test error: 0.341118 / Layer sizes: 10 10 1 Training error: 0.258305 / Test error: 0.335200 / Layer sizes: 10 10 1 Training error: 0.256260 / Test error: 0.333500 / Layer sizes: 10 10 1 Training error: 0.253706 / Test error: 0.317653 / Layer sizes: 10 10 1 Training error: 0.251388 / Test error: 0.302474 / Layer sizes: 10 10 1 Training error: 0.244075 / Test error: 0.288947 / Layer sizes: 10 10 1 Training error: 0.239347 / Test error: 0.287475 / Layer sizes: 10 10 1 Training error: 0.225965 / Test error: 0.279113 / Layer sizes: 10 10 1 Training error: 0.198427 / Test error: 0.276627 / Layer sizes: 10 10 1 Training error: 0.167081 / Test error: 0.269925 / Layer sizes: 10 10 1 Training error: 0.161086 / Test error: 0.262304 / Layer sizes: 10 10 1 Training error: 0.233959 / Test error: 0.259816 / Layer sizes: 10 10 10 1 Training error: 0.160862 / Test error: 0.259272 / Layer sizes: 10 10 1 Training error: 0.159310 / Test error: 0.258075 / Layer sizes: 10 10 1 Training error: 0.158619 / Test error: 0.257372 / Layer sizes: 10 10 1 Training error: 0.149663 / Test error: 0.253592 / Layer sizes: 10 10 1 Training error: 0.146892 / Test error: 0.238686 / Layer sizes: 10 10 1 Training error: 0.165279 / Test error: 0.238016 / Layer sizes: 10 7 1 Training error: 0.135105 / Test error: 0.237124 / Layer sizes: 10 10 10 1 Training error: 0.133294 / Test error: 0.236213 / Layer sizes: 10 10 10 1 Training error: 0.126661 / Test error: 0.225150 / Layer sizes: 10 10 1 Training error: 0.096592 / Test error: 0.210457 / Layer sizes: 10 10 10 1 Training error: 0.096137 / Test error: 0.207465 / Layer sizes: 10 10 10 1 Training error: 0.095880 / Test error: 0.204728 / Layer sizes: 10 10 10 1 Training error: 0.093093 / Test error: 0.204658 / Layer sizes: 10 10 10 1 Training error: 0.092692 / Test error: 0.203080 / Layer sizes: 10 10 10 1 Training error: 0.092379 / Test error: 0.196199 / Layer sizes: 10 10 10 1 Training error: 0.092603 / Test error: 0.194424 / Layer sizes: 10 3 3 1 Training error: 0.090866 / Test error: 0.192770 / Layer sizes: 10 3 3 1 Training error: 0.089920 / Test error: 0.192433 / Layer sizes: 10 3 3 1 Training error: 0.089661 / Test error: 0.191291 / Layer sizes: 10 3 3 1 Training error: 0.089292 / Test error: 0.190826 / Layer sizes: 10 3 3 1 Training error: 0.021765 / Test error: 0.174801 / Layer sizes: 10 9 4 1 Training error: 0.085270 / Test error: 0.174276 / Layer sizes: 10 3 1 Training error: 0.085264 / Test error: 0.171832 / Layer sizes: 10 3 1 Training error: 0.005477 / Test error: 0.169770 / Layer sizes: 10 10 10 1 Training error: 0.005351 / Test error: 0.142230 / Layer sizes: 10 10 10 1 Training error: 0.018993 / Test error: 0.127525 / Layer sizes: 10 10 1 Training error: 0.018933 / Test error: 0.124892 / Layer sizes: 10 10 1 Training error: 0.018788 / Test error: 0.123001 / Layer sizes: 10 10 1 Training error: 0.015597 / Test error: 0.121377 / Layer sizes: 10 10 1 Training error: 0.015172 / Test error: 0.119039 / Layer sizes: 10 10 1 Training error: 0.014865 / Test error: 0.118550 / Layer sizes: 10 10 1 Training error: 0.011181 / Test error: 0.113195 / Layer sizes: 10 10 1 Training error: 0.010527 / Test error: 0.106854 / Layer sizes: 10 10 1 Training error: 0.010319 / Test error: 0.106003 / Layer sizes: 10 10 1 Training error: 0.000000 / Test error: 0.083333 / Layer sizes: 10 9 4 1 Finishing... ================================================== auto-nng v1.7 Copyright (c) 2011 Public Software Group e. V. This software is EXPERIMENTAL and comes with ABSOLUTELY NO WARRANTY. web: http://www.public-software-group.org/ ================================================== Loading neuronal network from file "test.network.nn". Network loaded, processing data. 80.03 % correct. 19.97 % wrong. Limit: 17.41 %. Test failed, please try again. make: Leaving directory '/usr/src/RPM/BUILD/auto-nng.v1.7' + exit 0 Processing files: auto-nng-1.7-alt2_3.1 Executing(%doc): /bin/sh -e /usr/src/tmp/rpm-tmp.41358 + umask 022 + /bin/mkdir -p /usr/src/RPM/BUILD + cd /usr/src/RPM/BUILD + cd auto-nng.v1.7 + DOCDIR=/usr/src/tmp/auto-nng-buildroot/usr/share/doc/auto-nng-1.7 + export DOCDIR + rm -rf /usr/src/tmp/auto-nng-buildroot/usr/share/doc/auto-nng-1.7 + /bin/mkdir -p /usr/src/tmp/auto-nng-buildroot/usr/share/doc/auto-nng-1.7 + cp -prL LICENSE README /usr/src/tmp/auto-nng-buildroot/usr/share/doc/auto-nng-1.7 + chmod -R go-w /usr/src/tmp/auto-nng-buildroot/usr/share/doc/auto-nng-1.7 + chmod -R a+rX /usr/src/tmp/auto-nng-buildroot/usr/share/doc/auto-nng-1.7 + exit 0 Finding Provides (using /usr/lib/rpm/find-provides) Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.fbz53w find-provides: running scripts (alternatives,debuginfo,lib,pam,perl,pkgconfig,python,shell) Finding Requires (using /usr/lib/rpm/find-requires) Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.hH0eLx find-requires: running scripts (cpp,debuginfo,files,lib,pam,perl,pkgconfig,pkgconfiglib,python,rpmlib,shebang,shell,static,symlinks,systemd-services) Requires: /lib/ld-linux.so.2, libc.so.6(GLIBC_2.0), libc.so.6(GLIBC_2.1), libc.so.6(GLIBC_2.3.4), libc.so.6(GLIBC_2.4), libm.so.6(GLIBC_2.0), libm.so.6(GLIBC_2.1), libm.so.6(GLIBC_2.29), rtld(GNU_HASH) Finding debuginfo files (using /usr/lib/rpm/find-debuginfo-files) Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.9TvlYu Creating auto-nng-debuginfo package Processing files: auto-nng-debuginfo-1.7-alt2_3.1 Finding Provides (using /usr/lib/rpm/find-provides) Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.EPKTRw find-provides: running scripts (debuginfo) Finding Requires (using /usr/lib/rpm/find-requires) Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.6sd87t find-requires: running scripts (debuginfo) Requires: auto-nng = 1.7-alt2_3.1, /usr/lib/debug/lib/ld-linux.so.2.debug, debug(libc.so.6), debug(libm.so.6) Wrote: /usr/src/RPM/RPMS/i586/auto-nng-1.7-alt2_3.1.i586.rpm Wrote: /usr/src/RPM/RPMS/i586/auto-nng-debuginfo-1.7-alt2_3.1.i586.rpm 87.26user 0.58system 1:38.85elapsed 88%CPU (0avgtext+0avgdata 35824maxresident)k 0inputs+0outputs (0major+165812minor)pagefaults 0swaps 92.65user 3.70system 1:48.17elapsed 89%CPU (0avgtext+0avgdata 109064maxresident)k 0inputs+0outputs (0major+459070minor)pagefaults 0swaps --- auto-nng-1.7-alt2_3.1.i586.rpm.repo 2013-04-03 05:20:58.000000000 +0000 +++ auto-nng-1.7-alt2_3.1.i586.rpm.hasher 2020-11-25 12:35:28.088838577 +0000 @@ -11,2 +11,3 @@ Requires: libm.so.6(GLIBC_2.1) +Requires: libm.so.6(GLIBC_2.29) Requires: rtld(GNU_HASH)