<86>Dec 18 13:02:12 userdel[114371]: delete user 'rooter' <86>Dec 18 13:02:12 userdel[114371]: removed group 'rooter' owned by 'rooter' <86>Dec 18 13:02:12 groupadd[114380]: group added to /etc/group: name=rooter, GID=591 <86>Dec 18 13:02:12 groupadd[114380]: group added to /etc/gshadow: name=rooter <86>Dec 18 13:02:12 groupadd[114380]: new group: name=rooter, GID=591 <86>Dec 18 13:02:12 useradd[114392]: new user: name=rooter, UID=591, GID=591, home=/root, shell=/bin/bash <86>Dec 18 13:02:12 userdel[114408]: delete user 'builder' <86>Dec 18 13:02:12 userdel[114408]: removed group 'builder' owned by 'builder' <86>Dec 18 13:02:12 userdel[114408]: removed shadow group 'builder' owned by 'builder' <86>Dec 18 13:02:12 groupadd[114418]: group added to /etc/group: name=builder, GID=592 <86>Dec 18 13:02:12 groupadd[114418]: group added to /etc/gshadow: name=builder <86>Dec 18 13:02:12 groupadd[114418]: new group: name=builder, GID=592 <86>Dec 18 13:02:12 useradd[114424]: new user: name=builder, UID=592, GID=592, home=/usr/src, shell=/bin/bash <13>Dec 18 13:02:14 rpmi: libruby-2.5.5-alt4.1 sisyphus+237310.40.2.1 1568211319 installed <13>Dec 18 13:02:14 rpmi: libp11-kit-0.23.15-alt1 sisyphus+226408.100.2.1 1554288204 installed <13>Dec 18 13:02:14 rpmi: libtasn1-4.15.0-alt1 sisyphus+241940.100.1.1 1574959866 installed <13>Dec 18 13:02:14 rpmi: libgdbm-1.8.3-alt10 1454943334 installed <13>Dec 18 13:02:14 rpmi: libyaml2-0.2.2-alt1 sisyphus+229134.100.1.1 1557342721 installed <13>Dec 18 13:02:14 rpmi: rpm-macros-alternatives-0.5.1-alt1 sisyphus+226946.100.1.1 1554830426 installed <13>Dec 18 13:02:14 rpmi: alternatives-0.5.1-alt1 sisyphus+226946.100.1.1 1554830426 installed <13>Dec 18 13:02:14 rpmi: ca-certificates-2019.10.28-alt1 sisyphus+239875.300.1.1 1572267834 installed <13>Dec 18 13:02:14 rpmi: ca-trust-0.1.2-alt1 sisyphus+233348.100.1.1 1561653823 installed <13>Dec 18 13:02:14 rpmi: p11-kit-trust-0.23.15-alt1 sisyphus+226408.100.2.1 1554288204 installed <13>Dec 18 13:02:14 rpmi: libcrypto1.1-1.1.1d-alt1.1 sisyphus+237931.100.2.1 1569235729 installed <13>Dec 18 13:02:15 rpmi: libssl1.1-1.1.1d-alt1.1 sisyphus+237931.100.2.1 1569235729 installed <13>Dec 18 13:02:15 rpmi: openssl-1.1.1d-alt1.1 sisyphus+237931.100.2.1 1569235729 installed <13>Dec 18 13:02:15 rpmi: ruby-rubygems-update-3.0.4-alt1 sisyphus+231621.240.57.1 1567243682 installed <13>Dec 18 13:02:15 rpmi: gem-did-you-mean-1.3.0-alt2.1 sisyphus+237310.1100.2.1 1568211939 installed <13>Dec 18 13:02:15 rpmi: ruby-minitest-5.11.3-alt1 sisyphus+219345.3500.8.1 1547631954 installed <13>Dec 18 13:02:15 rpmi: ruby-net-telnet-0.2.0-alt1 sisyphus+219345.2700.8.1 1547631566 installed <13>Dec 18 13:02:15 rpmi: gem-power-assert-1.1.4-alt1 sisyphus+226411.3200.6.1 1554380195 installed <13>Dec 18 13:02:15 rpmi: ruby-test-unit-1:3.3.1-alt1 sisyphus+226411.5300.6.1 1554381151 installed <13>Dec 18 13:02:15 rpmi: ruby-xmlrpc-0.3.0-alt1 sisyphus+219345.3300.8.1 1547631818 installed <13>Dec 18 13:02:15 rpmi: gem-2.5.5-alt4.1 sisyphus+237310.40.2.1 1568211289 installed <13>Dec 18 13:02:15 rpmi: ri-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed <13>Dec 18 13:02:15 rpmi: rdoc-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed <13>Dec 18 13:02:15 rpmi: ruby-rdoc-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed <13>Dec 18 13:02:15 rpmi: erb-2.5.5-alt4.1 sisyphus+237310.40.2.1 1568211289 installed <13>Dec 18 13:02:15 rpmi: irb-2.5.5-alt4.1 sisyphus+237310.40.2.1 1568211289 installed <13>Dec 18 13:02:15 rpmi: rake-12.3.3-alt1 sisyphus+238087.3100.11.1 1569616589 installed <13>Dec 18 13:02:15 rpmi: ruby-rake-12.3.3-alt1 sisyphus+238087.3100.11.1 1569616589 installed <13>Dec 18 13:02:15 rpmi: ruby-stdlibs-2.5.5-alt4.1 sisyphus+237310.40.2.1 1568211319 installed <13>Dec 18 13:02:15 rpmi: bundle-2.0.2-alt2 sisyphus+237310.400.2.1 1568211679 installed <13>Dec 18 13:02:15 rpmi: ruby-2.5.5-alt4.1 sisyphus+237310.40.2.1 1568211319 installed <13>Dec 18 13:02:16 rpmi: ruby-bundler-2.0.2-alt2 sisyphus+237310.400.2.1 1568211679 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.15561 + 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.45881 + 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.45881 + 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.2332 + 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: 0.993798 / Test error: 0.999327 / Layer sizes: 10 7 1 Training error: 0.999489 / Test error: 0.998698 / Layer sizes: 10 3 1 Training error: 0.991395 / Test error: 0.996762 / Layer sizes: 10 7 1 Training error: 0.986637 / Test error: 0.991432 / Layer sizes: 10 3 1 Training error: 0.982071 / Test error: 0.988005 / Layer sizes: 10 3 1 Training error: 0.931266 / Test error: 0.980213 / Layer sizes: 10 1 Training error: 0.892675 / Test error: 0.935112 / Layer sizes: 10 1 Training error: 0.852124 / Test error: 0.873366 / Layer sizes: 10 1 Training error: 0.837596 / Test error: 0.855384 / Layer sizes: 10 1 Training error: 0.829357 / Test error: 0.830951 / Layer sizes: 10 1 Training error: 0.814436 / Test error: 0.830271 / Layer sizes: 10 1 Training error: 0.812446 / Test error: 0.824242 / Layer sizes: 10 1 Training error: 0.786168 / Test error: 0.810354 / Layer sizes: 10 1 Training error: 0.756333 / Test error: 0.796144 / Layer sizes: 10 1 Training error: 0.731698 / Test error: 0.771676 / Layer sizes: 10 1 Training error: 0.721038 / Test error: 0.748219 / Layer sizes: 10 1 Training error: 0.701046 / Test error: 0.729115 / Layer sizes: 10 1 Training error: 0.691602 / Test error: 0.714651 / Layer sizes: 10 1 Training error: 0.673758 / Test error: 0.696223 / Layer sizes: 10 1 Training error: 0.671353 / Test error: 0.685641 / Layer sizes: 10 1 Training error: 0.657565 / Test error: 0.674514 / Layer sizes: 10 1 Training error: 0.653978 / Test error: 0.659339 / Layer sizes: 10 1 Training error: 0.630067 / Test error: 0.647335 / Layer sizes: 10 1 Training error: 0.607003 / Test error: 0.636530 / Layer sizes: 10 1 Training error: 0.604076 / Test error: 0.623807 / Layer sizes: 10 1 Training error: 0.597567 / Test error: 0.614404 / Layer sizes: 10 1 Training error: 0.588975 / Test error: 0.608227 / Layer sizes: 10 1 Training error: 0.581648 / Test error: 0.604330 / Layer sizes: 10 1 Training error: 0.568169 / Test error: 0.578349 / Layer sizes: 10 1 Training error: 0.565253 / Test error: 0.573319 / Layer sizes: 10 1 Training error: 0.563834 / Test error: 0.572929 / Layer sizes: 10 1 Training error: 0.556055 / Test error: 0.562234 / Layer sizes: 10 1 Training error: 0.549237 / Test error: 0.558470 / Layer sizes: 10 1 Training error: 0.542257 / Test error: 0.558170 / Layer sizes: 10 1 Training error: 0.541658 / Test error: 0.547254 / Layer sizes: 10 1 Training error: 0.526529 / Test error: 0.532435 / Layer sizes: 10 1 Training error: 0.520654 / Test error: 0.527574 / Layer sizes: 10 1 Training error: 0.520083 / Test error: 0.519454 / Layer sizes: 10 1 Training error: 0.513015 / Test error: 0.512905 / Layer sizes: 10 1 Training error: 0.512031 / Test error: 0.500784 / Layer sizes: 10 1 Training error: 0.495642 / Test error: 0.496083 / Layer sizes: 10 1 Training error: 0.483359 / Test error: 0.494606 / Layer sizes: 10 1 Training error: 0.476798 / Test error: 0.490985 / Layer sizes: 10 1 Training error: 0.471194 / Test error: 0.485250 / Layer sizes: 10 1 Training error: 0.468470 / Test error: 0.483989 / Layer sizes: 10 1 Training error: 0.467402 / Test error: 0.482363 / Layer sizes: 10 1 Training error: 0.457680 / Test error: 0.474930 / Layer sizes: 10 1 Training error: 0.450579 / Test error: 0.472226 / Layer sizes: 10 1 Training error: 0.438516 / Test error: 0.468807 / Layer sizes: 10 1 Training error: 0.426961 / Test error: 0.468320 / Layer sizes: 10 1 Training error: 0.420708 / Test error: 0.453758 / Layer sizes: 10 1 Training error: 0.412061 / Test error: 0.451523 / Layer sizes: 10 1 Training error: 0.410278 / Test error: 0.448813 / Layer sizes: 10 1 Training error: 0.409728 / Test error: 0.448477 / Layer sizes: 10 1 Training error: 0.408225 / Test error: 0.445783 / Layer sizes: 10 1 Training error: 0.396654 / Test error: 0.445510 / Layer sizes: 10 7 1 Training error: 0.423336 / Test error: 0.444484 / Layer sizes: 10 10 1 Training error: 0.392819 / Test error: 0.435643 / Layer sizes: 10 10 1 Training error: 0.368628 / Test error: 0.433862 / Layer sizes: 10 7 1 Training error: 0.364241 / Test error: 0.429024 / Layer sizes: 10 7 1 Training error: 0.347031 / Test error: 0.427379 / Layer sizes: 10 10 10 1 Training error: 0.334709 / Test error: 0.412284 / Layer sizes: 10 10 10 1 Training error: 0.334466 / Test error: 0.402836 / Layer sizes: 10 10 10 1 Training error: 0.317363 / Test error: 0.400492 / Layer sizes: 10 10 10 1 Training error: 0.313803 / Test error: 0.389614 / Layer sizes: 10 10 10 1 Training error: 0.299777 / Test error: 0.375165 / Layer sizes: 10 10 10 1 Training error: 0.243557 / Test error: 0.369833 / Layer sizes: 10 10 10 1 Training error: 0.221492 / Test error: 0.365309 / Layer sizes: 10 10 10 1 Training error: 0.209970 / Test error: 0.364025 / Layer sizes: 10 10 10 1 Training error: 0.208573 / Test error: 0.360205 / Layer sizes: 10 10 10 1 Training error: 0.194260 / Test error: 0.350261 / Layer sizes: 10 10 10 1 Training error: 0.180048 / Test error: 0.345891 / Layer sizes: 10 10 10 1 Training error: 0.178861 / Test error: 0.337688 / Layer sizes: 10 10 10 1 Training error: 0.176437 / Test error: 0.334384 / Layer sizes: 10 10 10 1 Training error: 0.174156 / Test error: 0.333957 / Layer sizes: 10 10 10 1 Training error: 0.171243 / Test error: 0.328650 / Layer sizes: 10 10 10 1 Training error: 0.167953 / Test error: 0.328189 / Layer sizes: 10 10 10 1 Training error: 0.149655 / Test error: 0.327099 / Layer sizes: 10 10 10 1 Training error: 0.147742 / Test error: 0.322731 / Layer sizes: 10 10 10 1 Training error: 0.147491 / Test error: 0.321123 / Layer sizes: 10 10 10 1 Training error: 0.143553 / Test error: 0.316384 / Layer sizes: 10 10 10 1 Training error: 0.142035 / Test error: 0.313387 / Layer sizes: 10 10 10 1 Training error: 0.099719 / Test error: 0.302756 / Layer sizes: 10 10 10 1 Training error: 0.098975 / Test error: 0.297628 / Layer sizes: 10 10 10 1 Training error: 0.098495 / Test error: 0.287219 / Layer sizes: 10 10 10 1 Training error: 0.074757 / Test error: 0.282763 / Layer sizes: 10 10 1 Training error: 0.072256 / Test error: 0.269915 / Layer sizes: 10 10 1 Training error: 0.065974 / Test error: 0.268887 / Layer sizes: 10 10 1 Training error: 0.065657 / Test error: 0.266022 / Layer sizes: 10 10 1 Training error: 0.064321 / Test error: 0.265921 / Layer sizes: 10 10 1 Training error: 0.063310 / Test error: 0.260155 / Layer sizes: 10 10 1 Training error: 0.048376 / Test error: 0.258637 / Layer sizes: 10 10 1 Training error: 0.036866 / Test error: 0.246834 / Layer sizes: 10 10 1 Training error: 0.032996 / Test error: 0.242842 / Layer sizes: 10 10 1 Training error: 0.032496 / Test error: 0.239246 / Layer sizes: 10 10 1 Training error: 0.032455 / Test error: 0.235422 / Layer sizes: 10 10 1 Training error: 0.032407 / Test error: 0.233839 / Layer sizes: 10 10 1 Training error: 0.031917 / Test error: 0.232848 / Layer sizes: 10 10 1 Training error: 0.031373 / Test error: 0.220408 / Layer sizes: 10 10 1 Training error: 0.031226 / Test error: 0.219556 / Layer sizes: 10 10 1 Training error: 0.029667 / Test error: 0.217122 / Layer sizes: 10 10 1 Training error: 0.029084 / Test error: 0.214083 / Layer sizes: 10 10 1 Training error: 0.028712 / Test error: 0.204126 / Layer sizes: 10 10 1 Training error: 0.028523 / Test error: 0.199430 / Layer sizes: 10 10 1 Training error: 0.028389 / Test error: 0.193112 / Layer sizes: 10 10 1 Training error: 0.025608 / Test error: 0.184704 / Layer sizes: 10 10 1 Training error: 0.023165 / Test error: 0.178347 / Layer sizes: 10 10 1 Training error: 0.023148 / Test error: 0.173893 / Layer sizes: 10 10 1 Training error: 0.023141 / Test error: 0.172392 / Layer sizes: 10 10 1 Training error: 0.021617 / Test error: 0.169543 / Layer sizes: 10 10 1 Training error: 0.021264 / Test error: 0.169230 / Layer sizes: 10 10 1 Training error: 0.021217 / Test error: 0.160557 / Layer sizes: 10 10 1 Training error: 0.020591 / Test error: 0.151748 / Layer sizes: 10 10 1 Training error: 0.020582 / Test error: 0.147625 / Layer sizes: 10 10 1 Training error: 0.020510 / Test error: 0.143786 / Layer sizes: 10 10 1 Training error: 0.012245 / Test error: 0.136684 / Layer sizes: 10 10 1 Training error: 0.010234 / Test error: 0.135293 / Layer sizes: 10 10 1 Training error: 0.009461 / Test error: 0.133219 / Layer sizes: 10 10 1 Training error: 0.009450 / Test error: 0.123461 / Layer sizes: 10 10 1 Training error: 0.009415 / Test error: 0.122176 / Layer sizes: 10 10 1 Training error: 0.009380 / Test error: 0.112043 / Layer sizes: 10 10 1 Training error: 0.009018 / Test error: 0.108123 / Layer sizes: 10 10 1 Training error: 0.005245 / Test error: 0.107310 / Layer sizes: 10 10 1 Training error: 0.005241 / Test error: 0.099793 / Layer sizes: 10 10 1 Training error: 0.005169 / Test error: 0.093734 / Layer sizes: 10 10 1 Training error: 0.003021 / Test error: 0.091316 / Layer sizes: 10 10 1 Training error: 0.002633 / Test error: 0.088271 / Layer sizes: 10 10 1 Training error: 0.002402 / Test error: 0.081299 / Layer sizes: 10 10 1 Training error: 0.002395 / Test error: 0.080978 / Layer sizes: 10 10 1 Training error: 0.002371 / Test error: 0.080853 / Layer sizes: 10 10 1 Training error: 0.002297 / Test error: 0.077042 / Layer sizes: 10 10 1 Training error: 0.002276 / Test error: 0.075740 / Layer sizes: 10 10 1 Training error: 0.002269 / Test error: 0.074904 / Layer sizes: 10 10 1 Training error: 0.002100 / Test error: 0.072592 / Layer sizes: 10 10 1 Training error: 0.002094 / Test error: 0.062504 / Layer sizes: 10 10 1 Training error: 0.002090 / Test error: 0.054466 / Layer sizes: 10 10 1 Training error: 0.002089 / Test error: 0.045385 / Layer sizes: 10 10 1 Training error: 0.002073 / Test error: 0.045054 / Layer sizes: 10 10 1 Training error: 0.001805 / Test error: 0.042697 / Layer sizes: 10 10 1 Training error: 0.001710 / Test error: 0.042680 / Layer sizes: 10 10 1 Training error: 0.001663 / Test error: 0.035041 / Layer sizes: 10 10 1 Training error: 0.001027 / Test error: 0.034338 / Layer sizes: 10 10 1 Training error: 0.000604 / Test error: 0.033050 / Layer sizes: 10 10 1 Training error: 0.000516 / Test error: 0.027016 / Layer sizes: 10 10 1 Training error: 0.000515 / Test error: 0.022904 / Layer sizes: 10 10 1 Training error: 0.000450 / Test error: 0.018749 / Layer sizes: 10 10 1 Training error: 0.000445 / Test error: 0.016468 / Layer sizes: 10 10 1 Training error: 0.000435 / Test error: 0.004815 / Layer sizes: 10 10 1 Training error: 0.000432 / Test error: 0.004643 / Layer sizes: 10 10 1 Training error: 0.000425 / Test error: 0.002561 / Layer sizes: 10 10 1 Training error: 0.000420 / Test error: 0.001940 / Layer sizes: 10 10 1 Training error: 0.000384 / Test error: 0.001867 / Layer sizes: 10 10 1 Training error: 0.000384 / Test error: 0.001685 / Layer sizes: 10 10 1 Training error: 0.000381 / Test error: 0.001354 / Layer sizes: 10 10 1 Training error: 0.000378 / Test error: 0.001344 / Layer sizes: 10 10 1 Training error: 0.000375 / Test error: 0.001183 / Layer sizes: 10 10 1 Training error: 0.000180 / Test error: 0.000801 / Layer sizes: 10 10 1 Training error: 0.000180 / Test error: 0.000620 / Layer sizes: 10 10 1 Training error: 0.000141 / Test error: 0.000416 / Layer sizes: 10 10 1 Training error: 0.000127 / Test error: 0.000332 / Layer sizes: 10 10 1 Training error: 0.000127 / Test error: 0.000282 / Layer sizes: 10 10 1 Training error: 0.000127 / Test error: 0.000280 / Layer sizes: 10 10 1 Training error: 0.000124 / Test error: 0.000271 / Layer sizes: 10 10 1 Training error: 0.000124 / Test error: 0.000239 / Layer sizes: 10 10 1 Training error: 0.000123 / Test error: 0.000223 / Layer sizes: 10 10 1 Training error: 0.000116 / Test error: 0.000217 / Layer sizes: 10 10 1 Training error: 0.000114 / Test error: 0.000205 / Layer sizes: 10 10 1 Training error: 0.000114 / Test error: 0.000203 / Layer sizes: 10 10 1 Training error: 0.000113 / Test error: 0.000203 / Layer sizes: 10 10 1 Training error: 0.000032 / Test error: 0.000144 / Layer sizes: 10 10 1 Training error: 0.000030 / Test error: 0.000116 / Layer sizes: 10 10 1 Training error: 0.000004 / Test error: 0.000103 / Layer sizes: 10 10 1 Training error: 0.000004 / Test error: 0.000050 / Layer sizes: 10 10 1 Training error: 0.000004 / Test error: 0.000015 / Layer sizes: 10 10 1 Training error: 0.000004 / Test error: 0.000013 / Layer sizes: 10 10 1 Training error: 0.000003 / Test error: 0.000011 / Layer sizes: 10 10 1 Training error: 0.000003 / Test error: 0.000011 / Layer sizes: 10 10 1 Training error: 0.000003 / Test error: 0.000010 / Layer sizes: 10 10 1 Training error: 0.000003 / Test error: 0.000008 / Layer sizes: 10 10 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. 94.43 % correct. 5.57 % wrong. Limit: 17.70 %. Test passed. 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.79157 + 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.GmABKo 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.Gnl1Bq find-requires: running scripts (cpp,debuginfo,files,lib,pam,perl,pkgconfig,pkgconfiglib,python,rpmlib,shebang,shell,static,symlinks) 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.9kH9fq 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.OeCNlq find-provides: running scripts (debuginfo) Finding Requires (using /usr/lib/rpm/find-requires) Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.OUCTxq 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 61.67user 0.36system 1:40.78elapsed 61%CPU (0avgtext+0avgdata 35604maxresident)k 0inputs+0outputs (0major+160020minor)pagefaults 0swaps 67.39user 3.07system 1:51.25elapsed 63%CPU (0avgtext+0avgdata 109340maxresident)k 0inputs+0outputs (0major+483240minor)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 2019-12-18 13:04:02.052469322 +0000 @@ -11,2 +11,3 @@ Requires: libm.so.6(GLIBC_2.1) +Requires: libm.so.6(GLIBC_2.29) Requires: rtld(GNU_HASH)