<86>Apr 7 02:39:38 userdel[68973]: delete user 'rooter' <86>Apr 7 02:39:38 userdel[68973]: removed group 'rooter' owned by 'rooter' <86>Apr 7 02:39:38 userdel[68973]: removed shadow group 'rooter' owned by 'rooter' <86>Apr 7 02:39:38 groupadd[69026]: group added to /etc/group: name=rooter, GID=705 <86>Apr 7 02:39:38 groupadd[69026]: group added to /etc/gshadow: name=rooter <86>Apr 7 02:39:38 groupadd[69026]: new group: name=rooter, GID=705 <86>Apr 7 02:39:38 useradd[69051]: new user: name=rooter, UID=705, GID=705, home=/root, shell=/bin/bash <86>Apr 7 02:39:38 userdel[69079]: delete user 'builder' <86>Apr 7 02:39:38 userdel[69079]: removed group 'builder' owned by 'builder' <86>Apr 7 02:39:38 userdel[69079]: removed shadow group 'builder' owned by 'builder' <86>Apr 7 02:39:38 groupadd[69092]: group added to /etc/group: name=builder, GID=706 <86>Apr 7 02:39:38 groupadd[69092]: group added to /etc/gshadow: name=builder <86>Apr 7 02:39:38 groupadd[69092]: new group: name=builder, GID=706 <86>Apr 7 02:39:38 useradd[69109]: new user: name=builder, UID=706, GID=706, home=/usr/src, shell=/bin/bash <13>Apr 7 02:39:40 rpmi: libruby-2.5.1-alt0.M80P.1 1525659669 installed <13>Apr 7 02:39:40 rpmi: libyaml2-0.1.6-alt1 1397147705 installed <13>Apr 7 02:39:40 rpmi: libverto-0.2.6-alt1_6 1455633234 installed <13>Apr 7 02:39:40 rpmi: libgdbm-1.8.3-alt10 1454943313 installed <13>Apr 7 02:39:40 rpmi: libcom_err-1.42.13-alt2 1449075846 installed <13>Apr 7 02:39:40 rpmi: ca-certificates-2016.02.25-alt1 1462368370 installed <13>Apr 7 02:39:40 rpmi: libcrypto10-1.0.2n-alt0.M80P.1 1512766129 installed <13>Apr 7 02:39:40 rpmi: ruby-2.5.1-alt0.M80P.1 1525659669 installed <13>Apr 7 02:39:40 rpmi: libssl10-1.0.2n-alt0.M80P.1 1512766129 installed <86>Apr 7 02:39:40 groupadd[81044]: group added to /etc/group: name=_keytab, GID=499 <86>Apr 7 02:39:40 groupadd[81044]: group added to /etc/gshadow: name=_keytab <86>Apr 7 02:39:40 groupadd[81044]: new group: name=_keytab, GID=499 <13>Apr 7 02:39:40 rpmi: libkrb5-1.14.6-alt1.M80P.1 1525355673 installed <13>Apr 7 02:39:40 rpmi: ruby-stdlibs-2.5.1-alt0.M80P.1 1525659669 installed Installing auto-nng-1.7-alt2_3.1.src.rpm Building target platforms: x86_64 Building for target x86_64 Executing(%prep): /bin/sh -e /usr/src/tmp/rpm-tmp.43146 + 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/tar -xf - + /bin/gzip -dc /usr/src/RPM/SOURCES/auto-nng.v1.7.tar.gz + 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.43146 + umask 022 + /bin/mkdir -p /usr/src/RPM/BUILD + cd /usr/src/RPM/BUILD + cd auto-nng.v1.7 + make 'CFLAGS=-pipe -Wall -g -O2' make: Entering directory `/usr/src/RPM/BUILD/auto-nng.v1.7' cc -pipe -Wall -g -O2 -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] 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] 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] double *continuous_input_stats; ^ auto-nng.c:910:140: warning: 'continuous_output_stats' may be used uninitialized in this function [-Wmaybe-uninitialized] printf(DOUBLE_FORMAT, read_indicators(low_indicator, high_indicator) * continuous_output_stats[2*j+1] + continuous_output_stats[2*j]); ^ auto-nng.c:775:8: warning: 'continuous_output_cols' may be used uninitialized in this function [-Wmaybe-uninitialized] int *continuous_output_cols; ^ auto-nng.c:897:33: warning: 'binary_output_cols' may be used uninitialized in this function [-Wmaybe-uninitialized] if (binary_output_cols[j] == i) { ^ auto-nng.c:770:8: warning: 'continuous_input_cols' may be used uninitialized in this function [-Wmaybe-uninitialized] int *continuous_input_cols; ^ auto-nng.c:768:8: warning: 'binary_input_cols' may be used uninitialized in this function [-Wmaybe-uninitialized] int *binary_input_cols; ^ make: Leaving directory `/usr/src/RPM/BUILD/auto-nng.v1.7' + exit 0 Executing(%install): /bin/sh -e /usr/src/tmp/rpm-tmp.64764 + 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) 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) Hardlinking identical .pyc and .pyo files Executing(%check): /bin/sh -e /usr/src/tmp/rpm-tmp.64764 + 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: 0.994871 / Test error: 0.993501 / Layer sizes: 10 10 1 Training error: 0.994242 / Test error: 0.991848 / Layer sizes: 10 10 10 1 Training error: 0.991006 / Test error: 0.986974 / Layer sizes: 10 10 1 Training error: 0.977329 / Test error: 0.985306 / Layer sizes: 10 1 Training error: 0.984463 / Test error: 0.977578 / Layer sizes: 10 3 3 1 Training error: 0.986589 / Test error: 0.976774 / Layer sizes: 10 10 1 Training error: 0.979674 / Test error: 0.966694 / Layer sizes: 10 10 1 Training error: 0.974156 / Test error: 0.960317 / Layer sizes: 10 10 1 Training error: 0.970378 / Test error: 0.953053 / Layer sizes: 10 10 1 Training error: 0.961186 / Test error: 0.941845 / Layer sizes: 10 10 1 Training error: 0.960990 / Test error: 0.941640 / Layer sizes: 10 10 1 Training error: 0.960581 / Test error: 0.941559 / Layer sizes: 10 10 1 Training error: 0.944293 / Test error: 0.933627 / Layer sizes: 10 7 1 Training error: 0.956666 / Test error: 0.933152 / Layer sizes: 10 10 1 Training error: 0.954854 / Test error: 0.931458 / Layer sizes: 10 1 Training error: 0.953898 / Test error: 0.931388 / Layer sizes: 10 10 1 Training error: 0.958368 / Test error: 0.929614 / Layer sizes: 10 10 10 1 Training error: 0.942947 / Test error: 0.925681 / Layer sizes: 10 7 1 Training error: 0.957345 / Test error: 0.923236 / Layer sizes: 10 10 10 1 Training error: 0.904363 / Test error: 0.913138 / Layer sizes: 10 1 Training error: 0.939864 / Test error: 0.912279 / Layer sizes: 10 7 1 Training error: 0.950119 / Test error: 0.910897 / Layer sizes: 10 10 10 1 Training error: 0.929143 / Test error: 0.906102 / Layer sizes: 10 7 1 Training error: 0.926274 / Test error: 0.896881 / Layer sizes: 10 10 1 Training error: 0.926220 / Test error: 0.896609 / Layer sizes: 10 10 1 Training error: 0.919872 / Test error: 0.892182 / Layer sizes: 10 10 1 Training error: 0.890895 / Test error: 0.881261 / Layer sizes: 10 1 Training error: 0.918803 / Test error: 0.878617 / Layer sizes: 10 10 1 Training error: 0.876919 / Test error: 0.843458 / Layer sizes: 10 1 Training error: 0.849196 / Test error: 0.825042 / Layer sizes: 10 1 Training error: 0.792503 / Test error: 0.800850 / Layer sizes: 10 1 Training error: 0.778044 / Test error: 0.793216 / Layer sizes: 10 1 Training error: 0.772725 / Test error: 0.790018 / Layer sizes: 10 1 Training error: 0.756345 / Test error: 0.776944 / Layer sizes: 10 1 Training error: 0.743639 / Test error: 0.774185 / Layer sizes: 10 1 Training error: 0.711561 / Test error: 0.731139 / Layer sizes: 10 1 Training error: 0.699403 / Test error: 0.712456 / Layer sizes: 10 1 Training error: 0.697909 / Test error: 0.711433 / Layer sizes: 10 1 Training error: 0.665862 / Test error: 0.671791 / Layer sizes: 10 1 Training error: 0.658815 / Test error: 0.669094 / Layer sizes: 10 1 Training error: 0.657664 / Test error: 0.661498 / Layer sizes: 10 1 Training error: 0.649304 / Test error: 0.654750 / Layer sizes: 10 1 Training error: 0.647207 / Test error: 0.649244 / Layer sizes: 10 1 Training error: 0.633447 / Test error: 0.637003 / Layer sizes: 10 1 Training error: 0.627958 / Test error: 0.626405 / Layer sizes: 10 1 Training error: 0.618595 / Test error: 0.613053 / Layer sizes: 10 1 Training error: 0.609990 / Test error: 0.603594 / Layer sizes: 10 1 Training error: 0.601079 / Test error: 0.592174 / Layer sizes: 10 1 Training error: 0.599271 / Test error: 0.591350 / Layer sizes: 10 1 Training error: 0.588335 / Test error: 0.580003 / Layer sizes: 10 1 Training error: 0.584971 / Test error: 0.573921 / Layer sizes: 10 1 Training error: 0.580643 / Test error: 0.563028 / Layer sizes: 10 1 Training error: 0.575840 / Test error: 0.552629 / Layer sizes: 10 1 Training error: 0.575540 / Test error: 0.545840 / Layer sizes: 10 1 Training error: 0.574669 / Test error: 0.545322 / Layer sizes: 10 1 Training error: 0.565164 / Test error: 0.542441 / Layer sizes: 10 1 Training error: 0.554991 / Test error: 0.537157 / Layer sizes: 10 1 Training error: 0.554017 / Test error: 0.531324 / Layer sizes: 10 1 Training error: 0.550373 / Test error: 0.528440 / Layer sizes: 10 1 Training error: 0.569812 / Test error: 0.528373 / Layer sizes: 10 3 1 Training error: 0.567111 / Test error: 0.515471 / Layer sizes: 10 3 1 Training error: 0.545838 / Test error: 0.508093 / Layer sizes: 10 1 Training error: 0.563164 / Test error: 0.503161 / Layer sizes: 10 3 1 Training error: 0.561477 / Test error: 0.497268 / Layer sizes: 10 3 1 Training error: 0.543452 / Test error: 0.491418 / Layer sizes: 10 1 Training error: 0.537673 / Test error: 0.490999 / Layer sizes: 10 1 Training error: 0.531221 / Test error: 0.478818 / Layer sizes: 10 1 Training error: 0.528240 / Test error: 0.468312 / Layer sizes: 10 1 Training error: 0.524411 / Test error: 0.464995 / Layer sizes: 10 1 Training error: 0.522013 / Test error: 0.460841 / Layer sizes: 10 1 Training error: 0.518938 / Test error: 0.458258 / Layer sizes: 10 1 Training error: 0.449271 / Test error: 0.457779 / Layer sizes: 10 7 1 Training error: 0.445067 / Test error: 0.453906 / Layer sizes: 10 7 1 Training error: 0.440095 / Test error: 0.450465 / Layer sizes: 10 7 1 Training error: 0.436378 / Test error: 0.448231 / Layer sizes: 10 7 1 Training error: 0.433442 / Test error: 0.433495 / Layer sizes: 10 7 1 Training error: 0.438355 / Test error: 0.422297 / Layer sizes: 10 10 10 1 Training error: 0.437629 / Test error: 0.403491 / Layer sizes: 10 10 10 1 Training error: 0.410790 / Test error: 0.392200 / Layer sizes: 10 10 10 1 Training error: 0.407868 / Test error: 0.387265 / Layer sizes: 10 10 10 1 Training error: 0.377348 / Test error: 0.386277 / Layer sizes: 10 3 1 Training error: 0.375847 / Test error: 0.380121 / Layer sizes: 10 3 1 Training error: 0.368360 / Test error: 0.379873 / Layer sizes: 10 3 1 Training error: 0.230760 / Test error: 0.378054 / Layer sizes: 10 7 1 Training error: 0.309371 / Test error: 0.370531 / Layer sizes: 10 9 4 1 Training error: 0.308145 / Test error: 0.366499 / Layer sizes: 10 9 4 1 Training error: 0.221165 / Test error: 0.365195 / Layer sizes: 10 7 1 Training error: 0.196413 / Test error: 0.358125 / Layer sizes: 10 7 1 Training error: 0.177795 / Test error: 0.355824 / Layer sizes: 10 7 1 Training error: 0.170981 / Test error: 0.354269 / Layer sizes: 10 7 1 Training error: 0.168215 / Test error: 0.353166 / Layer sizes: 10 7 1 Training error: 0.165803 / Test error: 0.351336 / Layer sizes: 10 7 1 Training error: 0.164922 / Test error: 0.350340 / Layer sizes: 10 7 1 Training error: 0.146798 / Test error: 0.347746 / Layer sizes: 10 7 1 Training error: 0.145768 / Test error: 0.337669 / Layer sizes: 10 7 1 Training error: 0.144843 / Test error: 0.335569 / Layer sizes: 10 7 1 Training error: 0.140220 / Test error: 0.328788 / Layer sizes: 10 7 1 Training error: 0.139667 / Test error: 0.326504 / Layer sizes: 10 7 1 Training error: 0.138970 / Test error: 0.321625 / Layer sizes: 10 7 1 Training error: 0.115896 / Test error: 0.317901 / Layer sizes: 10 7 1 Training error: 0.115287 / Test error: 0.312978 / Layer sizes: 10 7 1 Training error: 0.112377 / Test error: 0.308926 / Layer sizes: 10 7 1 Training error: 0.111694 / Test error: 0.304410 / Layer sizes: 10 7 1 Training error: 0.110107 / Test error: 0.297936 / Layer sizes: 10 7 1 Training error: 0.104595 / Test error: 0.295335 / Layer sizes: 10 7 1 Training error: 0.104004 / Test error: 0.287542 / Layer sizes: 10 7 1 Training error: 0.103957 / Test error: 0.285673 / Layer sizes: 10 7 1 Training error: 0.100938 / Test error: 0.279633 / Layer sizes: 10 7 1 Training error: 0.100347 / Test error: 0.277687 / Layer sizes: 10 7 1 Training error: 0.071094 / Test error: 0.275176 / Layer sizes: 10 7 1 Training error: 0.064613 / Test error: 0.275040 / Layer sizes: 10 7 1 Training error: 0.064337 / Test error: 0.271560 / Layer sizes: 10 7 1 Training error: 0.063626 / Test error: 0.266569 / Layer sizes: 10 7 1 Training error: 0.042457 / Test error: 0.265680 / Layer sizes: 10 7 1 Training error: 0.041748 / Test error: 0.263648 / Layer sizes: 10 7 1 Training error: 0.041670 / Test error: 0.260591 / Layer sizes: 10 7 1 Training error: 0.041357 / Test error: 0.254354 / Layer sizes: 10 7 1 Training error: 0.041288 / Test error: 0.253409 / Layer sizes: 10 7 1 Training error: 0.030473 / Test error: 0.251543 / Layer sizes: 10 7 1 Training error: 0.059121 / Test error: 0.249850 / Layer sizes: 10 10 1 Training error: 0.057970 / Test error: 0.249061 / Layer sizes: 10 10 1 Training error: 0.055280 / Test error: 0.248713 / Layer sizes: 10 10 1 Training error: 0.054377 / Test error: 0.245141 / Layer sizes: 10 10 1 Training error: 0.053380 / Test error: 0.241695 / Layer sizes: 10 10 1 Training error: 0.048006 / Test error: 0.240457 / Layer sizes: 10 10 1 Training error: 0.047864 / Test error: 0.238380 / Layer sizes: 10 10 1 Training error: 0.047590 / Test error: 0.235401 / Layer sizes: 10 10 1 Training error: 0.046509 / Test error: 0.233598 / Layer sizes: 10 10 1 Training error: 0.046433 / Test error: 0.232290 / Layer sizes: 10 10 1 Training error: 0.046420 / Test error: 0.231202 / Layer sizes: 10 10 1 Training error: 0.046134 / Test error: 0.227474 / Layer sizes: 10 10 1 Training error: 0.014200 / Test error: 0.224998 / Layer sizes: 10 7 1 Training error: 0.014074 / Test error: 0.219816 / Layer sizes: 10 7 1 Training error: 0.013958 / Test error: 0.217510 / Layer sizes: 10 7 1 Training error: 0.013532 / Test error: 0.217385 / Layer sizes: 10 7 1 Training error: 0.018549 / Test error: 0.217185 / Layer sizes: 10 10 1 Training error: 0.018160 / Test error: 0.215567 / Layer sizes: 10 10 1 Training error: 0.018016 / Test error: 0.214266 / Layer sizes: 10 10 1 Training error: 0.016185 / Test error: 0.210976 / Layer sizes: 10 10 1 Training error: 0.015785 / Test error: 0.210494 / Layer sizes: 10 10 1 Training error: 0.015419 / Test error: 0.210186 / Layer sizes: 10 10 1 Training error: 0.015123 / Test error: 0.206536 / Layer sizes: 10 10 1 Training error: 0.015104 / Test error: 0.205344 / Layer sizes: 10 10 1 Training error: 0.015096 / Test error: 0.199457 / Layer sizes: 10 10 1 Training error: 0.014903 / Test error: 0.194776 / Layer sizes: 10 10 1 Training error: 0.014882 / Test error: 0.191305 / Layer sizes: 10 10 1 Training error: 0.014867 / Test error: 0.189988 / Layer sizes: 10 10 1 Training error: 0.014852 / Test error: 0.186642 / Layer sizes: 10 10 1 Training error: 0.014516 / Test error: 0.185798 / Layer sizes: 10 10 1 Training error: 0.014502 / Test error: 0.182841 / Layer sizes: 10 10 1 Training error: 0.014426 / Test error: 0.180128 / Layer sizes: 10 10 1 Training error: 0.007917 / Test error: 0.180123 / Layer sizes: 10 10 1 Training error: 0.007905 / Test error: 0.179463 / Layer sizes: 10 10 1 Training error: 0.007872 / Test error: 0.177066 / Layer sizes: 10 10 1 Training error: 0.007189 / Test error: 0.176733 / Layer sizes: 10 10 1 Training error: 0.003745 / Test error: 0.172001 / Layer sizes: 10 10 1 Training error: 0.003733 / Test error: 0.169825 / Layer sizes: 10 10 1 Training error: 0.003711 / Test error: 0.158983 / Layer sizes: 10 10 1 Training error: 0.003690 / Test error: 0.157473 / Layer sizes: 10 10 1 Training error: 0.003681 / Test error: 0.149634 / Layer sizes: 10 10 1 Training error: 0.003637 / Test error: 0.143358 / Layer sizes: 10 10 1 Training error: 0.003630 / Test error: 0.142956 / Layer sizes: 10 10 1 Training error: 0.003621 / Test error: 0.142609 / Layer sizes: 10 10 1 Training error: 0.003596 / Test error: 0.141800 / Layer sizes: 10 10 1 Training error: 0.003449 / Test error: 0.141363 / Layer sizes: 10 10 1 Training error: 0.003437 / Test error: 0.140645 / Layer sizes: 10 10 1 Training error: 0.000096 / Test error: 0.122695 / Layer sizes: 10 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. 87.89 % correct. 12.11 % wrong. Limit: 17.06 %. 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.74070 + 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.eMU1us 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.S2SCK0 find-requires: running scripts (cpp,debuginfo,files,lib,pam,perl,pkgconfig,pkgconfiglib,python,rpmlib,shebang,shell,static,symlinks) Requires: /lib64/ld-linux-x86-64.so.2, libc.so.6(GLIBC_2.14)(64bit), libc.so.6(GLIBC_2.2.5)(64bit), libc.so.6(GLIBC_2.3.4)(64bit), libc.so.6(GLIBC_2.4)(64bit), libm.so.6(GLIBC_2.2.5)(64bit), rtld(GNU_HASH) Finding debuginfo files (using /usr/lib/rpm/find-debuginfo-files) Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.SYITJB 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.Az6tsf find-provides: running scripts (debuginfo) Finding Requires (using /usr/lib/rpm/find-requires) Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.UF0yUV find-requires: running scripts (debuginfo) Requires: auto-nng = 1.7-alt2_3.1, /usr/lib/debug/lib64/ld-linux-x86-64.so.2.debug, debug64(libc.so.6), debug64(libm.so.6) Wrote: /usr/src/RPM/RPMS/x86_64/auto-nng-1.7-alt2_3.1.x86_64.rpm Wrote: /usr/src/RPM/RPMS/x86_64/auto-nng-debuginfo-1.7-alt2_3.1.x86_64.rpm 56.39user 0.41system 1:36.62elapsed 58%CPU (0avgtext+0avgdata 44256maxresident)k 0inputs+0outputs (0major+149288minor)pagefaults 0swaps 59.26user 2.37system 1:42.23elapsed 60%CPU (0avgtext+0avgdata 122064maxresident)k 0inputs+0outputs (0major+369012minor)pagefaults 0swaps --- auto-nng-1.7-alt2_3.1.x86_64.rpm.repo 2013-04-03 05:20:55.000000000 +0000 +++ auto-nng-1.7-alt2_3.1.x86_64.rpm.hasher 2019-04-07 02:41:18.833810113 +0000 @@ -5,2 +5,3 @@ Requires: /lib64/ld-linux-x86-64.so.2 +Requires: libc.so.6(GLIBC_2.14)(64bit) Requires: libc.so.6(GLIBC_2.2.5)(64bit)