<86>Apr 21 02:23:13 userdel[117883]: delete user 'rooter' <86>Apr 21 02:23:13 groupadd[117940]: group added to /etc/group: name=rooter, GID=585 <86>Apr 21 02:23:13 groupadd[117940]: group added to /etc/gshadow: name=rooter <86>Apr 21 02:23:13 groupadd[117940]: new group: name=rooter, GID=585 <86>Apr 21 02:23:13 useradd[117975]: new user: name=rooter, UID=585, GID=585, home=/root, shell=/bin/bash <86>Apr 21 02:23:13 userdel[118033]: delete user 'builder' <86>Apr 21 02:23:13 userdel[118033]: removed group 'builder' owned by 'builder' <86>Apr 21 02:23:13 userdel[118033]: removed shadow group 'builder' owned by 'builder' <86>Apr 21 02:23:13 groupadd[118083]: group added to /etc/group: name=builder, GID=586 <86>Apr 21 02:23:13 groupadd[118083]: group added to /etc/gshadow: name=builder <86>Apr 21 02:23:13 groupadd[118083]: new group: name=builder, GID=586 <86>Apr 21 02:23:13 useradd[118147]: new user: name=builder, UID=586, GID=586, home=/usr/src, shell=/bin/bash <13>Apr 21 02:23:15 rpmi: libruby-2.5.1-alt0.M80P.1 1525659669 installed <13>Apr 21 02:23:15 rpmi: libyaml2-0.1.6-alt1 1397147705 installed <13>Apr 21 02:23:15 rpmi: libverto-0.2.6-alt1_6 1455633234 installed <13>Apr 21 02:23:15 rpmi: libkeyutils-1.5.10-alt0.M80P.2 p8+216694.100.6.1 1547827915 installed <13>Apr 21 02:23:15 rpmi: libgdbm-1.8.3-alt10 1454943313 installed <13>Apr 21 02:23:15 rpmi: libcom_err-1.42.13-alt2 1449075846 installed <13>Apr 21 02:23:15 rpmi: ca-certificates-2016.02.25-alt1 1462368370 installed <13>Apr 21 02:23:15 rpmi: libcrypto10-1.0.2n-alt0.M80P.1 1512766129 installed <13>Apr 21 02:23:15 rpmi: ruby-2.5.1-alt0.M80P.1 1525659669 installed <13>Apr 21 02:23:15 rpmi: libssl10-1.0.2n-alt0.M80P.1 1512766129 installed <86>Apr 21 02:23:15 groupadd[130102]: group added to /etc/group: name=_keytab, GID=499 <86>Apr 21 02:23:15 groupadd[130102]: group added to /etc/gshadow: name=_keytab <86>Apr 21 02:23:15 groupadd[130102]: new group: name=_keytab, GID=499 <13>Apr 21 02:23:15 rpmi: libkrb5-1.14.6-alt1.M80P.1 1525355673 installed <13>Apr 21 02:23:16 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.93192 + 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.93192 + 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.44348 + 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.57125 + 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: 0.995792 / Test error: 0.997838 / Layer sizes: 10 3 1 Training error: 0.994287 / Test error: 0.997203 / Layer sizes: 10 3 3 1 Training error: 0.992610 / Test error: 0.996364 / Layer sizes: 10 9 4 1 Training error: 0.986241 / Test error: 0.992370 / Layer sizes: 10 3 1 Training error: 0.979051 / Test error: 0.990272 / Layer sizes: 10 9 4 1 Training error: 0.975843 / Test error: 0.988929 / Layer sizes: 10 10 10 1 Training error: 0.972358 / Test error: 0.986996 / Layer sizes: 10 3 1 Training error: 0.966494 / Test error: 0.983008 / Layer sizes: 10 3 1 Training error: 0.896660 / Test error: 0.946164 / Layer sizes: 10 1 Training error: 0.871103 / Test error: 0.898136 / Layer sizes: 10 1 Training error: 0.858826 / Test error: 0.884453 / Layer sizes: 10 1 Training error: 0.842079 / Test error: 0.877391 / Layer sizes: 10 1 Training error: 0.791267 / Test error: 0.811980 / Layer sizes: 10 1 Training error: 0.773425 / Test error: 0.773273 / Layer sizes: 10 1 Training error: 0.756698 / Test error: 0.752285 / Layer sizes: 10 1 Training error: 0.752989 / Test error: 0.739211 / Layer sizes: 10 1 Training error: 0.727012 / Test error: 0.718177 / Layer sizes: 10 1 Training error: 0.681828 / Test error: 0.702078 / Layer sizes: 10 1 Training error: 0.666457 / Test error: 0.687964 / Layer sizes: 10 1 Training error: 0.628544 / Test error: 0.648983 / Layer sizes: 10 1 Training error: 0.621910 / Test error: 0.639446 / Layer sizes: 10 1 Training error: 0.610581 / Test error: 0.623246 / Layer sizes: 10 1 Training error: 0.586440 / Test error: 0.584095 / Layer sizes: 10 1 Training error: 0.580745 / Test error: 0.569615 / Layer sizes: 10 1 Training error: 0.580470 / Test error: 0.566635 / Layer sizes: 10 1 Training error: 0.578904 / Test error: 0.562477 / Layer sizes: 10 1 Training error: 0.575265 / Test error: 0.558171 / Layer sizes: 10 1 Training error: 0.571687 / Test error: 0.548172 / Layer sizes: 10 1 Training error: 0.558591 / Test error: 0.541739 / Layer sizes: 10 1 Training error: 0.552838 / Test error: 0.531613 / Layer sizes: 10 1 Training error: 0.541324 / Test error: 0.510195 / Layer sizes: 10 1 Training error: 0.538559 / Test error: 0.507967 / Layer sizes: 10 1 Training error: 0.517398 / Test error: 0.501104 / Layer sizes: 10 1 Training error: 0.496119 / Test error: 0.475417 / Layer sizes: 10 1 Training error: 0.480340 / Test error: 0.453790 / Layer sizes: 10 1 Training error: 0.475564 / Test error: 0.450158 / Layer sizes: 10 1 Training error: 0.466793 / Test error: 0.437814 / Layer sizes: 10 1 Training error: 0.458338 / Test error: 0.423687 / Layer sizes: 10 1 Training error: 0.450316 / Test error: 0.416002 / Layer sizes: 10 1 Training error: 0.448916 / Test error: 0.413899 / Layer sizes: 10 1 Training error: 0.429768 / Test error: 0.402242 / Layer sizes: 10 1 Training error: 0.412905 / Test error: 0.395414 / Layer sizes: 10 1 Training error: 0.409843 / Test error: 0.394571 / Layer sizes: 10 1 Training error: 0.396589 / Test error: 0.389362 / Layer sizes: 10 1 Training error: 0.391169 / Test error: 0.388776 / Layer sizes: 10 1 Training error: 0.388224 / Test error: 0.382930 / Layer sizes: 10 1 Training error: 0.383325 / Test error: 0.375526 / Layer sizes: 10 1 Training error: 0.376577 / Test error: 0.359466 / Layer sizes: 10 1 Training error: 0.358729 / Test error: 0.354472 / Layer sizes: 10 1 Training error: 0.356968 / Test error: 0.349188 / Layer sizes: 10 1 Training error: 0.341402 / Test error: 0.347784 / Layer sizes: 10 1 Training error: 0.336733 / Test error: 0.341272 / Layer sizes: 10 1 Training error: 0.332046 / Test error: 0.329162 / Layer sizes: 10 1 Training error: 0.317092 / Test error: 0.320164 / Layer sizes: 10 1 Training error: 0.344333 / Test error: 0.316089 / Layer sizes: 10 7 1 Training error: 0.342431 / Test error: 0.305032 / Layer sizes: 10 7 1 Training error: 0.340872 / Test error: 0.304509 / Layer sizes: 10 7 1 Training error: 0.332347 / Test error: 0.298859 / Layer sizes: 10 7 1 Training error: 0.303332 / Test error: 0.297000 / Layer sizes: 10 1 Training error: 0.299677 / Test error: 0.288579 / Layer sizes: 10 1 Training error: 0.294789 / Test error: 0.287217 / Layer sizes: 10 1 Training error: 0.294728 / Test error: 0.285832 / Layer sizes: 10 1 Training error: 0.293231 / Test error: 0.279828 / Layer sizes: 10 1 Training error: 0.299402 / Test error: 0.275504 / Layer sizes: 10 7 1 Training error: 0.291382 / Test error: 0.274480 / Layer sizes: 10 7 1 Training error: 0.285847 / Test error: 0.273732 / Layer sizes: 10 7 1 Training error: 0.283594 / Test error: 0.263997 / Layer sizes: 10 7 1 Training error: 0.271970 / Test error: 0.254315 / Layer sizes: 10 7 1 Training error: 0.261643 / Test error: 0.250749 / Layer sizes: 10 7 1 Training error: 0.255923 / Test error: 0.250092 / Layer sizes: 10 7 1 Training error: 0.263544 / Test error: 0.249532 / Layer sizes: 10 1 Training error: 0.261584 / Test error: 0.248682 / Layer sizes: 10 1 Training error: 0.259954 / Test error: 0.246022 / Layer sizes: 10 1 Training error: 0.259895 / Test error: 0.240448 / Layer sizes: 10 1 Training error: 0.259666 / Test error: 0.237029 / Layer sizes: 10 1 Training error: 0.247904 / Test error: 0.236480 / Layer sizes: 10 1 Training error: 0.247825 / Test error: 0.231359 / Layer sizes: 10 1 Training error: 0.247594 / Test error: 0.230087 / Layer sizes: 10 1 Training error: 0.242752 / Test error: 0.229628 / Layer sizes: 10 1 Training error: 0.242485 / Test error: 0.227469 / Layer sizes: 10 1 Training error: 0.236986 / Test error: 0.226300 / Layer sizes: 10 1 Training error: 0.231794 / Test error: 0.224118 / Layer sizes: 10 1 Training error: 0.227304 / Test error: 0.223410 / Layer sizes: 10 1 Training error: 0.226224 / Test error: 0.222579 / Layer sizes: 10 1 Training error: 0.222246 / Test error: 0.221992 / Layer sizes: 10 1 Training error: 0.207822 / Test error: 0.218987 / Layer sizes: 10 3 1 Training error: 0.206954 / Test error: 0.214263 / Layer sizes: 10 3 1 Training error: 0.206851 / Test error: 0.214025 / Layer sizes: 10 3 1 Training error: 0.205449 / Test error: 0.210984 / Layer sizes: 10 3 1 Training error: 0.161321 / Test error: 0.209991 / Layer sizes: 10 9 4 1 Training error: 0.155884 / Test error: 0.191954 / Layer sizes: 10 9 4 1 Training error: 0.151076 / Test error: 0.191818 / Layer sizes: 10 9 4 1 Training error: 0.143996 / Test error: 0.190630 / Layer sizes: 10 9 4 1 Training error: 0.137392 / Test error: 0.188318 / Layer sizes: 10 9 4 1 Training error: 0.136771 / Test error: 0.186812 / Layer sizes: 10 9 4 1 Training error: 0.134900 / Test error: 0.182331 / Layer sizes: 10 9 4 1 Training error: 0.134827 / Test error: 0.179620 / Layer sizes: 10 9 4 1 Training error: 0.133786 / Test error: 0.175145 / Layer sizes: 10 9 4 1 Training error: 0.133141 / Test error: 0.170992 / Layer sizes: 10 9 4 1 Training error: 0.132834 / Test error: 0.168054 / Layer sizes: 10 9 4 1 Training error: 0.131376 / Test error: 0.167842 / Layer sizes: 10 9 4 1 Training error: 0.131101 / Test error: 0.166642 / Layer sizes: 10 9 4 1 Training error: 0.016435 / Test error: 0.161344 / Layer sizes: 10 3 3 1 Training error: 0.016338 / Test error: 0.136930 / Layer sizes: 10 3 3 1 Training error: 0.016189 / Test error: 0.136372 / Layer sizes: 10 3 3 1 Training error: 0.001162 / Test error: 0.121604 / Layer sizes: 10 3 3 1 Training error: 0.001156 / Test error: 0.118493 / Layer sizes: 10 3 3 1 Training error: 0.001147 / Test error: 0.117283 / Layer sizes: 10 3 3 1 Training error: 0.000003 / Test error: 0.083224 / Layer sizes: 10 3 3 1 Training error: 0.000003 / Test error: 0.083191 / Layer sizes: 10 3 3 1 Training error: 0.000003 / Test error: 0.083190 / Layer sizes: 10 3 3 1 Training error: 0.000003 / Test error: 0.083186 / Layer sizes: 10 3 3 1 Training error: 0.000003 / Test error: 0.083178 / Layer 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/ Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 3 3 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. 90.11 % correct. 9.89 % wrong. Limit: 17.01 %. 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.34652 + 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.HfzP0R 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.RNuGUC 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.5F1UAq 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.Di1M4g find-provides: running scripts (debuginfo) Finding Requires (using /usr/lib/rpm/find-requires) Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.JQnqqa 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 55.37user 0.27system 1:38.18elapsed 56%CPU (0avgtext+0avgdata 44380maxresident)k 0inputs+0outputs (0major+147826minor)pagefaults 0swaps 58.44user 1.92system 1:45.32elapsed 57%CPU (0avgtext+0avgdata 121972maxresident)k 0inputs+0outputs (0major+367293minor)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 2019-04-21 02:24:56.503790294 +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)