<86>Dec 22 13:51:24 userdel[4193097]: delete user 'rooter'
<86>Dec 22 13:51:24 groupadd[4193103]: group added to /etc/group: name=rooter, GID=642
<86>Dec 22 13:51:24 groupadd[4193103]: group added to /etc/gshadow: name=rooter
<86>Dec 22 13:51:24 groupadd[4193103]: new group: name=rooter, GID=642
<86>Dec 22 13:51:24 useradd[4193107]: new user: name=rooter, UID=642, GID=642, home=/root, shell=/bin/bash
<86>Dec 22 13:51:24 userdel[4193113]: delete user 'builder'
<86>Dec 22 13:51:24 userdel[4193113]: removed group 'builder' owned by 'builder'
<86>Dec 22 13:51:24 userdel[4193113]: removed shadow group 'builder' owned by 'builder'
<86>Dec 22 13:51:24 groupadd[4193118]: group added to /etc/group: name=builder, GID=643
<86>Dec 22 13:51:24 groupadd[4193118]: group added to /etc/gshadow: name=builder
<86>Dec 22 13:51:24 groupadd[4193118]: new group: name=builder, GID=643
<86>Dec 22 13:51:24 useradd[4193122]: new user: name=builder, UID=643, GID=643, home=/usr/src, shell=/bin/bash
<13>Dec 22 13:51:26 rpmi: libruby-2.7.2-alt1.1 sisyphus+262971.100.1.1 1607192190 installed
<13>Dec 22 13:51:26 rpmi: libp11-kit-0.23.15-alt2 sisyphus+252784.100.2.2 1591274901 installed
<13>Dec 22 13:51:26 rpmi: libtasn1-4.16.0-alt1 sisyphus+245480.100.1.1 1580825062 installed
<13>Dec 22 13:51:26 rpmi: libgdbm-1.8.3-alt10 1454943334 installed
<13>Dec 22 13:51:26 rpmi: libyaml2-0.2.5-alt1 sisyphus+253672.100.1.1 1592583137 installed
<13>Dec 22 13:51:26 rpmi: rpm-macros-alternatives-0.5.1-alt1 sisyphus+226946.100.1.1 1554830426 installed
<13>Dec 22 13:51:26 rpmi: alternatives-0.5.1-alt1 sisyphus+226946.100.1.1 1554830426 installed
<13>Dec 22 13:51:26 rpmi: ca-certificates-2020.10.22-alt1 sisyphus+260224.300.2.1 1603549301 installed
<13>Dec 22 13:51:26 rpmi: ca-trust-0.1.2-alt1 sisyphus+233348.100.1.1 1561653823 installed
<13>Dec 22 13:51:26 rpmi: p11-kit-trust-0.23.15-alt2 sisyphus+252784.100.2.2 1591274901 installed
<13>Dec 22 13:51:26 rpmi: libcrypto1.1-1.1.1i-alt1 sisyphus+263103.100.1.1 1607445576 installed
<13>Dec 22 13:51:26 rpmi: libssl1.1-1.1.1i-alt1 sisyphus+263103.100.1.1 1607445576 installed
<13>Dec 22 13:51:26 rpmi: gem-minitest-5.14.1-alt0.1 sisyphus+249637.100.1.1 1586421683 installed
<13>Dec 22 13:51:26 rpmi: ruby-net-telnet-0.2.0-alt1 sisyphus+219345.2700.8.1 1547631566 installed
<13>Dec 22 13:51:26 rpmi: gem-rake-13.0.1-alt1 sisyphus+248971.320.47.1 1586259947 installed
<13>Dec 22 13:51:26 rpmi: ruby-xmlrpc-0.3.0-alt1 sisyphus+219345.3300.8.1 1547631818 installed
<13>Dec 22 13:51:26 rpmi: gem-2:3.1.2-alt1.1 sisyphus+262971.100.1.1 1607192116 installed
<13>Dec 22 13:51:26 rpmi: ri-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed
<13>Dec 22 13:51:26 rpmi: rdoc-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed
<13>Dec 22 13:51:26 rpmi: ruby-rdoc-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed
<13>Dec 22 13:51:26 rpmi: rake-13.0.1-alt1 sisyphus+248971.320.47.1 1586259947 installed
<13>Dec 22 13:51:26 rpmi: erb-0:2.7.2-alt1.1 sisyphus+262971.100.1.1 1607192116 installed
<13>Dec 22 13:51:26 rpmi: irb-2.7.2-alt1.1 sisyphus+262971.100.1.1 1607192116 installed
<13>Dec 22 13:51:26 rpmi: gem-test-unit-3.3.5-alt1 sisyphus+248971.620.47.1 1586260035 installed
<13>Dec 22 13:51:26 rpmi: gem-power-assert-1.1.7-alt1 sisyphus+248971.220.47.1 1586259894 installed
<13>Dec 22 13:51:26 rpmi: bundle-2.1.4-alt1 sisyphus+247301.1100.3.2 1583840910 installed
<13>Dec 22 13:51:27 rpmi: gem-bundler-2.1.4-alt1 sisyphus+247301.1100.3.2 1583840910 installed
<13>Dec 22 13:51:27 rpmi: ruby-2.7.2-alt1.1 sisyphus+262971.100.1.1 1607192190 installed
<13>Dec 22 13:51:28 rpmi: ruby-stdlibs-2.7.2-alt1.1 sisyphus+262971.100.1.1 1607192190 installed
Building target platforms: i586
Building for target i586
Wrote: /usr/src/in/nosrpm/auto-nng-1.7-alt2_3.1.nosrc.rpm (w1.gzdio)
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.43751
+ 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.43751
+ 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: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: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: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.86874
+ 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
+ PATH=/usr/libexec/rpm-build:/usr/src/bin:/bin:/usr/bin:/usr/X11R6/bin:/usr/games
+ 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,gnuconfig)
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.86874
+ 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: 0.990187 / Test error: 0.991412 / Layer sizes: 10 1
Training error: 0.990891 / Test error: 0.990900 / Layer sizes: 10 3 3 1
Training error: 0.987571 / Test error: 0.989513 / Layer sizes: 10 10 1
Training error: 0.979136 / Test error: 0.979102 / Layer sizes: 10 3 3 1
Training error: 0.948471 / Test error: 0.969594 / Layer sizes: 10 1
Training error: 0.955992 / Test error: 0.955933 / Layer sizes: 10 3 3 1
Training error: 0.888559 / Test error: 0.934567 / Layer sizes: 10 1
Training error: 0.880409 / Test error: 0.906110 / Layer sizes: 10 1
Training error: 0.855881 / Test error: 0.873180 / Layer sizes: 10 1
Training error: 0.852503 / Test error: 0.859057 / Layer sizes: 10 1
Training error: 0.820929 / Test error: 0.824997 / Layer sizes: 10 1
Training error: 0.806318 / Test error: 0.809389 / Layer sizes: 10 1
Training error: 0.765466 / Test error: 0.756737 / Layer sizes: 10 1
Training error: 0.762227 / Test error: 0.727697 / Layer sizes: 10 1
Training error: 0.749974 / Test error: 0.725716 / Layer sizes: 10 1
Training error: 0.734687 / Test error: 0.694655 / Layer sizes: 10 1
Training error: 0.720330 / Test error: 0.688203 / Layer sizes: 10 1
Training error: 0.710572 / Test error: 0.672472 / Layer sizes: 10 1
Training error: 0.699758 / Test error: 0.665138 / Layer sizes: 10 1
Training error: 0.694020 / Test error: 0.660016 / Layer sizes: 10 1
Training error: 0.693315 / Test error: 0.630508 / Layer sizes: 10 1
Training error: 0.646617 / Test error: 0.620482 / Layer sizes: 10 1
Training error: 0.624263 / Test error: 0.596246 / Layer sizes: 10 1
Training error: 0.621608 / Test error: 0.582602 / Layer sizes: 10 1
Training error: 0.616085 / Test error: 0.575558 / Layer sizes: 10 1
Training error: 0.608638 / Test error: 0.554205 / Layer sizes: 10 1
Training error: 0.604693 / Test error: 0.540346 / Layer sizes: 10 1
Training error: 0.595187 / Test error: 0.522586 / Layer sizes: 10 1
Training error: 0.583879 / Test error: 0.520730 / Layer sizes: 10 1
Training error: 0.580176 / Test error: 0.514268 / Layer sizes: 10 1
Training error: 0.575311 / Test error: 0.507317 / Layer sizes: 10 1
Training error: 0.569580 / Test error: 0.492185 / Layer sizes: 10 1
Training error: 0.567954 / Test error: 0.484398 / Layer sizes: 10 1
Training error: 0.563033 / Test error: 0.475387 / Layer sizes: 10 1
Training error: 0.547525 / Test error: 0.469958 / Layer sizes: 10 1
Training error: 0.544415 / Test error: 0.460686 / Layer sizes: 10 1
Training error: 0.539653 / Test error: 0.458208 / Layer sizes: 10 1
Training error: 0.536887 / Test error: 0.453366 / Layer sizes: 10 1
Training error: 0.535719 / Test error: 0.449574 / Layer sizes: 10 1
Training error: 0.528785 / Test error: 0.447361 / Layer sizes: 10 1
Training error: 0.524727 / Test error: 0.446082 / Layer sizes: 10 1
Training error: 0.522532 / Test error: 0.436116 / Layer sizes: 10 1
Training error: 0.522394 / Test error: 0.430087 / Layer sizes: 10 1
Training error: 0.522260 / Test error: 0.418016 / Layer sizes: 10 1
Training error: 0.520685 / Test error: 0.413481 / Layer sizes: 10 1
Training error: 0.519846 / Test error: 0.410871 / Layer sizes: 10 1
Training error: 0.518858 / Test error: 0.408704 / Layer sizes: 10 1
Training error: 0.517995 / Test error: 0.404318 / Layer sizes: 10 1
Training error: 0.517507 / Test error: 0.402077 / Layer sizes: 10 1
Training error: 0.514191 / Test error: 0.401685 / Layer sizes: 10 1
Training error: 0.512392 / Test error: 0.397300 / Layer sizes: 10 1
Training error: 0.508854 / Test error: 0.392019 / Layer sizes: 10 1
Training error: 0.506859 / Test error: 0.386525 / Layer sizes: 10 1
Training error: 0.503522 / Test error: 0.383711 / Layer sizes: 10 1
Training error: 0.500499 / Test error: 0.382795 / Layer sizes: 10 1
Training error: 0.499497 / Test error: 0.382169 / Layer sizes: 10 1
Training error: 0.499494 / Test error: 0.374296 / Layer sizes: 10 1
Training error: 0.470214 / Test error: 0.363405 / Layer sizes: 10 3 1
Training error: 0.464610 / Test error: 0.362764 / Layer sizes: 10 3 1
Training error: 0.459928 / Test error: 0.359163 / Layer sizes: 10 3 1
Training error: 0.459013 / Test error: 0.357852 / Layer sizes: 10 3 1
Training error: 0.457451 / Test error: 0.354696 / Layer sizes: 10 3 1
Training error: 0.442530 / Test error: 0.354109 / Layer sizes: 10 3 1
Training error: 0.441204 / Test error: 0.349386 / Layer sizes: 10 3 1
Training error: 0.400891 / Test error: 0.340094 / Layer sizes: 10 3 3 1
Training error: 0.433151 / Test error: 0.335745 / Layer sizes: 10 3 1
Training error: 0.396145 / Test error: 0.330863 / Layer sizes: 10 3 3 1
Training error: 0.393118 / Test error: 0.330116 / Layer sizes: 10 3 3 1
Training error: 0.383017 / Test error: 0.322156 / Layer sizes: 10 3 3 1
Training error: 0.421118 / Test error: 0.320869 / Layer sizes: 10 3 1
Training error: 0.363604 / Test error: 0.312821 / Layer sizes: 10 3 3 1
Training error: 0.360890 / Test error: 0.307841 / Layer sizes: 10 3 3 1
Training error: 0.358394 / Test error: 0.303783 / Layer sizes: 10 3 3 1
Training error: 0.407546 / Test error: 0.303085 / Layer sizes: 10 3 1
Training error: 0.357838 / Test error: 0.291004 / Layer sizes: 10 3 3 1
Training error: 0.348639 / Test error: 0.283073 / Layer sizes: 10 3 3 1
Training error: 0.333614 / Test error: 0.272173 / Layer sizes: 10 3 3 1
Training error: 0.377645 / Test error: 0.269862 / Layer sizes: 10 3 1
Training error: 0.377146 / Test error: 0.266987 / Layer sizes: 10 3 1
Training error: 0.376474 / Test error: 0.264204 / Layer sizes: 10 3 1
Training error: 0.358321 / Test error: 0.261026 / Layer sizes: 10 3 1
Training error: 0.356330 / Test error: 0.256032 / Layer sizes: 10 3 1
Training error: 0.228649 / Test error: 0.252376 / Layer sizes: 10 3 3 1
Training error: 0.207595 / Test error: 0.239259 / Layer sizes: 10 3 3 1
Training error: 0.196692 / Test error: 0.239118 / Layer sizes: 10 3 3 1
Training error: 0.194743 / Test error: 0.238911 / Layer sizes: 10 3 3 1
Training error: 0.152965 / Test error: 0.238306 / Layer sizes: 10 3 1
Training error: 0.152249 / Test error: 0.225011 / Layer sizes: 10 3 1
Training error: 0.151043 / Test error: 0.217386 / Layer sizes: 10 3 1
Training error: 0.149570 / Test error: 0.208077 / Layer sizes: 10 3 1
Training error: 0.132008 / Test error: 0.206228 / Layer sizes: 10 3 1
Training error: 0.128964 / Test error: 0.204284 / Layer sizes: 10 3 1
Training error: 0.126280 / Test error: 0.196041 / Layer sizes: 10 3 1
Training error: 0.116883 / Test error: 0.190749 / Layer sizes: 10 3 1
Training error: 0.115190 / Test error: 0.177160 / Layer sizes: 10 3 1
Training error: 0.105563 / Test error: 0.173916 / Layer sizes: 10 3 1
Training error: 0.100468 / Test error: 0.168847 / Layer sizes: 10 3 1
Training error: 0.100143 / Test error: 0.166722 / Layer sizes: 10 3 1
Training error: 0.099001 / Test error: 0.152565 / Layer sizes: 10 3 1
Training error: 0.098946 / Test error: 0.147384 / Layer sizes: 10 3 1
Training error: 0.097953 / Test error: 0.145973 / Layer sizes: 10 3 1
Training error: 0.097069 / Test error: 0.140809 / Layer sizes: 10 3 1
Training error: 0.095726 / Test error: 0.136080 / Layer sizes: 10 3 1
Training error: 0.077315 / Test error: 0.131922 / Layer sizes: 10 3 1
Training error: 0.076951 / Test error: 0.126828 / Layer sizes: 10 3 1
Training error: 0.076736 / Test error: 0.126627 / Layer sizes: 10 3 1
Training error: 0.075000 / Test error: 0.115663 / Layer sizes: 10 3 1
Training error: 0.073924 / Test error: 0.115230 / Layer sizes: 10 3 1
Training error: 0.049143 / Test error: 0.102056 / Layer sizes: 10 3 1
Training error: 0.039340 / Test error: 0.100270 / Layer sizes: 10 3 1
Training error: 0.039086 / Test error: 0.099281 / Layer sizes: 10 3 1
Training error: 0.038253 / Test error: 0.095759 / Layer sizes: 10 3 1
Training error: 0.037602 / Test error: 0.093346 / Layer sizes: 10 3 1
Training error: 0.036158 / Test error: 0.091505 / Layer sizes: 10 3 1
Training error: 0.036140 / Test error: 0.089390 / Layer sizes: 10 3 1
Training error: 0.028795 / Test error: 0.087069 / Layer sizes: 10 3 1
Training error: 0.034262 / Test error: 0.083121 / Layer sizes: 10 7 1
Training error: 0.033929 / Test error: 0.079674 / Layer sizes: 10 7 1
Training error: 0.033290 / Test error: 0.077638 / Layer sizes: 10 7 1
Training error: 0.032950 / Test error: 0.077627 / Layer sizes: 10 7 1
Training error: 0.032790 / Test error: 0.074227 / Layer sizes: 10 7 1
Training error: 0.031281 / Test error: 0.072592 / Layer sizes: 10 7 1
Training error: 0.030936 / Test error: 0.067207 / Layer sizes: 10 7 1
Training error: 0.030643 / Test error: 0.065652 / Layer sizes: 10 7 1
Training error: 0.030319 / Test error: 0.062196 / Layer sizes: 10 7 1
Training error: 0.030066 / Test error: 0.060023 / Layer sizes: 10 7 1
Training error: 0.029638 / Test error: 0.054921 / Layer sizes: 10 7 1
Training error: 0.026472 / Test error: 0.054798 / Layer sizes: 10 7 1
Training error: 0.025594 / Test error: 0.054029 / Layer sizes: 10 7 1
Training error: 0.025117 / Test error: 0.052355 / Layer sizes: 10 7 1
Training error: 0.024979 / Test error: 0.052109 / Layer sizes: 10 7 1
Training error: 0.022814 / Test error: 0.050877 / Layer sizes: 10 7 1
Training error: 0.022582 / Test error: 0.048356 / Layer sizes: 10 7 1
Training error: 0.022120 / Test error: 0.044777 / Layer sizes: 10 7 1
Training error: 0.021547 / Test error: 0.041833 / Layer sizes: 10 7 1
Training error: 0.019946 / Test error: 0.041368 / Layer sizes: 10 7 1
Training error: 0.019886 / Test error: 0.040323 / Layer sizes: 10 7 1
Training error: 0.018058 / Test error: 0.038834 / Layer sizes: 10 7 1
Training error: 0.017956 / Test error: 0.037136 / Layer sizes: 10 7 1
Training error: 0.017760 / Test error: 0.034845 / Layer sizes: 10 7 1
Training error: 0.017672 / Test error: 0.033318 / Layer sizes: 10 7 1
Training error: 0.014473 / Test error: 0.033181 / Layer sizes: 10 7 1
Training error: 0.014418 / Test error: 0.033145 / Layer sizes: 10 7 1
Training error: 0.014157 / Test error: 0.029600 / Layer sizes: 10 7 1
Training error: 0.013302 / Test error: 0.026401 / Layer sizes: 10 7 1
Training error: 0.013298 / Test error: 0.025015 / Layer sizes: 10 7 1
Training error: 0.013281 / Test error: 0.024868 / Layer sizes: 10 7 1
Training error: 0.013174 / Test error: 0.024038 / Layer sizes: 10 7 1
Training error: 0.013122 / Test error: 0.023866 / Layer sizes: 10 7 1
Training error: 0.013061 / Test error: 0.022855 / Layer sizes: 10 7 1
Training error: 0.013022 / Test error: 0.022491 / Layer sizes: 10 7 1
Training error: 0.012960 / Test error: 0.021936 / Layer sizes: 10 7 1
Training error: 0.012858 / Test error: 0.021835 / Layer sizes: 10 7 1
Training error: 0.012664 / Test error: 0.020941 / Layer sizes: 10 7 1
Training error: 0.012479 / Test error: 0.020764 / Layer sizes: 10 7 1
Training error: 0.012375 / Test error: 0.020713 / Layer sizes: 10 7 1
Training error: 0.010965 / Test error: 0.019753 / Layer sizes: 10 7 1
Training error: 0.010883 / Test error: 0.019430 / Layer sizes: 10 7 1
Training error: 0.010874 / Test error: 0.019027 / Layer sizes: 10 7 1
Training error: 0.006664 / Test error: 0.018746 / Layer sizes: 10 7 1
Training error: 0.006633 / Test error: 0.016479 / Layer sizes: 10 7 1
Training error: 0.005856 / Test error: 0.016099 / Layer sizes: 10 7 1
Training error: 0.005821 / Test error: 0.014527 / Layer sizes: 10 7 1
Training error: 0.005753 / Test error: 0.013942 / Layer sizes: 10 7 1
Training error: 0.005745 / Test error: 0.013825 / Layer sizes: 10 7 1
Training error: 0.005726 / Test error: 0.012125 / Layer sizes: 10 7 1
Training error: 0.005068 / Test error: 0.011868 / Layer sizes: 10 7 1
Training error: 0.005060 / Test error: 0.009178 / Layer sizes: 10 7 1
Training error: 0.005020 / Test error: 0.008522 / Layer sizes: 10 7 1
Training error: 0.005009 / Test error: 0.008488 / Layer sizes: 10 7 1
Training error: 0.004908 / Test error: 0.008430 / Layer sizes: 10 7 1
Training error: 0.004866 / Test error: 0.008314 / Layer sizes: 10 7 1
Training error: 0.004833 / Test error: 0.007896 / Layer sizes: 10 7 1
Training error: 0.000161 / Test error: 0.000223 / Layer sizes: 10 9 4 1
Training error: 0.000140 / Test error: 0.000202 / Layer sizes: 10 9 4 1
Training error: 0.000001 / Test error: 0.000001 / Layer sizes: 10 9 4 1
Training error: 0.000001 / Test error: 0.000001 / Layer sizes: 10 9 4 1
Training error: 0.000001 / Test error: 0.000001 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 9 4 1
Training error: 0.000000 / Test error: 0.000000 / 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.
85.40 % correct.
14.60 % wrong.
Limit: 18.06 %.
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.34489
+ 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.Zp0oKy
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.RwOfjA
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_2.1.3), 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.6ptwQw
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.lyUa7w
find-provides: running scripts (debuginfo)
Finding Requires (using /usr/lib/rpm/find-requires)
Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.nCwflB
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 (w2.lzdio)
Wrote: /usr/src/RPM/RPMS/i586/auto-nng-debuginfo-1.7-alt2_3.1.i586.rpm (w2.lzdio)
91.38user 0.51system 1:38.89elapsed 92%CPU (0avgtext+0avgdata 36416maxresident)k
0inputs+0outputs (0major+172365minor)pagefaults 0swaps
97.31user 3.25system 1:48.11elapsed 93%CPU (0avgtext+0avgdata 108944maxresident)k
0inputs+0outputs (0major+490635minor)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 2020-12-22 13:53:10.667549887 +0000
@@ -7,2 +7,3 @@
Requires: libc.so.6(GLIBC_2.1)
+Requires: libc.so.6(GLIBC_2.1.3)
Requires: libc.so.6(GLIBC_2.3.4)
@@ -11,2 +12,3 @@
Requires: libm.so.6(GLIBC_2.1)
+Requires: libm.so.6(GLIBC_2.29)
Requires: rtld(GNU_HASH)