<86>Mar 16 13:56:31 userdel[1100264]: delete user 'rooter' <86>Mar 16 13:56:31 userdel[1100264]: removed group 'rooter' owned by 'rooter' <86>Mar 16 13:56:31 groupadd[1100278]: group added to /etc/group: name=rooter, GID=699 <86>Mar 16 13:56:31 groupadd[1100278]: group added to /etc/gshadow: name=rooter <86>Mar 16 13:56:31 groupadd[1100278]: new group: name=rooter, GID=699 <86>Mar 16 13:56:31 useradd[1100289]: new user: name=rooter, UID=699, GID=699, home=/root, shell=/bin/bash <86>Mar 16 13:56:31 userdel[1100310]: delete user 'builder' <86>Mar 16 13:56:31 userdel[1100310]: removed group 'builder' owned by 'builder' <86>Mar 16 13:56:31 userdel[1100310]: removed shadow group 'builder' owned by 'builder' <86>Mar 16 13:56:31 groupadd[1100323]: group added to /etc/group: name=builder, GID=700 <86>Mar 16 13:56:31 groupadd[1100323]: group added to /etc/gshadow: name=builder <86>Mar 16 13:56:31 groupadd[1100323]: new group: name=builder, GID=700 <86>Mar 16 13:56:31 useradd[1100332]: new user: name=builder, UID=700, GID=700, home=/usr/src, shell=/bin/bash <13>Mar 16 13:56:34 rpmi: libruby-2.5.5-alt4.2 sisyphus+246908.100.1.1 1582630167 installed <13>Mar 16 13:56:34 rpmi: libp11-kit-0.23.15-alt1 sisyphus+226408.100.2.1 1554288204 installed <13>Mar 16 13:56:34 rpmi: libtasn1-4.16.0-alt1 sisyphus+245480.100.1.1 1580825062 installed <13>Mar 16 13:56:34 rpmi: libgdbm-1.8.3-alt10 1454943334 installed <13>Mar 16 13:56:34 rpmi: libyaml2-0.2.2-alt1 sisyphus+229134.100.1.1 1557342721 installed <13>Mar 16 13:56:34 rpmi: rpm-macros-alternatives-0.5.1-alt1 sisyphus+226946.100.1.1 1554830426 installed <13>Mar 16 13:56:34 rpmi: alternatives-0.5.1-alt1 sisyphus+226946.100.1.1 1554830426 installed <13>Mar 16 13:56:34 rpmi: ca-certificates-2020.01.23-alt1 sisyphus+244791.300.2.1 1580285500 installed <13>Mar 16 13:56:34 rpmi: ca-trust-0.1.2-alt1 sisyphus+233348.100.1.1 1561653823 installed <13>Mar 16 13:56:34 rpmi: p11-kit-trust-0.23.15-alt1 sisyphus+226408.100.2.1 1554288204 installed <13>Mar 16 13:56:34 rpmi: libcrypto1.1-1.1.1d-alt1.1 sisyphus+237931.100.2.1 1569235729 installed <13>Mar 16 13:56:34 rpmi: libssl1.1-1.1.1d-alt1.1 sisyphus+237931.100.2.1 1569235729 installed <13>Mar 16 13:56:34 rpmi: openssl-1.1.1d-alt1.1 sisyphus+237931.100.2.1 1569235729 installed <13>Mar 16 13:56:34 rpmi: ruby-rubygems-update-3.0.4-alt1 sisyphus+231621.240.57.1 1567243682 installed <13>Mar 16 13:56:34 rpmi: gem-did-you-mean-1.3.0-alt2.1 sisyphus+237310.1100.2.1 1568211939 installed <13>Mar 16 13:56:34 rpmi: ruby-minitest-5.11.3-alt1 sisyphus+219345.3500.8.1 1547631954 installed <13>Mar 16 13:56:34 rpmi: ruby-net-telnet-0.2.0-alt1 sisyphus+219345.2700.8.1 1547631566 installed <13>Mar 16 13:56:34 rpmi: gem-power-assert-1.1.4-alt1 sisyphus+226411.3200.6.1 1554380195 installed <13>Mar 16 13:56:34 rpmi: ruby-test-unit-1:3.3.1-alt1 sisyphus+226411.5300.6.1 1554381151 installed <13>Mar 16 13:56:34 rpmi: ruby-xmlrpc-0.3.0-alt1 sisyphus+219345.3300.8.1 1547631818 installed <13>Mar 16 13:56:34 rpmi: gem-2.5.5-alt4.2 sisyphus+246908.100.1.1 1582630116 installed <13>Mar 16 13:56:34 rpmi: ri-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed <13>Mar 16 13:56:34 rpmi: rdoc-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed <13>Mar 16 13:56:34 rpmi: ruby-rdoc-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed <13>Mar 16 13:56:34 rpmi: erb-2.5.5-alt4.2 sisyphus+246908.100.1.1 1582630116 installed <13>Mar 16 13:56:34 rpmi: irb-2.5.5-alt4.2 sisyphus+246908.100.1.1 1582630116 installed <13>Mar 16 13:56:34 rpmi: rake-12.3.3-alt1 sisyphus+238087.3100.11.1 1569616589 installed <13>Mar 16 13:56:34 rpmi: ruby-rake-12.3.3-alt1 sisyphus+238087.3100.11.1 1569616589 installed <13>Mar 16 13:56:35 rpmi: ruby-stdlibs-2.5.5-alt4.2 sisyphus+246908.100.1.1 1582630167 installed <13>Mar 16 13:56:35 rpmi: bundle-2.1.4-alt1 sisyphus+247301.1100.3.2 1583840910 installed <13>Mar 16 13:56:35 rpmi: ruby-2.5.5-alt4.2 sisyphus+246908.100.1.1 1582630167 installed <13>Mar 16 13:56:36 rpmi: gem-bundler-2.1.4-alt1 sisyphus+247301.1100.3.2 1583840910 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.94893 + 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.94893 + 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.65895 + 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.79088 + 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: 0.969537 / Test error: 0.993004 / Layer sizes: 10 7 1 Training error: 0.961517 / Test error: 0.992909 / Layer sizes: 10 3 3 1 Training error: 0.974436 / Test error: 0.960899 / Layer sizes: 10 1 Training error: 0.963018 / Test error: 0.954593 / Layer sizes: 10 1 Training error: 0.952697 / Test error: 0.949233 / Layer sizes: 10 1 Training error: 0.922309 / Test error: 0.903643 / Layer sizes: 10 1 Training error: 0.916383 / Test error: 0.891547 / Layer sizes: 10 1 Training error: 0.885527 / Test error: 0.883092 / Layer sizes: 10 1 Training error: 0.874015 / Test error: 0.870392 / Layer sizes: 10 1 Training error: 0.870596 / Test error: 0.854381 / Layer sizes: 10 1 Training error: 0.858188 / Test error: 0.848810 / Layer sizes: 10 1 Training error: 0.834299 / Test error: 0.812470 / Layer sizes: 10 1 Training error: 0.830418 / Test error: 0.790011 / Layer sizes: 10 1 Training error: 0.818846 / Test error: 0.777194 / Layer sizes: 10 1 Training error: 0.805222 / Test error: 0.748311 / Layer sizes: 10 1 Training error: 0.803482 / Test error: 0.738183 / Layer sizes: 10 1 Training error: 0.773696 / Test error: 0.707871 / Layer sizes: 10 1 Training error: 0.767892 / Test error: 0.696219 / Layer sizes: 10 1 Training error: 0.750423 / Test error: 0.656241 / Layer sizes: 10 1 Training error: 0.745552 / Test error: 0.654911 / Layer sizes: 10 1 Training error: 0.730197 / Test error: 0.645317 / Layer sizes: 10 1 Training error: 0.722501 / Test error: 0.644750 / Layer sizes: 10 1 Training error: 0.702951 / Test error: 0.617077 / Layer sizes: 10 1 Training error: 0.698643 / Test error: 0.605222 / Layer sizes: 10 1 Training error: 0.696520 / Test error: 0.602268 / Layer sizes: 10 1 Training error: 0.690959 / Test error: 0.583075 / Layer sizes: 10 1 Training error: 0.681272 / Test error: 0.573833 / Layer sizes: 10 1 Training error: 0.676896 / Test error: 0.570577 / Layer sizes: 10 1 Training error: 0.676422 / Test error: 0.568333 / Layer sizes: 10 1 Training error: 0.669572 / Test error: 0.566287 / Layer sizes: 10 1 Training error: 0.661257 / Test error: 0.554766 / Layer sizes: 10 1 Training error: 0.651950 / Test error: 0.553317 / Layer sizes: 10 1 Training error: 0.639976 / Test error: 0.537486 / Layer sizes: 10 1 Training error: 0.634195 / Test error: 0.528600 / Layer sizes: 10 1 Training error: 0.623218 / Test error: 0.506973 / Layer sizes: 10 1 Training error: 0.622518 / Test error: 0.505876 / Layer sizes: 10 1 Training error: 0.613269 / Test error: 0.498610 / Layer sizes: 10 1 Training error: 0.602213 / Test error: 0.496124 / Layer sizes: 10 1 Training error: 0.600824 / Test error: 0.475499 / Layer sizes: 10 1 Training error: 0.592762 / Test error: 0.462201 / Layer sizes: 10 1 Training error: 0.589324 / Test error: 0.453331 / Layer sizes: 10 1 Training error: 0.579145 / Test error: 0.444801 / Layer sizes: 10 1 Training error: 0.558902 / Test error: 0.438071 / Layer sizes: 10 1 Training error: 0.544695 / Test error: 0.428480 / Layer sizes: 10 1 Training error: 0.542216 / Test error: 0.423089 / Layer sizes: 10 1 Training error: 0.539131 / Test error: 0.415638 / Layer sizes: 10 1 Training error: 0.537425 / Test error: 0.402127 / Layer sizes: 10 1 Training error: 0.535663 / Test error: 0.396727 / Layer sizes: 10 1 Training error: 0.524629 / Test error: 0.390457 / Layer sizes: 10 1 Training error: 0.524268 / Test error: 0.385320 / Layer sizes: 10 1 Training error: 0.517210 / Test error: 0.379346 / Layer sizes: 10 1 Training error: 0.503828 / Test error: 0.378057 / Layer sizes: 10 1 Training error: 0.503240 / Test error: 0.373938 / Layer sizes: 10 1 Training error: 0.478909 / Test error: 0.368526 / Layer sizes: 10 3 1 Training error: 0.496950 / Test error: 0.364603 / Layer sizes: 10 1 Training error: 0.471623 / Test error: 0.361250 / Layer sizes: 10 3 1 Training error: 0.488083 / Test error: 0.350195 / Layer sizes: 10 1 Training error: 0.470086 / Test error: 0.349716 / Layer sizes: 10 3 1 Training error: 0.485045 / Test error: 0.336995 / Layer sizes: 10 1 Training error: 0.483544 / Test error: 0.327292 / Layer sizes: 10 1 Training error: 0.482212 / Test error: 0.318322 / Layer sizes: 10 1 Training error: 0.480339 / Test error: 0.311481 / Layer sizes: 10 1 Training error: 0.478568 / Test error: 0.311087 / Layer sizes: 10 1 Training error: 0.387312 / Test error: 0.297361 / Layer sizes: 10 3 3 1 Training error: 0.384831 / Test error: 0.287908 / Layer sizes: 10 3 3 1 Training error: 0.375506 / Test error: 0.279346 / Layer sizes: 10 3 3 1 Training error: 0.322831 / Test error: 0.277311 / Layer sizes: 10 10 10 1 Training error: 0.318228 / Test error: 0.275941 / Layer sizes: 10 10 10 1 Training error: 0.330806 / Test error: 0.262983 / Layer sizes: 10 3 3 1 Training error: 0.328858 / Test error: 0.261267 / Layer sizes: 10 3 3 1 Training error: 0.327126 / Test error: 0.257931 / Layer sizes: 10 3 3 1 Training error: 0.325532 / Test error: 0.255629 / Layer sizes: 10 3 3 1 Training error: 0.324957 / Test error: 0.252882 / Layer sizes: 10 3 3 1 Training error: 0.322323 / Test error: 0.252542 / Layer sizes: 10 3 3 1 Training error: 0.261949 / Test error: 0.244121 / Layer sizes: 10 10 10 1 Training error: 0.282203 / Test error: 0.238191 / Layer sizes: 10 3 3 1 Training error: 0.279104 / Test error: 0.233674 / Layer sizes: 10 3 3 1 Training error: 0.278871 / Test error: 0.231524 / Layer sizes: 10 3 3 1 Training error: 0.277395 / Test error: 0.229496 / Layer sizes: 10 3 3 1 Training error: 0.276756 / Test error: 0.219250 / Layer sizes: 10 3 3 1 Training error: 0.271793 / Test error: 0.212811 / Layer sizes: 10 3 3 1 Training error: 0.211696 / Test error: 0.209004 / Layer sizes: 10 10 10 1 Training error: 0.208940 / Test error: 0.200571 / Layer sizes: 10 10 10 1 Training error: 0.265100 / Test error: 0.199710 / Layer sizes: 10 3 3 1 Training error: 0.264123 / Test error: 0.197324 / Layer sizes: 10 3 3 1 Training error: 0.161040 / Test error: 0.194564 / Layer sizes: 10 10 10 1 Training error: 0.152101 / Test error: 0.188534 / Layer sizes: 10 10 10 1 Training error: 0.149219 / Test error: 0.178203 / Layer sizes: 10 10 10 1 Training error: 0.147397 / Test error: 0.177005 / Layer sizes: 10 10 10 1 Training error: 0.145141 / Test error: 0.167136 / Layer sizes: 10 10 10 1 Training error: 0.141382 / Test error: 0.162808 / Layer sizes: 10 10 10 1 Training error: 0.128563 / Test error: 0.150603 / Layer sizes: 10 10 10 1 Training error: 0.098263 / Test error: 0.148686 / Layer sizes: 10 10 10 1 Training error: 0.098049 / Test error: 0.147996 / Layer sizes: 10 10 10 1 Training error: 0.095984 / Test error: 0.137000 / Layer sizes: 10 10 10 1 Training error: 0.095533 / Test error: 0.135221 / Layer sizes: 10 10 10 1 Training error: 0.078786 / Test error: 0.131386 / Layer sizes: 10 10 10 1 Training error: 0.075237 / Test error: 0.128138 / Layer sizes: 10 10 10 1 Training error: 0.075174 / Test error: 0.119610 / Layer sizes: 10 10 10 1 Training error: 0.194539 / Test error: 0.113148 / Layer sizes: 10 3 3 1 Training error: 0.193691 / Test error: 0.101202 / Layer sizes: 10 3 3 1 Training error: 0.193363 / Test error: 0.098564 / Layer sizes: 10 3 3 1 Training error: 0.192994 / Test error: 0.087939 / Layer sizes: 10 3 3 1 Training error: 0.184320 / Test error: 0.086121 / Layer sizes: 10 3 3 1 Training error: 0.162478 / Test error: 0.084930 / Layer sizes: 10 3 3 1 Training error: 0.161648 / Test error: 0.082532 / Layer sizes: 10 3 3 1 Training error: 0.041625 / Test error: 0.078605 / Layer sizes: 10 10 10 1 Training error: 0.041267 / Test error: 0.071684 / Layer sizes: 10 10 10 1 Training error: 0.037505 / Test error: 0.069392 / Layer sizes: 10 10 10 1 Training error: 0.033607 / Test error: 0.063740 / Layer sizes: 10 10 10 1 Training error: 0.032800 / Test error: 0.060647 / Layer sizes: 10 10 10 1 Training error: 0.029465 / Test error: 0.059516 / Layer sizes: 10 10 10 1 Training error: 0.029350 / Test error: 0.056783 / Layer sizes: 10 10 10 1 Training error: 0.023026 / Test error: 0.055489 / Layer sizes: 10 10 10 1 Training error: 0.021440 / Test error: 0.051114 / Layer sizes: 10 10 10 1 Training error: 0.021337 / Test error: 0.047866 / Layer sizes: 10 10 10 1 Training error: 0.018877 / Test error: 0.047219 / Layer sizes: 10 10 10 1 Training error: 0.015554 / Test error: 0.042784 / Layer sizes: 10 10 10 1 Training error: 0.015524 / Test error: 0.037045 / Layer sizes: 10 10 10 1 Training error: 0.015319 / Test error: 0.033940 / Layer sizes: 10 10 10 1 Training error: 0.014723 / Test error: 0.030594 / Layer sizes: 10 10 10 1 Training error: 0.013990 / Test error: 0.028559 / Layer sizes: 10 10 10 1 Training error: 0.008161 / Test error: 0.024761 / Layer sizes: 10 10 10 1 Training error: 0.008053 / Test error: 0.017512 / Layer sizes: 10 10 10 1 Training error: 0.007729 / Test error: 0.016497 / Layer sizes: 10 10 10 1 Training error: 0.007587 / Test error: 0.013004 / Layer sizes: 10 10 10 1 Training error: 0.006750 / Test error: 0.011162 / Layer sizes: 10 10 10 1 Training error: 0.006504 / Test error: 0.009888 / Layer sizes: 10 10 10 1 Training error: 0.006387 / Test error: 0.008681 / Layer sizes: 10 10 10 1 Training error: 0.006319 / Test error: 0.008128 / Layer sizes: 10 10 10 1 Training error: 0.001669 / Test error: 0.004750 / Layer sizes: 10 10 10 1 Training error: 0.001631 / Test error: 0.002871 / Layer sizes: 10 10 10 1 Training error: 0.001266 / Test error: 0.002851 / Layer sizes: 10 10 10 1 Training error: 0.001174 / Test error: 0.001951 / Layer sizes: 10 10 10 1 Training error: 0.000876 / Test error: 0.001541 / Layer sizes: 10 10 10 1 Training error: 0.000873 / Test error: 0.001457 / Layer sizes: 10 10 10 1 Training error: 0.000867 / Test error: 0.001400 / Layer sizes: 10 10 10 1 Training error: 0.000808 / Test error: 0.001289 / Layer sizes: 10 10 10 1 Training error: 0.000521 / Test error: 0.001137 / Layer sizes: 10 10 10 1 Training error: 0.000518 / Test error: 0.000845 / Layer sizes: 10 10 10 1 Training error: 0.000518 / Test error: 0.000795 / Layer sizes: 10 10 10 1 Training error: 0.000423 / Test error: 0.000543 / Layer sizes: 10 10 10 1 Training error: 0.000324 / Test error: 0.000425 / Layer sizes: 10 10 10 1 Training error: 0.000318 / Test error: 0.000412 / Layer sizes: 10 10 10 1 Training error: 0.000313 / Test error: 0.000382 / Layer sizes: 10 10 10 1 Training error: 0.000307 / Test error: 0.000359 / Layer sizes: 10 10 10 1 Training error: 0.000304 / Test error: 0.000356 / Layer sizes: 10 10 10 1 Training error: 0.000269 / Test error: 0.000320 / Layer sizes: 10 10 10 1 Training error: 0.000259 / Test error: 0.000310 / Layer sizes: 10 10 10 1 Training error: 0.000255 / Test error: 0.000302 / Layer sizes: 10 10 10 1 Training error: 0.000254 / Test error: 0.000302 / Layer sizes: 10 10 10 1 Training error: 0.000252 / Test error: 0.000300 / Layer sizes: 10 10 10 1 Training error: 0.000243 / Test error: 0.000291 / Layer sizes: 10 10 10 1 Training error: 0.000241 / Test error: 0.000284 / Layer sizes: 10 10 10 1 Training error: 0.000239 / Test error: 0.000280 / Layer sizes: 10 10 10 1 Training error: 0.000169 / Test error: 0.000261 / Layer sizes: 10 10 10 1 Training error: 0.000168 / Test error: 0.000258 / Layer sizes: 10 10 10 1 Training error: 0.000167 / Test error: 0.000258 / Layer sizes: 10 10 10 1 Training error: 0.000164 / Test error: 0.000208 / Layer sizes: 10 10 10 1 Training error: 0.000160 / Test error: 0.000199 / Layer sizes: 10 10 10 1 Training error: 0.000155 / Test error: 0.000181 / Layer sizes: 10 10 10 1 Training error: 0.000143 / Test error: 0.000176 / Layer sizes: 10 10 10 1 Training error: 0.000124 / Test error: 0.000156 / Layer sizes: 10 10 10 1 Training error: 0.000084 / Test error: 0.000104 / Layer sizes: 10 10 10 1 Training error: 0.000082 / Test error: 0.000097 / Layer sizes: 10 10 10 1 Training error: 0.000081 / Test error: 0.000091 / Layer sizes: 10 10 10 1 Training error: 0.000063 / Test error: 0.000081 / Layer sizes: 10 10 10 1 Training error: 0.000061 / Test error: 0.000081 / Layer sizes: 10 10 10 1 Training error: 0.000060 / Test error: 0.000071 / Layer sizes: 10 10 10 1 Training error: 0.000056 / Test error: 0.000068 / Layer sizes: 10 10 10 1 Training error: 0.000002 / Test error: 0.000004 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / Layer sizes: 10 10 10 1 Training error: 0.000000 / Test error: 0.000000 / 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. 90.36 % correct. 9.64 % wrong. Limit: 17.58 %. 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.73150 + 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.Qr0Urf 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.RGTQse find-requires: running scripts (cpp,debuginfo,files,lib,pam,perl,pkgconfig,pkgconfiglib,python,rpmlib,shebang,shell,static,symlinks,systemd-services) Requires: /lib/ld-linux.so.2, libc.so.6(GLIBC_2.0), libc.so.6(GLIBC_2.1), libc.so.6(GLIBC_2.3.4), libc.so.6(GLIBC_2.4), libm.so.6(GLIBC_2.0), libm.so.6(GLIBC_2.1), libm.so.6(GLIBC_2.29), rtld(GNU_HASH) Finding debuginfo files (using /usr/lib/rpm/find-debuginfo-files) Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.CgiWig 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.8KmF1e find-provides: running scripts (debuginfo) Finding Requires (using /usr/lib/rpm/find-requires) Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.gWNXJh 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 49.03user 0.47system 2:01.58elapsed 40%CPU (0avgtext+0avgdata 36000maxresident)k 0inputs+0outputs (0major+161771minor)pagefaults 0swaps 55.33user 4.29system 2:23.27elapsed 41%CPU (0avgtext+0avgdata 108852maxresident)k 0inputs+0outputs (0major+500070minor)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 2020-03-16 13:58:53.288719750 +0000 @@ -11,2 +11,3 @@ Requires: libm.so.6(GLIBC_2.1) +Requires: libm.so.6(GLIBC_2.29) Requires: rtld(GNU_HASH)