<86>Nov 19 12:57:38 userdel[3356131]: delete user 'rooter' <86>Nov 19 12:57:38 userdel[3356131]: removed group 'rooter' owned by 'rooter' <86>Nov 19 12:57:38 userdel[3356131]: removed shadow group 'rooter' owned by 'rooter' <86>Nov 19 12:57:38 groupadd[3356340]: group added to /etc/group: name=rooter, GID=693 <86>Nov 19 12:57:38 groupadd[3356340]: group added to /etc/gshadow: name=rooter <86>Nov 19 12:57:38 groupadd[3356340]: new group: name=rooter, GID=693 <86>Nov 19 12:57:38 useradd[3356520]: new user: name=rooter, UID=693, GID=693, home=/root, shell=/bin/bash <86>Nov 19 12:57:38 userdel[3356973]: delete user 'builder' <86>Nov 19 12:57:38 userdel[3356973]: removed group 'builder' owned by 'builder' <86>Nov 19 12:57:38 userdel[3356973]: removed shadow group 'builder' owned by 'builder' <86>Nov 19 12:57:38 groupadd[3357005]: group added to /etc/group: name=builder, GID=694 <86>Nov 19 12:57:38 groupadd[3357005]: group added to /etc/gshadow: name=builder <86>Nov 19 12:57:38 groupadd[3357005]: new group: name=builder, GID=694 <86>Nov 19 12:57:38 useradd[3357016]: new user: name=builder, UID=694, GID=694, home=/usr/src, shell=/bin/bash <13>Nov 19 12:57:41 rpmi: libruby-2.7.1-alt2.1 sisyphus+255293.40.2.1 1595537052 installed <13>Nov 19 12:57:41 rpmi: libgdbm-1.8.3-alt10 1454943334 installed <13>Nov 19 12:57:41 rpmi: libyaml2-0.2.5-alt1 sisyphus+253672.100.1.1 1592583137 installed <13>Nov 19 12:57:41 rpmi: erb-0:2.7.1-alt2.1 sisyphus+255293.40.2.1 1595536976 installed <13>Nov 19 12:57:41 rpmi: irb-2.7.1-alt2.1 sisyphus+255293.40.2.1 1595536976 installed <13>Nov 19 12:57:41 rpmi: gem-minitest-5.14.1-alt0.1 sisyphus+249637.100.1.1 1586421683 installed <13>Nov 19 12:57:41 rpmi: ruby-net-telnet-0.2.0-alt1 sisyphus+219345.2700.8.1 1547631566 installed <13>Nov 19 12:57:41 rpmi: gem-power-assert-1.1.7-alt1 sisyphus+248971.220.47.1 1586259894 installed <13>Nov 19 12:57:41 rpmi: rake-13.0.1-alt1 sisyphus+248971.320.47.1 1586259947 installed <13>Nov 19 12:57:41 rpmi: gem-rake-13.0.1-alt1 sisyphus+248971.320.47.1 1586259947 installed <13>Nov 19 12:57:41 rpmi: gem-test-unit-3.3.5-alt1 sisyphus+248971.620.47.1 1586260035 installed <13>Nov 19 12:57:41 rpmi: ruby-xmlrpc-0.3.0-alt1 sisyphus+219345.3300.8.1 1547631818 installed <13>Nov 19 12:57:41 rpmi: ri-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed <13>Nov 19 12:57:41 rpmi: rdoc-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed <13>Nov 19 12:57:41 rpmi: ruby-rdoc-6.1.1-alt3 sisyphus+220149.7500.44.1 1552167568 installed <13>Nov 19 12:57:41 rpmi: gem-1:3.1.2-alt2.1 sisyphus+255293.40.2.1 1595536976 installed <13>Nov 19 12:57:41 rpmi: bundle-2.1.4-alt1 sisyphus+247301.1100.3.2 1583840910 installed <13>Nov 19 12:57:42 rpmi: gem-bundler-2.1.4-alt1 sisyphus+247301.1100.3.2 1583840910 installed <13>Nov 19 12:57:42 rpmi: ruby-2.7.1-alt2.1 sisyphus+255293.40.2.1 1595537052 installed <13>Nov 19 12:57:43 rpmi: ruby-stdlibs-2.7.1-alt2.1 sisyphus+255293.40.2.1 1595537052 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.39883 + 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.95703 + 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.95703 + 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.72330 + 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: 0.996038 / Test error: 0.994919 / Layer sizes: 10 7 1 Training error: 0.991085 / Test error: 0.988267 / Layer sizes: 10 9 4 1 Training error: 0.985100 / Test error: 0.980274 / Layer sizes: 10 9 4 1 Training error: 0.983485 / Test error: 0.980004 / Layer sizes: 10 7 1 Training error: 0.975897 / Test error: 0.967405 / Layer sizes: 10 9 4 1 Training error: 0.970617 / Test error: 0.959586 / Layer sizes: 10 9 4 1 Training error: 0.968948 / Test error: 0.957185 / Layer sizes: 10 9 4 1 Training error: 0.961304 / Test error: 0.945386 / Layer sizes: 10 9 4 1 Training error: 0.959945 / Test error: 0.945198 / Layer sizes: 10 7 1 Training error: 0.958129 / Test error: 0.939992 / Layer sizes: 10 9 4 1 Training error: 0.951979 / Test error: 0.929334 / Layer sizes: 10 7 1 Training error: 0.945908 / Test error: 0.921054 / Layer sizes: 10 7 1 Training error: 0.836611 / Test error: 0.903566 / Layer sizes: 10 1 Training error: 0.796916 / Test error: 0.851136 / Layer sizes: 10 1 Training error: 0.787698 / Test error: 0.801566 / Layer sizes: 10 1 Training error: 0.751353 / Test error: 0.779387 / Layer sizes: 10 1 Training error: 0.738614 / Test error: 0.765536 / Layer sizes: 10 1 Training error: 0.737095 / Test error: 0.762488 / Layer sizes: 10 1 Training error: 0.707973 / Test error: 0.748992 / Layer sizes: 10 1 Training error: 0.695043 / Test error: 0.722379 / Layer sizes: 10 1 Training error: 0.694952 / Test error: 0.717782 / Layer sizes: 10 1 Training error: 0.679725 / Test error: 0.678362 / Layer sizes: 10 1 Training error: 0.669368 / Test error: 0.673722 / Layer sizes: 10 1 Training error: 0.656458 / Test error: 0.669152 / Layer sizes: 10 1 Training error: 0.641882 / Test error: 0.658296 / Layer sizes: 10 1 Training error: 0.638348 / Test error: 0.639147 / Layer sizes: 10 1 Training error: 0.632492 / Test error: 0.635364 / Layer sizes: 10 1 Training error: 0.612128 / Test error: 0.619849 / Layer sizes: 10 1 Training error: 0.584732 / Test error: 0.608618 / Layer sizes: 10 1 Training error: 0.577478 / Test error: 0.594990 / Layer sizes: 10 1 Training error: 0.561552 / Test error: 0.573952 / Layer sizes: 10 1 Training error: 0.542844 / Test error: 0.544587 / Layer sizes: 10 1 Training error: 0.538980 / Test error: 0.541410 / Layer sizes: 10 1 Training error: 0.509316 / Test error: 0.528361 / Layer sizes: 10 1 Training error: 0.560616 / Test error: 0.523691 / Layer sizes: 10 10 1 Training error: 0.501530 / Test error: 0.523086 / Layer sizes: 10 1 Training error: 0.492146 / Test error: 0.511400 / Layer sizes: 10 1 Training error: 0.485711 / Test error: 0.493363 / Layer sizes: 10 1 Training error: 0.483021 / Test error: 0.487589 / Layer sizes: 10 1 Training error: 0.482608 / Test error: 0.482587 / Layer sizes: 10 1 Training error: 0.479201 / Test error: 0.477455 / Layer sizes: 10 1 Training error: 0.477754 / Test error: 0.472010 / Layer sizes: 10 1 Training error: 0.475968 / Test error: 0.466618 / Layer sizes: 10 1 Training error: 0.473994 / Test error: 0.456417 / Layer sizes: 10 1 Training error: 0.460868 / Test error: 0.434165 / Layer sizes: 10 1 Training error: 0.449544 / Test error: 0.433947 / Layer sizes: 10 1 Training error: 0.440783 / Test error: 0.430609 / Layer sizes: 10 1 Training error: 0.463564 / Test error: 0.425883 / Layer sizes: 10 10 1 Training error: 0.460224 / Test error: 0.422672 / Layer sizes: 10 10 1 Training error: 0.423310 / Test error: 0.419041 / Layer sizes: 10 1 Training error: 0.422338 / Test error: 0.406922 / Layer sizes: 10 1 Training error: 0.455484 / Test error: 0.398052 / Layer sizes: 10 10 1 Training error: 0.415322 / Test error: 0.395356 / Layer sizes: 10 1 Training error: 0.409586 / Test error: 0.394300 / Layer sizes: 10 1 Training error: 0.408680 / Test error: 0.387693 / Layer sizes: 10 1 Training error: 0.400889 / Test error: 0.383828 / Layer sizes: 10 1 Training error: 0.399993 / Test error: 0.383462 / Layer sizes: 10 1 Training error: 0.392538 / Test error: 0.380005 / Layer sizes: 10 1 Training error: 0.391589 / Test error: 0.365737 / Layer sizes: 10 1 Training error: 0.389391 / Test error: 0.364126 / Layer sizes: 10 1 Training error: 0.387417 / Test error: 0.358877 / Layer sizes: 10 1 Training error: 0.382173 / Test error: 0.339305 / Layer sizes: 10 1 Training error: 0.382161 / Test error: 0.337967 / Layer sizes: 10 1 Training error: 0.376188 / Test error: 0.335131 / Layer sizes: 10 1 Training error: 0.372877 / Test error: 0.327691 / Layer sizes: 10 1 Training error: 0.371286 / Test error: 0.320013 / Layer sizes: 10 1 Training error: 0.370162 / Test error: 0.311926 / Layer sizes: 10 1 Training error: 0.366730 / Test error: 0.309317 / Layer sizes: 10 1 Training error: 0.364705 / Test error: 0.305150 / Layer sizes: 10 1 Training error: 0.361913 / Test error: 0.303175 / Layer sizes: 10 1 Training error: 0.361141 / Test error: 0.301587 / Layer sizes: 10 1 Training error: 0.348523 / Test error: 0.295681 / Layer sizes: 10 1 Training error: 0.348153 / Test error: 0.295474 / Layer sizes: 10 1 Training error: 0.347840 / Test error: 0.294980 / Layer sizes: 10 1 Training error: 0.347109 / Test error: 0.293273 / Layer sizes: 10 1 Training error: 0.346225 / Test error: 0.284077 / Layer sizes: 10 1 Training error: 0.325833 / Test error: 0.280767 / Layer sizes: 10 1 Training error: 0.228093 / Test error: 0.271541 / Layer sizes: 10 10 1 Training error: 0.290190 / Test error: 0.270884 / Layer sizes: 10 3 3 1 Training error: 0.286973 / Test error: 0.268498 / Layer sizes: 10 3 3 1 Training error: 0.213246 / Test error: 0.262479 / Layer sizes: 10 10 10 1 Training error: 0.212465 / Test error: 0.259650 / Layer sizes: 10 10 10 1 Training error: 0.276411 / Test error: 0.247779 / Layer sizes: 10 3 3 1 Training error: 0.091271 / Test error: 0.243481 / Layer sizes: 10 10 10 1 Training error: 0.090612 / Test error: 0.238323 / Layer sizes: 10 10 10 1 Training error: 0.087845 / Test error: 0.237848 / Layer sizes: 10 10 10 1 Training error: 0.086681 / Test error: 0.227750 / Layer sizes: 10 10 10 1 Training error: 0.082851 / Test error: 0.222600 / Layer sizes: 10 10 10 1 Training error: 0.079751 / Test error: 0.215914 / Layer sizes: 10 10 10 1 Training error: 0.058369 / Test error: 0.209908 / Layer sizes: 10 10 1 Training error: 0.058302 / Test error: 0.208821 / Layer sizes: 10 10 1 Training error: 0.057662 / Test error: 0.198725 / Layer sizes: 10 10 1 Training error: 0.057254 / Test error: 0.197901 / Layer sizes: 10 10 1 Training error: 0.057228 / Test error: 0.195551 / Layer sizes: 10 10 1 Training error: 0.056375 / Test error: 0.185798 / Layer sizes: 10 10 1 Training error: 0.055753 / Test error: 0.180412 / Layer sizes: 10 10 1 Training error: 0.055546 / Test error: 0.172194 / Layer sizes: 10 10 1 Training error: 0.052224 / Test error: 0.170317 / Layer sizes: 10 10 1 Training error: 0.051223 / Test error: 0.166097 / Layer sizes: 10 10 1 Training error: 0.049175 / Test error: 0.153932 / Layer sizes: 10 10 1 Training error: 0.047603 / Test error: 0.145439 / Layer sizes: 10 10 1 Training error: 0.046374 / Test error: 0.137600 / Layer sizes: 10 10 1 Training error: 0.046290 / Test error: 0.134477 / Layer sizes: 10 10 1 Training error: 0.046267 / Test error: 0.131115 / Layer sizes: 10 10 1 Training error: 0.036315 / Test error: 0.129838 / Layer sizes: 10 10 1 Training error: 0.034126 / Test error: 0.126781 / Layer sizes: 10 10 1 Training error: 0.033158 / Test error: 0.119615 / Layer sizes: 10 10 1 Training error: 0.032872 / Test error: 0.117094 / Layer sizes: 10 10 1 Training error: 0.031795 / Test error: 0.116793 / Layer sizes: 10 10 1 Training error: 0.027213 / Test error: 0.116141 / Layer sizes: 10 10 1 Training error: 0.027076 / Test error: 0.110150 / Layer sizes: 10 10 1 Training error: 0.026839 / Test error: 0.105412 / Layer sizes: 10 10 1 Training error: 0.025652 / Test error: 0.098782 / Layer sizes: 10 10 1 Training error: 0.025651 / Test error: 0.097513 / Layer sizes: 10 10 1 Training error: 0.024097 / Test error: 0.096219 / Layer sizes: 10 10 1 Training error: 0.024002 / Test error: 0.093649 / Layer sizes: 10 10 1 Training error: 0.023604 / Test error: 0.092225 / Layer sizes: 10 10 1 Training error: 0.022802 / Test error: 0.091778 / Layer sizes: 10 10 1 Training error: 0.022499 / Test error: 0.089396 / Layer sizes: 10 10 1 Training error: 0.021302 / Test error: 0.083744 / Layer sizes: 10 10 1 Training error: 0.021212 / Test error: 0.083650 / Layer sizes: 10 10 1 Training error: 0.020426 / Test error: 0.082553 / Layer sizes: 10 10 1 Training error: 0.020250 / Test error: 0.082468 / Layer sizes: 10 10 1 Training error: 0.019983 / Test error: 0.078981 / Layer sizes: 10 10 1 Training error: 0.019845 / Test error: 0.078773 / Layer sizes: 10 10 1 Training error: 0.018288 / Test error: 0.076412 / Layer sizes: 10 10 1 Training error: 0.018205 / Test error: 0.075856 / Layer sizes: 10 10 1 Training error: 0.010539 / Test error: 0.072574 / Layer sizes: 10 10 1 Training error: 0.010483 / Test error: 0.056447 / Layer sizes: 10 10 1 Training error: 0.004120 / Test error: 0.052675 / Layer sizes: 10 10 1 Training error: 0.000000 / Test error: 0.041667 / Layer sizes: 10 10 10 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. 92.04 % correct. 7.96 % wrong. Limit: 17.36 %. 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.61818 + 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.Od7Smy 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.6IjK4A 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.QHbzaz 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.uJgWdA find-provides: running scripts (debuginfo) Finding Requires (using /usr/lib/rpm/find-requires) Executing: /bin/sh -e /usr/src/tmp/rpm-tmp.qxQIoy 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 90.90user 0.47system 1:38.28elapsed 92%CPU (0avgtext+0avgdata 35772maxresident)k 0inputs+0outputs (0major+163727minor)pagefaults 0swaps 96.14user 3.07system 1:49.65elapsed 90%CPU (0avgtext+0avgdata 108608maxresident)k 0inputs+0outputs (0major+454452minor)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 2020-11-19 12:59:23.844521847 +0000 @@ -11,2 +11,3 @@ Requires: libm.so.6(GLIBC_2.1) +Requires: libm.so.6(GLIBC_2.29) Requires: rtld(GNU_HASH)