0s autopkgtest [01:34:18]: starting date and time: 2025-03-16 01:34:18+0000
  0s autopkgtest [01:34:18]: git checkout: 325255d2 Merge branch 'pin-any-arch' into 'ubuntu/production'
  0s autopkgtest [01:34:18]: host juju-7f2275-prod-proposed-migration-environment-9; command line: /home/ubuntu/autopkgtest/runner/autopkgtest --output-dir /tmp/autopkgtest-work.oxfo7qip/out --timeout-copy=6000 --setup-commands 'ln -s /dev/null /etc/systemd/system/bluetooth.service; printf "http_proxy=http://squid.internal:3128\nhttps_proxy=http://squid.internal:3128\nno_proxy=127.0.0.1,127.0.1.1,login.ubuntu.com,localhost,localdomain,novalocal,internal,archive.ubuntu.com,ports.ubuntu.com,security.ubuntu.com,ddebs.ubuntu.com,changelogs.ubuntu.com,keyserver.ubuntu.com,launchpadlibrarian.net,launchpadcontent.net,launchpad.net,10.24.0.0/24,keystone.ps5.canonical.com,objectstorage.prodstack5.canonical.com,radosgw.ps5.canonical.com\n" >> /etc/environment' --apt-pocket=proposed=src:scikit-learn --apt-upgrade xgboost --timeout-short=300 --timeout-copy=20000 --timeout-build=20000 --env=ADT_TEST_TRIGGERS=scikit-learn/1.4.2+dfsg-8 -- lxd -r lxd-armhf-10.145.243.85 lxd-armhf-10.145.243.85:autopkgtest/ubuntu/plucky/armhf
 24s autopkgtest [01:34:42]: testbed dpkg architecture: armhf
 26s autopkgtest [01:34:44]: testbed apt version: 2.9.33
 30s autopkgtest [01:34:48]: @@@@@@@@@@@@@@@@@@@@ test bed setup
 32s autopkgtest [01:34:50]: testbed release detected to be: None
 40s autopkgtest [01:34:58]: updating testbed package index (apt update)
 42s Get:1 http://ftpmaster.internal/ubuntu plucky-proposed InRelease [126 kB]
 42s Get:2 http://ftpmaster.internal/ubuntu plucky InRelease [257 kB]
 43s Get:3 http://ftpmaster.internal/ubuntu plucky-updates InRelease [126 kB]
 43s Get:4 http://ftpmaster.internal/ubuntu plucky-security InRelease [126 kB]
 43s Get:5 http://ftpmaster.internal/ubuntu plucky-proposed/main Sources [41.4 kB]
 43s Get:6 http://ftpmaster.internal/ubuntu plucky-proposed/multiverse Sources [17.7 kB]
 43s Get:7 http://ftpmaster.internal/ubuntu plucky-proposed/universe Sources [365 kB]
 43s Get:8 http://ftpmaster.internal/ubuntu plucky-proposed/main armhf Packages [74.9 kB]
 44s Get:9 http://ftpmaster.internal/ubuntu plucky-proposed/main armhf c-n-f Metadata [1792 B]
 44s Get:10 http://ftpmaster.internal/ubuntu plucky-proposed/restricted armhf c-n-f Metadata [116 B]
 44s Get:11 http://ftpmaster.internal/ubuntu plucky-proposed/universe armhf Packages [290 kB]
 44s Get:12 http://ftpmaster.internal/ubuntu plucky-proposed/universe armhf c-n-f Metadata [10.5 kB]
 44s Get:13 http://ftpmaster.internal/ubuntu plucky-proposed/multiverse armhf Packages [4168 B]
 44s Get:14 http://ftpmaster.internal/ubuntu plucky-proposed/multiverse armhf c-n-f Metadata [240 B]
 44s Get:15 http://ftpmaster.internal/ubuntu plucky/multiverse Sources [299 kB]
 44s Get:16 http://ftpmaster.internal/ubuntu plucky/universe Sources [21.0 MB]
 60s Get:17 http://ftpmaster.internal/ubuntu plucky/main Sources [1389 kB]
 60s Get:18 http://ftpmaster.internal/ubuntu plucky/main armhf Packages [1378 kB]
 61s Get:19 http://ftpmaster.internal/ubuntu plucky/main armhf c-n-f Metadata [29.5 kB]
 61s Get:20 http://ftpmaster.internal/ubuntu plucky/restricted armhf c-n-f Metadata [108 B]
 61s Get:21 http://ftpmaster.internal/ubuntu plucky/universe armhf Packages [15.3 MB]
 67s Get:22 http://ftpmaster.internal/ubuntu plucky/multiverse armhf Packages [172 kB]
 69s Fetched 41.1 MB in 27s (1518 kB/s)
 71s Reading package lists...
 79s autopkgtest [01:35:36]: upgrading testbed (apt dist-upgrade and autopurge)
 80s Reading package lists...
 80s Building dependency tree...
 80s Reading state information...
 82s Calculating upgrade...Starting pkgProblemResolver with broken count: 0
 82s Starting 2 pkgProblemResolver with broken count: 0
 82s Done
 83s Entering ResolveByKeep
 84s 
 84s Calculating upgrade...
 85s The following packages will be upgraded:
 85s   pinentry-curses python3-jinja2 sos strace
 86s 4 upgraded, 0 newly installed, 0 to remove and 0 not upgraded.
 86s Need to get 960 kB of archives.
 86s After this operation, 23.6 kB of additional disk space will be used.
 86s Get:1 http://ftpmaster.internal/ubuntu plucky/main armhf strace armhf 6.13+ds-1ubuntu1 [445 kB]
 86s Get:2 http://ftpmaster.internal/ubuntu plucky/main armhf pinentry-curses armhf 1.3.1-2ubuntu3 [40.6 kB]
 86s Get:3 http://ftpmaster.internal/ubuntu plucky/main armhf python3-jinja2 all 3.1.5-2ubuntu1 [109 kB]
 86s Get:4 http://ftpmaster.internal/ubuntu plucky/main armhf sos all 4.9.0-5 [365 kB]
 87s Fetched 960 kB in 1s (829 kB/s)
 88s (Reading database ... 
(Reading database ... 5%
(Reading database ... 10%
(Reading database ... 15%
(Reading database ... 20%
(Reading database ... 25%
(Reading database ... 30%
(Reading database ... 35%
(Reading database ... 40%
(Reading database ... 45%
(Reading database ... 50%
(Reading database ... 55%
(Reading database ... 60%
(Reading database ... 65%
(Reading database ... 70%
(Reading database ... 75%
(Reading database ... 80%
(Reading database ... 85%
(Reading database ... 90%
(Reading database ... 95%
(Reading database ... 100%
(Reading database ... 64655 files and directories currently installed.)
 88s Preparing to unpack .../strace_6.13+ds-1ubuntu1_armhf.deb ...
 88s Unpacking strace (6.13+ds-1ubuntu1) over (6.11-0ubuntu1) ...
 88s Preparing to unpack .../pinentry-curses_1.3.1-2ubuntu3_armhf.deb ...
 88s Unpacking pinentry-curses (1.3.1-2ubuntu3) over (1.3.1-2ubuntu2) ...
 88s Preparing to unpack .../python3-jinja2_3.1.5-2ubuntu1_all.deb ...
 88s Unpacking python3-jinja2 (3.1.5-2ubuntu1) over (3.1.5-2) ...
 88s Preparing to unpack .../archives/sos_4.9.0-5_all.deb ...
 88s Unpacking sos (4.9.0-5) over (4.9.0-4) ...
 89s Setting up sos (4.9.0-5) ...
 89s Setting up pinentry-curses (1.3.1-2ubuntu3) ...
 89s Setting up python3-jinja2 (3.1.5-2ubuntu1) ...
 90s Setting up strace (6.13+ds-1ubuntu1) ...
 90s Processing triggers for man-db (2.13.0-1) ...
 93s Reading package lists...
 94s Building dependency tree...
 94s Reading state information...
 95s Starting pkgProblemResolver with broken count: 0
 95s Starting 2 pkgProblemResolver with broken count: 0
 95s Done
 96s Solving dependencies...
 97s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded.
 99s autopkgtest [01:35:57]: rebooting testbed after setup commands that affected boot
141s autopkgtest [01:36:39]: testbed running kernel: Linux 6.8.0-52-generic #53~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Wed Jan 15 18:10:51 UTC 2
167s autopkgtest [01:37:05]: @@@@@@@@@@@@@@@@@@@@ apt-source xgboost
186s Get:1 http://ftpmaster.internal/ubuntu plucky/universe xgboost 2.1.4-1build1 (dsc) [2340 B]
186s Get:2 http://ftpmaster.internal/ubuntu plucky/universe xgboost 2.1.4-1build1 (tar) [2138 kB]
186s Get:3 http://ftpmaster.internal/ubuntu plucky/universe xgboost 2.1.4-1build1 (diff) [23.2 kB]
186s gpgv: Signature made Wed Mar  5 01:20:21 2025 UTC
186s gpgv:                using RSA key 25E3FF2D7F469DBE7D0D4E50AFCFEC8E669CE1C2
186s gpgv: Can't check signature: No public key
186s dpkg-source: warning: cannot verify inline signature for ./xgboost_2.1.4-1build1.dsc: no acceptable signature found
186s autopkgtest [01:37:24]: testing package xgboost version 2.1.4-1build1
189s autopkgtest [01:37:27]: build not needed
191s autopkgtest [01:37:29]: test run-demos: preparing testbed
193s Reading package lists...
193s Building dependency tree...
193s Reading state information...
194s Starting pkgProblemResolver with broken count: 0
194s Starting 2 pkgProblemResolver with broken count: 0
194s Done
196s The following NEW packages will be installed:
196s   blt fontconfig-config fonts-dejavu-core fonts-dejavu-mono fonts-lyx libblas3
196s   libdeflate0 libdmlc0t64 libfontconfig1 libfreetype6 libgfortran5 libgomp1
196s   libgraphite2-3 libharfbuzz0b libimagequant0 libjbig0 libjpeg-turbo8 libjpeg8
196s   libjs-jquery libjs-jquery-ui liblapack3 liblbfgsb0 liblcms2-2 liblerc4
196s   libopenjp2-7 libqhull-r8.0 libraqm0 libsharpyuv0 libtcl8.6 libtiff6 libtk8.6
196s   libwebp7 libwebpdemux2 libwebpmux3 libxft2 libxgboost-dev libxgboost0
196s   libxrender1 libxslt1.1 libxss1 python-matplotlib-data python3-brotli
196s   python3-contourpy python3-cycler python3-decorator python3-fonttools
196s   python3-fs python3-joblib python3-kiwisolver python3-lxml python3-lz4
196s   python3-matplotlib python3-mpmath python3-numpy python3-numpy-dev
196s   python3-pandas python3-pandas-lib python3-pil python3-pil.imagetk
196s   python3-platformdirs python3-pytz python3-scipy python3-sklearn
196s   python3-sklearn-lib python3-sympy python3-threadpoolctl python3-tk
196s   python3-tz python3-ufolib2 python3-unicodedata2 python3-xgboost
196s   python3.12-tk python3.13-tk tk8.6-blt2.5 unicode-data x11-common
196s 0 upgraded, 76 newly installed, 0 to remove and 0 not upgraded.
196s Need to get 85.2 MB of archives.
196s After this operation, 334 MB of additional disk space will be used.
196s Get:1 http://ftpmaster.internal/ubuntu plucky/main armhf python3-numpy-dev armhf 1:2.2.3+ds-5 [141 kB]
196s Get:2 http://ftpmaster.internal/ubuntu plucky/main armhf libblas3 armhf 3.12.1-2 [132 kB]
196s Get:3 http://ftpmaster.internal/ubuntu plucky/main armhf libgfortran5 armhf 15-20250222-0ubuntu1 [330 kB]
197s Get:4 http://ftpmaster.internal/ubuntu plucky/main armhf liblapack3 armhf 3.12.1-2 [2091 kB]
197s Get:5 http://ftpmaster.internal/ubuntu plucky/main armhf python3-numpy armhf 1:2.2.3+ds-5 [3725 kB]
197s Get:6 http://ftpmaster.internal/ubuntu plucky/main armhf libtcl8.6 armhf 8.6.16+dfsg-1 [909 kB]
197s Get:7 http://ftpmaster.internal/ubuntu plucky/main armhf libfreetype6 armhf 2.13.3+dfsg-1 [330 kB]
197s Get:8 http://ftpmaster.internal/ubuntu plucky/main armhf fonts-dejavu-mono all 2.37-8 [502 kB]
197s Get:9 http://ftpmaster.internal/ubuntu plucky/main armhf fonts-dejavu-core all 2.37-8 [835 kB]
197s Get:10 http://ftpmaster.internal/ubuntu plucky/main armhf fontconfig-config armhf 2.15.0-2ubuntu1 [37.5 kB]
197s Get:11 http://ftpmaster.internal/ubuntu plucky/main armhf libfontconfig1 armhf 2.15.0-2ubuntu1 [114 kB]
197s Get:12 http://ftpmaster.internal/ubuntu plucky/main armhf libxrender1 armhf 1:0.9.10-1.1build1 [16.0 kB]
197s Get:13 http://ftpmaster.internal/ubuntu plucky/main armhf libxft2 armhf 2.3.6-1build1 [37.4 kB]
197s Get:14 http://ftpmaster.internal/ubuntu plucky/main armhf x11-common all 1:7.7+23ubuntu3 [21.7 kB]
197s Get:15 http://ftpmaster.internal/ubuntu plucky/main armhf libxss1 armhf 1:1.2.3-1build3 [6500 B]
197s Get:16 http://ftpmaster.internal/ubuntu plucky/main armhf libtk8.6 armhf 8.6.16-1 [686 kB]
197s Get:17 http://ftpmaster.internal/ubuntu plucky/main armhf tk8.6-blt2.5 armhf 2.5.3+dfsg-8 [527 kB]
197s Get:18 http://ftpmaster.internal/ubuntu plucky/main armhf blt armhf 2.5.3+dfsg-8 [4824 B]
197s Get:19 http://ftpmaster.internal/ubuntu plucky/universe armhf fonts-lyx all 2.4.3-1 [171 kB]
197s Get:20 http://ftpmaster.internal/ubuntu plucky/main armhf libdeflate0 armhf 1.23-1 [38.5 kB]
197s Get:21 http://ftpmaster.internal/ubuntu plucky/main armhf libgomp1 armhf 15-20250222-0ubuntu1 [128 kB]
197s Get:22 http://ftpmaster.internal/ubuntu plucky/universe armhf libdmlc0t64 armhf 0.5+git20240614.1334185-1 [205 kB]
197s Get:23 http://ftpmaster.internal/ubuntu plucky/main armhf libgraphite2-3 armhf 1.3.14-2ubuntu1 [64.8 kB]
197s Get:24 http://ftpmaster.internal/ubuntu plucky/main armhf libharfbuzz0b armhf 10.2.0-1 [464 kB]
197s Get:25 http://ftpmaster.internal/ubuntu plucky/main armhf libimagequant0 armhf 2.18.0-1build1 [31.1 kB]
197s Get:26 http://ftpmaster.internal/ubuntu plucky/main armhf libjpeg-turbo8 armhf 2.1.5-3ubuntu2 [127 kB]
197s Get:27 http://ftpmaster.internal/ubuntu plucky/main armhf libjpeg8 armhf 8c-2ubuntu11 [2148 B]
197s Get:28 http://ftpmaster.internal/ubuntu plucky/main armhf libjs-jquery all 3.6.1+dfsg+~3.5.14-1 [328 kB]
197s Get:29 http://ftpmaster.internal/ubuntu plucky/universe armhf libjs-jquery-ui all 1.13.2+dfsg-1 [252 kB]
197s Get:30 http://ftpmaster.internal/ubuntu plucky/universe armhf liblbfgsb0 armhf 3.0+dfsg.4-1build1 [27.4 kB]
197s Get:31 http://ftpmaster.internal/ubuntu plucky/main armhf liblcms2-2 armhf 2.16-2 [137 kB]
197s Get:32 http://ftpmaster.internal/ubuntu plucky/main armhf liblerc4 armhf 4.0.0+ds-5ubuntu1 [160 kB]
197s Get:33 http://ftpmaster.internal/ubuntu plucky/universe armhf libqhull-r8.0 armhf 2020.2-6build1 [173 kB]
197s Get:34 http://ftpmaster.internal/ubuntu plucky/main armhf libraqm0 armhf 0.10.2-1 [12.4 kB]
197s Get:35 http://ftpmaster.internal/ubuntu plucky/main armhf libsharpyuv0 armhf 1.5.0-0.1 [16.4 kB]
197s Get:36 http://ftpmaster.internal/ubuntu plucky/main armhf libjbig0 armhf 2.1-6.1ubuntu2 [24.9 kB]
198s Get:37 http://ftpmaster.internal/ubuntu plucky/main armhf libwebp7 armhf 1.5.0-0.1 [188 kB]
198s Get:38 http://ftpmaster.internal/ubuntu plucky/main armhf libtiff6 armhf 4.5.1+git230720-4ubuntu4 [179 kB]
198s Get:39 http://ftpmaster.internal/ubuntu plucky/main armhf libwebpdemux2 armhf 1.5.0-0.1 [11.5 kB]
198s Get:40 http://ftpmaster.internal/ubuntu plucky/main armhf libwebpmux3 armhf 1.5.0-0.1 [22.4 kB]
198s Get:41 http://ftpmaster.internal/ubuntu plucky/universe armhf libxgboost0 armhf 2.1.4-1build1 [1831 kB]
198s Get:42 http://ftpmaster.internal/ubuntu plucky/universe armhf libxgboost-dev armhf 2.1.4-1build1 [74.3 kB]
198s Get:43 http://ftpmaster.internal/ubuntu plucky/main armhf libxslt1.1 armhf 1.1.39-0exp1ubuntu2 [152 kB]
198s Get:44 http://ftpmaster.internal/ubuntu plucky/universe armhf python-matplotlib-data all 3.8.3-7build1 [2934 kB]
198s Get:45 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-brotli armhf 1.1.0-2build4 [322 kB]
198s Get:46 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-contourpy armhf 1.3.1-1build1 [195 kB]
198s Get:47 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-cycler all 0.12.1-1 [9716 B]
198s Get:48 http://ftpmaster.internal/ubuntu plucky/main armhf python3-decorator all 5.1.1-5 [10.1 kB]
198s Get:49 http://ftpmaster.internal/ubuntu plucky/main armhf python3-platformdirs all 4.3.6-1 [16.8 kB]
198s Get:50 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-fs all 2.4.16-7 [90.8 kB]
198s Get:51 http://ftpmaster.internal/ubuntu plucky/main armhf python3-lxml armhf 5.3.1-1build1 [1282 kB]
198s Get:52 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-lz4 armhf 4.4.0+dfsg-1build1 [25.3 kB]
198s Get:53 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-scipy armhf 1.14.1-4ubuntu2 [16.7 MB]
198s Get:54 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-mpmath all 1.3.0-1 [425 kB]
198s Get:55 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-sympy all 1.13.3-5 [4229 kB]
198s Get:56 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-ufolib2 all 0.17.0+dfsg1-1 [33.5 kB]
198s Get:57 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-unicodedata2 armhf 15.1.0+ds-1build3 [357 kB]
198s Get:58 http://ftpmaster.internal/ubuntu plucky/universe armhf unicode-data all 15.1.0-1 [8878 kB]
199s Get:59 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-fonttools armhf 4.55.3-2build1 [1462 kB]
199s Get:60 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-joblib all 1.4.2-3 [205 kB]
199s Get:61 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-kiwisolver armhf 1.4.7-3build1 [57.7 kB]
199s Get:62 http://ftpmaster.internal/ubuntu plucky/main armhf libopenjp2-7 armhf 2.5.3-2 [172 kB]
199s Get:63 http://ftpmaster.internal/ubuntu plucky/main armhf python3-pil armhf 11.1.0-5build1 [435 kB]
199s Get:64 http://ftpmaster.internal/ubuntu plucky/main armhf python3.12-tk armhf 3.12.9-1 [113 kB]
199s Get:65 http://ftpmaster.internal/ubuntu plucky/main armhf python3.13-tk armhf 3.13.2-2 [103 kB]
199s Get:66 http://ftpmaster.internal/ubuntu plucky/main armhf python3-tk armhf 3.13.1-1 [9770 B]
199s Get:67 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-pil.imagetk armhf 11.1.0-5build1 [9226 B]
199s Get:68 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-matplotlib armhf 3.8.3-7build1 [17.3 MB]
199s Get:69 http://ftpmaster.internal/ubuntu plucky/main armhf python3-pytz all 2025.1-3 [162 kB]
199s Get:70 http://ftpmaster.internal/ubuntu plucky/main armhf python3-tz all 2025.1-3 [1866 B]
199s Get:71 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-pandas-lib armhf 2.2.3+dfsg-8build1 [4877 kB]
199s Get:72 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-pandas all 2.2.3+dfsg-8build1 [3112 kB]
200s Get:73 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-threadpoolctl all 3.1.0-1 [21.3 kB]
200s Get:74 http://ftpmaster.internal/ubuntu plucky-proposed/universe armhf python3-sklearn-lib armhf 1.4.2+dfsg-8 [4014 kB]
200s Get:75 http://ftpmaster.internal/ubuntu plucky-proposed/universe armhf python3-sklearn all 1.4.2+dfsg-8 [2258 kB]
200s Get:76 http://ftpmaster.internal/ubuntu plucky/universe armhf python3-xgboost armhf 2.1.4-1build1 [119 kB]
201s Fetched 85.2 MB in 4s (19.3 MB/s)
201s Selecting previously unselected package python3-numpy-dev:armhf.
201s (Reading database ... 
(Reading database ... 5%
(Reading database ... 10%
(Reading database ... 15%
(Reading database ... 20%
(Reading database ... 25%
(Reading database ... 30%
(Reading database ... 35%
(Reading database ... 40%
(Reading database ... 45%
(Reading database ... 50%
(Reading database ... 55%
(Reading database ... 60%
(Reading database ... 65%
(Reading database ... 70%
(Reading database ... 75%
(Reading database ... 80%
(Reading database ... 85%
(Reading database ... 90%
(Reading database ... 95%
(Reading database ... 100%
(Reading database ... 64655 files and directories currently installed.)
201s Preparing to unpack .../00-python3-numpy-dev_1%3a2.2.3+ds-5_armhf.deb ...
201s Unpacking python3-numpy-dev:armhf (1:2.2.3+ds-5) ...
201s Selecting previously unselected package libblas3:armhf.
201s Preparing to unpack .../01-libblas3_3.12.1-2_armhf.deb ...
201s Unpacking libblas3:armhf (3.12.1-2) ...
201s Selecting previously unselected package libgfortran5:armhf.
201s Preparing to unpack .../02-libgfortran5_15-20250222-0ubuntu1_armhf.deb ...
201s Unpacking libgfortran5:armhf (15-20250222-0ubuntu1) ...
201s Selecting previously unselected package liblapack3:armhf.
201s Preparing to unpack .../03-liblapack3_3.12.1-2_armhf.deb ...
201s Unpacking liblapack3:armhf (3.12.1-2) ...
201s Selecting previously unselected package python3-numpy.
201s Preparing to unpack .../04-python3-numpy_1%3a2.2.3+ds-5_armhf.deb ...
201s Unpacking python3-numpy (1:2.2.3+ds-5) ...
202s Selecting previously unselected package libtcl8.6:armhf.
202s Preparing to unpack .../05-libtcl8.6_8.6.16+dfsg-1_armhf.deb ...
202s Unpacking libtcl8.6:armhf (8.6.16+dfsg-1) ...
202s Selecting previously unselected package libfreetype6:armhf.
202s Preparing to unpack .../06-libfreetype6_2.13.3+dfsg-1_armhf.deb ...
202s Unpacking libfreetype6:armhf (2.13.3+dfsg-1) ...
202s Selecting previously unselected package fonts-dejavu-mono.
202s Preparing to unpack .../07-fonts-dejavu-mono_2.37-8_all.deb ...
202s Unpacking fonts-dejavu-mono (2.37-8) ...
202s Selecting previously unselected package fonts-dejavu-core.
202s Preparing to unpack .../08-fonts-dejavu-core_2.37-8_all.deb ...
202s Unpacking fonts-dejavu-core (2.37-8) ...
202s Selecting previously unselected package fontconfig-config.
202s Preparing to unpack .../09-fontconfig-config_2.15.0-2ubuntu1_armhf.deb ...
203s Unpacking fontconfig-config (2.15.0-2ubuntu1) ...
203s Selecting previously unselected package libfontconfig1:armhf.
203s Preparing to unpack .../10-libfontconfig1_2.15.0-2ubuntu1_armhf.deb ...
203s Unpacking libfontconfig1:armhf (2.15.0-2ubuntu1) ...
203s Selecting previously unselected package libxrender1:armhf.
203s Preparing to unpack .../11-libxrender1_1%3a0.9.10-1.1build1_armhf.deb ...
203s Unpacking libxrender1:armhf (1:0.9.10-1.1build1) ...
203s Selecting previously unselected package libxft2:armhf.
203s Preparing to unpack .../12-libxft2_2.3.6-1build1_armhf.deb ...
203s Unpacking libxft2:armhf (2.3.6-1build1) ...
203s Selecting previously unselected package x11-common.
203s Preparing to unpack .../13-x11-common_1%3a7.7+23ubuntu3_all.deb ...
203s Unpacking x11-common (1:7.7+23ubuntu3) ...
203s Selecting previously unselected package libxss1:armhf.
203s Preparing to unpack .../14-libxss1_1%3a1.2.3-1build3_armhf.deb ...
203s Unpacking libxss1:armhf (1:1.2.3-1build3) ...
203s Selecting previously unselected package libtk8.6:armhf.
203s Preparing to unpack .../15-libtk8.6_8.6.16-1_armhf.deb ...
203s Unpacking libtk8.6:armhf (8.6.16-1) ...
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211s Setting up libgraphite2-3:armhf (1.3.14-2ubuntu1) ...
211s Setting up liblcms2-2:armhf (2.16-2) ...
211s Setting up libsharpyuv0:armhf (1.5.0-0.1) ...
211s Setting up liblerc4:armhf (4.0.0+ds-5ubuntu1) ...
211s Setting up libxrender1:armhf (1:0.9.10-1.1build1) ...
211s Setting up python3-joblib (1.4.2-3) ...
211s Setting up python3-lz4 (4.4.0+dfsg-1build1) ...
211s Setting up python3-unicodedata2 (15.1.0+ds-1build3) ...
211s Setting up fonts-lyx (2.4.3-1) ...
211s Setting up python3-threadpoolctl (3.1.0-1) ...
211s Setting up x11-common (1:7.7+23ubuntu3) ...
212s Setting up libdeflate0:armhf (1.23-1) ...
212s Setting up libqhull-r8.0:armhf (2020.2-6build1) ...
212s Setting up python3-pytz (2025.1-3) ...
212s Setting up libgomp1:armhf (15-20250222-0ubuntu1) ...
212s Setting up libjbig0:armhf (2.1-6.1ubuntu2) ...
212s Setting up python3-platformdirs (4.3.6-1) ...
212s Setting up python3-tz (2025.1-3) ...
212s Setting up python3-fs (2.4.16-7) ...
213s Setting up unicode-data (15.1.0-1) ...
213s Setting up python3-decorator (5.1.1-5) ...
213s Setting up libblas3:armhf (3.12.1-2) ...
213s update-alternatives: using /usr/lib/arm-linux-gnueabihf/blas/libblas.so.3 to provide /usr/lib/arm-linux-gnueabihf/libblas.so.3 (libblas.so.3-arm-linux-gnueabihf) in auto mode
213s Setting up libfreetype6:armhf (2.13.3+dfsg-1) ...
213s Setting up python3-brotli (1.1.0-2build4) ...
213s Setting up python3-cycler (0.12.1-1) ...
213s Setting up libimagequant0:armhf (2.18.0-1build1) ...
213s Setting up fonts-dejavu-mono (2.37-8) ...
213s Setting up python3-kiwisolver (1.4.7-3build1) ...
213s Setting up python3-numpy-dev:armhf (1:2.2.3+ds-5) ...
213s Setting up libtcl8.6:armhf (8.6.16+dfsg-1) ...
213s Setting up fonts-dejavu-core (2.37-8) ...
214s Setting up libjpeg-turbo8:armhf (2.1.5-3ubuntu2) ...
214s Setting up libgfortran5:armhf (15-20250222-0ubuntu1) ...
214s Setting up libwebp7:armhf (1.5.0-0.1) ...
214s Setting up libxslt1.1:armhf (1.1.39-0exp1ubuntu2) ...
214s Setting up libopenjp2-7:armhf (2.5.3-2) ...
214s Setting up libharfbuzz0b:armhf (10.2.0-1) ...
214s Setting up libxss1:armhf (1:1.2.3-1build3) ...
214s Setting up libjs-jquery (3.6.1+dfsg+~3.5.14-1) ...
214s Setting up python3-mpmath (1.3.0-1) ...
214s Setting up python-matplotlib-data (3.8.3-7build1) ...
214s Setting up libwebpmux3:armhf (1.5.0-0.1) ...
214s Setting up libjpeg8:armhf (8c-2ubuntu11) ...
214s Setting up python3-sympy (1.13.3-5) ...
222s Setting up liblapack3:armhf (3.12.1-2) ...
222s update-alternatives: using /usr/lib/arm-linux-gnueabihf/lapack/liblapack.so.3 to provide /usr/lib/arm-linux-gnueabihf/liblapack.so.3 (liblapack.so.3-arm-linux-gnueabihf) in auto mode
222s Setting up libdmlc0t64:armhf (0.5+git20240614.1334185-1) ...
222s Setting up fontconfig-config (2.15.0-2ubuntu1) ...
223s Setting up libwebpdemux2:armhf (1.5.0-0.1) ...
223s Setting up libjs-jquery-ui (1.13.2+dfsg-1) ...
223s Setting up libraqm0:armhf (0.10.2-1) ...
223s Setting up python3-numpy (1:2.2.3+ds-5) ...
226s Setting up python3-lxml:armhf (5.3.1-1build1) ...
226s Setting up libtiff6:armhf (4.5.1+git230720-4ubuntu4) ...
226s Setting up libxgboost0 (2.1.4-1build1) ...
226s Setting up python3-contourpy (1.3.1-1build1) ...
226s Setting up libfontconfig1:armhf (2.15.0-2ubuntu1) ...
226s Setting up liblbfgsb0:armhf (3.0+dfsg.4-1build1) ...
226s Setting up libxft2:armhf (2.3.6-1build1) ...
226s Setting up python3-scipy (1.14.1-4ubuntu2) ...
231s Setting up libtk8.6:armhf (8.6.16-1) ...
231s Setting up python3-pandas-lib:armhf (2.2.3+dfsg-8build1) ...
231s Setting up python3.12-tk (3.12.9-1) ...
231s Setting up python3-sklearn-lib:armhf (1.4.2+dfsg-8) ...
231s Setting up python3.13-tk (3.13.2-2) ...
231s Setting up python3-pil:armhf (11.1.0-5build1) ...
232s Setting up python3-xgboost (2.1.4-1build1) ...
232s Setting up python3-pandas (2.2.3+dfsg-8build1) ...
240s Setting up libxgboost-dev (2.1.4-1build1) ...
240s Setting up python3-sklearn (1.4.2+dfsg-8) ...
243s Setting up tk8.6-blt2.5 (2.5.3+dfsg-8) ...
243s Setting up blt (2.5.3+dfsg-8) ...
243s Setting up python3-tk:armhf (3.13.1-1) ...
243s Setting up python3-pil.imagetk:armhf (11.1.0-5build1) ...
243s Setting up python3-fonttools (4.55.3-2build1) ...
244s Setting up python3-ufolib2 (0.17.0+dfsg1-1) ...
244s Setting up python3-matplotlib (3.8.3-7build1) ...
247s Processing triggers for libc-bin (2.41-1ubuntu1) ...
247s Processing triggers for man-db (2.13.0-1) ...
260s autopkgtest [01:38:38]: test run-demos: [-----------------------
262s ==========================================
262s Running case basic_walkthrough.py...
264s [0]	eval-logloss:0.22646	train-logloss:0.23316
264s [1]	eval-logloss:0.13776	train-logloss:0.13654
264s error=0.021726
264s ==========================================
264s Running case boost_from_prediction.py...
265s /usr/lib/python3/dist-packages/xgboost/core.py:723: FutureWarning: Pass `evals` as keyword args.
265s   warnings.warn(msg, FutureWarning)
265s start running example to start from a initial prediction
265s [0]	eval-logloss:0.22646	train-logloss:0.23316
265s this is result of running from initial prediction
265s [0]	eval-logloss:0.13776	train-logloss:0.13654
265s ==========================================
265s Running case callbacks.py...
268s /usr/lib/python3/dist-packages/xgboost/core.py:158: UserWarning: [01:38:46] WARNING: ./src/context.cc:196: XGBoost is not compiled with CUDA support.
268s   warnings.warn(smsg, UserWarning)
268s [0]	Train-error:0.03052	Train-rmse:0.35870	Valid-error:0.06993	Valid-rmse:0.37215
268s [1]	Train-error:0.01174	Train-rmse:0.27804	Valid-error:0.04895	Valid-rmse:0.29761
268s [2]	Train-error:0.01174	Train-rmse:0.21911	Valid-error:0.04895	Valid-rmse:0.25064
268s [3]	Train-error:0.00939	Train-rmse:0.17913	Valid-error:0.02797	Valid-rmse:0.21447
268s [4]	Train-error:0.00939	Train-rmse:0.14893	Valid-error:0.02797	Valid-rmse:0.19740
268s [5]	Train-error:0.00939	Train-rmse:0.12816	Valid-error:0.03497	Valid-rmse:0.18098
268s [6]	Train-error:0.00704	Train-rmse:0.11060	Valid-error:0.03497	Valid-rmse:0.17131
268s [7]	Train-error:0.00704	Train-rmse:0.09947	Valid-error:0.03497	Valid-rmse:0.16077
268s [8]	Train-error:0.00469	Train-rmse:0.08816	Valid-error:0.02797	Valid-rmse:0.14865
268s [9]	Train-error:0.00469	Train-rmse:0.07863	Valid-error:0.03497	Valid-rmse:0.15073
268s [10]	Train-error:0.00469	Train-rmse:0.07164	Valid-error:0.02098	Valid-rmse:0.14161
268s [11]	Train-error:0.00469	Train-rmse:0.06692	Valid-error:0.01399	Valid-rmse:0.14028
268s [12]	Train-error:0.00235	Train-rmse:0.06216	Valid-error:0.01399	Valid-rmse:0.13727
268s [13]	Train-error:0.00235	Train-rmse:0.05811	Valid-error:0.01399	Valid-rmse:0.13495
268s [14]	Train-error:0.00000	Train-rmse:0.05532	Valid-error:0.02098	Valid-rmse:0.13500
269s [15]	Train-error:0.00000	Train-rmse:0.05178	Valid-error:0.02098	Valid-rmse:0.13226
269s [16]	Train-error:0.00000	Train-rmse:0.04924	Valid-error:0.02098	Valid-rmse:0.13329
269s [17]	Train-error:0.00000	Train-rmse:0.04656	Valid-error:0.01399	Valid-rmse:0.13183
269s [18]	Train-error:0.00000	Train-rmse:0.04437	Valid-error:0.01399	Valid-rmse:0.13353
269s [19]	Train-error:0.00000	Train-rmse:0.04272	Valid-error:0.02098	Valid-rmse:0.13468
269s [20]	Train-error:0.00000	Train-rmse:0.04030	Valid-error:0.02098	Valid-rmse:0.13419
269s [21]	Train-error:0.00000	Train-rmse:0.03869	Valid-error:0.02797	Valid-rmse:0.13543
269s [22]	Train-error:0.00000	Train-rmse:0.03548	Valid-error:0.03497	Valid-rmse:0.13316
269s [23]	Train-error:0.00000	Train-rmse:0.03444	Valid-error:0.03497	Valid-rmse:0.13637
269s [24]	Train-error:0.00000	Train-rmse:0.03369	Valid-error:0.04196	Valid-rmse:0.13663
269s [25]	Train-error:0.00000	Train-rmse:0.03213	Valid-error:0.03497	Valid-rmse:0.13386
269s [26]	Train-error:0.00000	Train-rmse:0.03100	Valid-error:0.03497	Valid-rmse:0.13180
269s [27]	Train-error:0.00000	Train-rmse:0.03036	Valid-error:0.03497	Valid-rmse:0.13263
269s [28]	Train-error:0.00000	Train-rmse:0.02957	Valid-error:0.04196	Valid-rmse:0.13493
269s [29]	Train-error:0.00000	Train-rmse:0.02866	Valid-error:0.03497	Valid-rmse:0.13487
269s [30]	Train-error:0.00000	Train-rmse:0.02851	Valid-error:0.04196	Valid-rmse:0.13384
269s [31]	Train-error:0.00000	Train-rmse:0.02721	Valid-error:0.02797	Valid-rmse:0.13117
269s [32]	Train-error:0.00000	Train-rmse:0.02615	Valid-error:0.03497	Valid-rmse:0.13188
269s [33]	Train-error:0.00000	Train-rmse:0.02559	Valid-error:0.03497	Valid-rmse:0.13096
269s [34]	Train-error:0.00000	Train-rmse:0.02520	Valid-error:0.04196	Valid-rmse:0.13283
269s [35]	Train-error:0.00000	Train-rmse:0.02438	Valid-error:0.03497	Valid-rmse:0.13220
269s [36]	Train-error:0.00000	Train-rmse:0.02356	Valid-error:0.03497	Valid-rmse:0.13030
269s [37]	Train-error:0.00000	Train-rmse:0.02348	Valid-error:0.03497	Valid-rmse:0.12942
270s [38]	Train-error:0.00000	Train-rmse:0.02337	Valid-error:0.03497	Valid-rmse:0.12955
270s [39]	Train-error:0.00000	Train-rmse:0.02265	Valid-error:0.02797	Valid-rmse:0.12785
270s [40]	Train-error:0.00000	Train-rmse:0.02283	Valid-error:0.03497	Valid-rmse:0.12889
270s [41]	Train-error:0.00000	Train-rmse:0.02255	Valid-error:0.03497	Valid-rmse:0.13066
270s [42]	Train-error:0.00000	Train-rmse:0.02190	Valid-error:0.03497	Valid-rmse:0.12905
270s [43]	Train-error:0.00000	Train-rmse:0.02173	Valid-error:0.03497	Valid-rmse:0.12833
270s [44]	Train-error:0.00000	Train-rmse:0.02180	Valid-error:0.03497	Valid-rmse:0.12884
270s [45]	Train-error:0.00000	Train-rmse:0.02153	Valid-error:0.03497	Valid-rmse:0.13050
270s [46]	Train-error:0.00000	Train-rmse:0.02149	Valid-error:0.03497	Valid-rmse:0.12927
270s [47]	Train-error:0.00000	Train-rmse:0.02134	Valid-error:0.02797	Valid-rmse:0.13012
270s [48]	Train-error:0.00000	Train-rmse:0.02119	Valid-error:0.03497	Valid-rmse:0.12936
270s [49]	Train-error:0.00000	Train-rmse:0.02124	Valid-error:0.02797	Valid-rmse:0.12989
270s [50]	Train-error:0.00000	Train-rmse:0.02116	Valid-error:0.02797	Valid-rmse:0.13014
270s [51]	Train-error:0.00000	Train-rmse:0.02107	Valid-error:0.02797	Valid-rmse:0.12953
270s [52]	Train-error:0.00000	Train-rmse:0.02121	Valid-error:0.02797	Valid-rmse:0.12976
270s [53]	Train-error:0.00000	Train-rmse:0.02080	Valid-error:0.02797	Valid-rmse:0.12903
270s [54]	Train-error:0.00000	Train-rmse:0.02060	Valid-error:0.02797	Valid-rmse:0.13032
271s [55]	Train-error:0.00000	Train-rmse:0.02069	Valid-error:0.02797	Valid-rmse:0.13027
271s [56]	Train-error:0.00000	Train-rmse:0.02039	Valid-error:0.02797	Valid-rmse:0.12900
271s [57]	Train-error:0.00000	Train-rmse:0.02031	Valid-error:0.02797	Valid-rmse:0.12845
271s [58]	Train-error:0.00000	Train-rmse:0.02047	Valid-error:0.02797	Valid-rmse:0.12928
271s [59]	Train-error:0.00000	Train-rmse:0.02013	Valid-error:0.02797	Valid-rmse:0.12865
271s [60]	Train-error:0.00000	Train-rmse:0.02027	Valid-error:0.02797	Valid-rmse:0.12884
271s [61]	Train-error:0.00000	Train-rmse:0.02023	Valid-error:0.02797	Valid-rmse:0.12917
271s [62]	Train-error:0.00000	Train-rmse:0.02013	Valid-error:0.02797	Valid-rmse:0.12947
271s [63]	Train-error:0.00000	Train-rmse:0.01986	Valid-error:0.02797	Valid-rmse:0.12827
271s [64]	Train-error:0.00000	Train-rmse:0.01980	Valid-error:0.02797	Valid-rmse:0.12780
271s [65]	Train-error:0.00000	Train-rmse:0.01971	Valid-error:0.02797	Valid-rmse:0.12888
271s [66]	Train-error:0.00000	Train-rmse:0.01980	Valid-error:0.02797	Valid-rmse:0.12928
271s [67]	Train-error:0.00000	Train-rmse:0.01977	Valid-error:0.02797	Valid-rmse:0.12962
271s [68]	Train-error:0.00000	Train-rmse:0.01969	Valid-error:0.02797	Valid-rmse:0.12991
271s [69]	Train-error:0.00000	Train-rmse:0.01940	Valid-error:0.02797	Valid-rmse:0.12920
271s [70]	Train-error:0.00000	Train-rmse:0.01941	Valid-error:0.02797	Valid-rmse:0.12825
271s [71]	Train-error:0.00000	Train-rmse:0.01936	Valid-error:0.02797	Valid-rmse:0.12785
271s [72]	Train-error:0.00000	Train-rmse:0.01950	Valid-error:0.02797	Valid-rmse:0.12858
271s [73]	Train-error:0.00000	Train-rmse:0.01921	Valid-error:0.02797	Valid-rmse:0.12791
271s [74]	Train-error:0.00000	Train-rmse:0.01914	Valid-error:0.02797	Valid-rmse:0.12832
272s [75]	Train-error:0.00000	Train-rmse:0.01912	Valid-error:0.02797	Valid-rmse:0.12821
272s [76]	Train-error:0.00000	Train-rmse:0.01906	Valid-error:0.02797	Valid-rmse:0.12814
272s [77]	Train-error:0.00000	Train-rmse:0.01897	Valid-error:0.02797	Valid-rmse:0.12845
272s [78]	Train-error:0.00000	Train-rmse:0.01875	Valid-error:0.02797	Valid-rmse:0.12734
272s [79]	Train-error:0.00000	Train-rmse:0.01873	Valid-error:0.02797	Valid-rmse:0.12765
272s [80]	Train-error:0.00000	Train-rmse:0.01866	Valid-error:0.02797	Valid-rmse:0.12793
272s [81]	Train-error:0.00000	Train-rmse:0.01869	Valid-error:0.02797	Valid-rmse:0.12708
272s [82]	Train-error:0.00000	Train-rmse:0.01844	Valid-error:0.02797	Valid-rmse:0.12642
272s [83]	Train-error:0.00000	Train-rmse:0.01857	Valid-error:0.02797	Valid-rmse:0.12709
272s [84]	Train-error:0.00000	Train-rmse:0.01853	Valid-error:0.02797	Valid-rmse:0.12674
272s [85]	Train-error:0.00000	Train-rmse:0.01862	Valid-error:0.02797	Valid-rmse:0.12712
272s [86]	Train-error:0.00000	Train-rmse:0.01853	Valid-error:0.02797	Valid-rmse:0.12754
272s [87]	Train-error:0.00000	Train-rmse:0.01829	Valid-error:0.02797	Valid-rmse:0.12693
272s [88]	Train-error:0.00000	Train-rmse:0.01821	Valid-error:0.02797	Valid-rmse:0.12788
272s [89]	Train-error:0.00000	Train-rmse:0.01816	Valid-error:0.02797	Valid-rmse:0.12782
272s [90]	Train-error:0.00000	Train-rmse:0.01816	Valid-error:0.02797	Valid-rmse:0.12768
272s [91]	Train-error:0.00000	Train-rmse:0.01809	Valid-error:0.02797	Valid-rmse:0.12797
272s [92]	Train-error:0.00000	Train-rmse:0.01807	Valid-error:0.02797	Valid-rmse:0.12768
272s [93]	Train-error:0.00000	Train-rmse:0.01798	Valid-error:0.02797	Valid-rmse:0.12858
272s [94]	Train-error:0.00000	Train-rmse:0.01776	Valid-error:0.02797	Valid-rmse:0.12801
273s [95]	Train-error:0.00000	Train-rmse:0.01786	Valid-error:0.02797	Valid-rmse:0.12804
273s [96]	Train-error:0.00000	Train-rmse:0.01779	Valid-error:0.02797	Valid-rmse:0.12844
273s [97]	Train-error:0.00000	Train-rmse:0.01778	Valid-error:0.02797	Valid-rmse:0.12875
273s [98]	Train-error:0.00000	Train-rmse:0.01759	Valid-error:0.02797	Valid-rmse:0.12806
273s [99]	Train-error:0.00000	Train-rmse:0.01771	Valid-error:0.02797	Valid-rmse:0.12865
273s ==========================================
273s Skip case cat_in_the_dat.py...
273s ==========================================
273s Running case cat_pipeline.py...
275s ==========================================
275s Running case categorical.py...
276s /usr/lib/python3/dist-packages/xgboost/core.py:158: UserWarning: [01:38:54] WARNING: ./src/context.cc:196: XGBoost is not compiled with CUDA support.
276s   warnings.warn(smsg, UserWarning)
276s [0]	validation_0-rmse:2.94171
276s [1]	validation_0-rmse:2.40095
276s [2]	validation_0-rmse:1.96121
276s [3]	validation_0-rmse:1.61285
277s [4]	validation_0-rmse:1.35854
277s [5]	validation_0-rmse:1.12286
277s [6]	validation_0-rmse:0.96789
277s [7]	validation_0-rmse:0.79707
277s [8]	validation_0-rmse:0.66201
277s [9]	validation_0-rmse:0.55282
277s [10]	validation_0-rmse:0.46038
277s [11]	validation_0-rmse:0.38278
277s [12]	validation_0-rmse:0.32840
277s [13]	validation_0-rmse:0.27462
277s [14]	validation_0-rmse:0.23398
277s [15]	validation_0-rmse:0.19823
277s [16]	validation_0-rmse:0.16984
277s [17]	validation_0-rmse:0.14636
277s [18]	validation_0-rmse:0.12447
277s [19]	validation_0-rmse:0.10444
277s [20]	validation_0-rmse:0.08984
277s [21]	validation_0-rmse:0.07610
277s [22]	validation_0-rmse:0.06622
277s [23]	validation_0-rmse:0.05653
277s [24]	validation_0-rmse:0.04906
277s [25]	validation_0-rmse:0.04173
277s [26]	validation_0-rmse:0.03550
277s [27]	validation_0-rmse:0.03046
277s [28]	validation_0-rmse:0.02585
277s [29]	validation_0-rmse:0.02187
277s [30]	validation_0-rmse:0.01863
277s [31]	validation_0-rmse:0.01597
277s [32]	validation_0-rmse:0.01361
277s [33]	validation_0-rmse:0.01166
277s [34]	validation_0-rmse:0.01041
277s [35]	validation_0-rmse:0.00909
277s [36]	validation_0-rmse:0.00780
277s [37]	validation_0-rmse:0.00666
277s [38]	validation_0-rmse:0.00569
277s [39]	validation_0-rmse:0.00493
277s [40]	validation_0-rmse:0.00426
277s [41]	validation_0-rmse:0.00365
277s [42]	validation_0-rmse:0.00314
277s [43]	validation_0-rmse:0.00268
277s [44]	validation_0-rmse:0.00233
277s [45]	validation_0-rmse:0.00200
277s [46]	validation_0-rmse:0.00170
277s [47]	validation_0-rmse:0.00148
277s [48]	validation_0-rmse:0.00130
277s [49]	validation_0-rmse:0.00116
277s [50]	validation_0-rmse:0.00100
277s [51]	validation_0-rmse:0.00090
277s [52]	validation_0-rmse:0.00082
277s [53]	validation_0-rmse:0.00075
277s [54]	validation_0-rmse:0.00075
277s [55]	validation_0-rmse:0.00075
277s [56]	validation_0-rmse:0.00075
277s [57]	validation_0-rmse:0.00075
277s [58]	validation_0-rmse:0.00075
277s [59]	validation_0-rmse:0.00075
277s [60]	validation_0-rmse:0.00075
277s [61]	validation_0-rmse:0.00075
277s [62]	validation_0-rmse:0.00075
277s [63]	validation_0-rmse:0.00075
277s [64]	validation_0-rmse:0.00075
277s [65]	validation_0-rmse:0.00075
277s [66]	validation_0-rmse:0.00075
277s [67]	validation_0-rmse:0.00075
277s [68]	validation_0-rmse:0.00075
277s [69]	validation_0-rmse:0.00075
277s [70]	validation_0-rmse:0.00075
277s [71]	validation_0-rmse:0.00075
277s [72]	validation_0-rmse:0.00075
277s [73]	validation_0-rmse:0.00075
277s [74]	validation_0-rmse:0.00075
277s [75]	validation_0-rmse:0.00075
277s [76]	validation_0-rmse:0.00075
277s [77]	validation_0-rmse:0.00075
277s [78]	validation_0-rmse:0.00075
277s [79]	validation_0-rmse:0.00075
277s [80]	validation_0-rmse:0.00075
277s [81]	validation_0-rmse:0.00075
277s [82]	validation_0-rmse:0.00075
277s [83]	validation_0-rmse:0.00075
277s [84]	validation_0-rmse:0.00075
277s [85]	validation_0-rmse:0.00075
277s [86]	validation_0-rmse:0.00075
277s [87]	validation_0-rmse:0.00075
277s [88]	validation_0-rmse:0.00075
277s [89]	validation_0-rmse:0.00075
277s [90]	validation_0-rmse:0.00075
277s [91]	validation_0-rmse:0.00075
277s [92]	validation_0-rmse:0.00075
277s [93]	validation_0-rmse:0.00075
277s [94]	validation_0-rmse:0.00075
277s [95]	validation_0-rmse:0.00075
277s [96]	validation_0-rmse:0.00075
277s [97]	validation_0-rmse:0.00075
277s [98]	validation_0-rmse:0.00075
277s [99]	validation_0-rmse:0.00075
278s /usr/lib/python3/dist-packages/xgboost/core.py:158: UserWarning: [01:38:55] WARNING: ./src/context.cc:196: XGBoost is not compiled with CUDA support.
278s   warnings.warn(smsg, UserWarning)
278s [0]	validation_0-rmse:2.94171
278s [1]	validation_0-rmse:2.40095
278s [2]	validation_0-rmse:1.96121
278s [3]	validation_0-rmse:1.61285
278s [4]	validation_0-rmse:1.35854
278s [5]	validation_0-rmse:1.12286
278s [6]	validation_0-rmse:0.96789
278s [7]	validation_0-rmse:0.79707
278s [8]	validation_0-rmse:0.66201
278s [9]	validation_0-rmse:0.55282
278s [10]	validation_0-rmse:0.46038
278s [11]	validation_0-rmse:0.38278
278s [12]	validation_0-rmse:0.32840
278s [13]	validation_0-rmse:0.27462
278s [14]	validation_0-rmse:0.23398
278s [15]	validation_0-rmse:0.19823
278s [16]	validation_0-rmse:0.16984
278s [17]	validation_0-rmse:0.14636
278s [18]	validation_0-rmse:0.12447
278s [19]	validation_0-rmse:0.10444
278s [20]	validation_0-rmse:0.08984
278s [21]	validation_0-rmse:0.07610
278s [22]	validation_0-rmse:0.06622
278s [23]	validation_0-rmse:0.05653
278s [24]	validation_0-rmse:0.04906
278s [25]	validation_0-rmse:0.04173
278s [26]	validation_0-rmse:0.03550
278s [27]	validation_0-rmse:0.03046
278s [28]	validation_0-rmse:0.02585
278s [29]	validation_0-rmse:0.02187
278s [30]	validation_0-rmse:0.01863
278s [31]	validation_0-rmse:0.01597
278s [32]	validation_0-rmse:0.01361
278s [33]	validation_0-rmse:0.01166
278s [34]	validation_0-rmse:0.01041
278s [35]	validation_0-rmse:0.00909
278s [36]	validation_0-rmse:0.00780
278s [37]	validation_0-rmse:0.00666
278s [38]	validation_0-rmse:0.00569
278s [39]	validation_0-rmse:0.00493
278s [40]	validation_0-rmse:0.00426
278s [41]	validation_0-rmse:0.00365
278s [42]	validation_0-rmse:0.00314
278s [43]	validation_0-rmse:0.00268
278s [44]	validation_0-rmse:0.00233
278s [45]	validation_0-rmse:0.00200
278s [46]	validation_0-rmse:0.00170
278s [47]	validation_0-rmse:0.00148
278s [48]	validation_0-rmse:0.00130
278s [49]	validation_0-rmse:0.00116
278s [50]	validation_0-rmse:0.00100
278s [51]	validation_0-rmse:0.00090
278s [52]	validation_0-rmse:0.00082
278s [53]	validation_0-rmse:0.00075
278s [54]	validation_0-rmse:0.00075
278s [55]	validation_0-rmse:0.00075
278s [56]	validation_0-rmse:0.00075
278s [57]	validation_0-rmse:0.00075
278s [58]	validation_0-rmse:0.00075
278s [59]	validation_0-rmse:0.00075
278s [60]	validation_0-rmse:0.00075
278s [61]	validation_0-rmse:0.00075
278s [62]	validation_0-rmse:0.00075
278s [63]	validation_0-rmse:0.00075
278s [64]	validation_0-rmse:0.00075
278s [65]	validation_0-rmse:0.00075
278s [66]	validation_0-rmse:0.00075
278s [67]	validation_0-rmse:0.00075
278s [68]	validation_0-rmse:0.00075
278s [69]	validation_0-rmse:0.00075
278s [70]	validation_0-rmse:0.00075
278s [71]	validation_0-rmse:0.00075
278s [72]	validation_0-rmse:0.00075
278s [73]	validation_0-rmse:0.00075
278s [74]	validation_0-rmse:0.00075
278s [75]	validation_0-rmse:0.00075
278s [76]	validation_0-rmse:0.00075
278s [77]	validation_0-rmse:0.00075
278s [78]	validation_0-rmse:0.00075
278s [79]	validation_0-rmse:0.00075
278s [80]	validation_0-rmse:0.00075
278s [81]	validation_0-rmse:0.00075
278s [82]	validation_0-rmse:0.00075
278s [83]	validation_0-rmse:0.00075
278s [84]	validation_0-rmse:0.00075
278s [85]	validation_0-rmse:0.00075
278s [86]	validation_0-rmse:0.00075
278s [87]	validation_0-rmse:0.00075
278s [88]	validation_0-rmse:0.00075
278s [89]	validation_0-rmse:0.00075
278s [90]	validation_0-rmse:0.00075
278s [91]	validation_0-rmse:0.00075
278s [92]	validation_0-rmse:0.00075
278s [93]	validation_0-rmse:0.00075
278s [94]	validation_0-rmse:0.00075
278s [95]	validation_0-rmse:0.00075
278s [96]	validation_0-rmse:0.00075
278s [97]	validation_0-rmse:0.00075
278s [98]	validation_0-rmse:0.00075
278s [99]	validation_0-rmse:0.00075
279s ==========================================
279s Running case continuation.py...
280s [0]	validation_0-logloss:0.43281
280s [1]	validation_0-logloss:0.30816
280s [2]	validation_0-logloss:0.22816
280s [3]	validation_0-logloss:0.17470
280s [4]	validation_0-logloss:0.13438
280s [5]	validation_0-logloss:0.10538
280s [6]	validation_0-logloss:0.08467
280s [7]	validation_0-logloss:0.06909
280s [8]	validation_0-logloss:0.05766
280s [9]	validation_0-logloss:0.04842
280s [10]	validation_0-logloss:0.04121
280s [11]	validation_0-logloss:0.03545
280s [12]	validation_0-logloss:0.03077
280s [13]	validation_0-logloss:0.02742
280s [14]	validation_0-logloss:0.02444
280s [15]	validation_0-logloss:0.02208
280s [16]	validation_0-logloss:0.01993
280s [17]	validation_0-logloss:0.01819
280s [18]	validation_0-logloss:0.01676
280s [19]	validation_0-logloss:0.01575
280s [20]	validation_0-logloss:0.01461
280s [21]	validation_0-logloss:0.01383
280s [22]	validation_0-logloss:0.01304
280s [23]	validation_0-logloss:0.01243
280s [24]	validation_0-logloss:0.01179
280s [25]	validation_0-logloss:0.01142
280s [26]	validation_0-logloss:0.01103
280s [27]	validation_0-logloss:0.01066
280s [28]	validation_0-logloss:0.01037
280s [29]	validation_0-logloss:0.00993
280s [30]	validation_0-logloss:0.00966
280s [31]	validation_0-logloss:0.00920
280s [32]	validation_0-logloss:0.00900
280s [33]	validation_0-logloss:0.00876
280s [34]	validation_0-logloss:0.00852
280s [35]	validation_0-logloss:0.00835
280s [36]	validation_0-logloss:0.00810
280s [37]	validation_0-logloss:0.00791
280s [38]	validation_0-logloss:0.00764
280s [39]	validation_0-logloss:0.00753
280s [40]	validation_0-logloss:0.00739
280s [41]	validation_0-logloss:0.00723
280s [42]	validation_0-logloss:0.00706
280s [43]	validation_0-logloss:0.00695
280s [44]	validation_0-logloss:0.00688
280s [45]	validation_0-logloss:0.00671
280s [46]	validation_0-logloss:0.00662
280s [47]	validation_0-logloss:0.00650
280s [48]	validation_0-logloss:0.00637
280s [49]	validation_0-logloss:0.00628
280s [50]	validation_0-logloss:0.00623
280s [51]	validation_0-logloss:0.00618
280s [52]	validation_0-logloss:0.00614
280s [53]	validation_0-logloss:0.00609
280s [54]	validation_0-logloss:0.00600
280s [55]	validation_0-logloss:0.00590
280s [56]	validation_0-logloss:0.00582
280s [57]	validation_0-logloss:0.00578
280s [58]	validation_0-logloss:0.00570
280s [59]	validation_0-logloss:0.00566
280s [60]	validation_0-logloss:0.00563
280s [61]	validation_0-logloss:0.00559
280s [62]	validation_0-logloss:0.00556
280s [63]	validation_0-logloss:0.00553
280s [64]	validation_0-logloss:0.00549
280s [65]	validation_0-logloss:0.00546
280s [66]	validation_0-logloss:0.00543
280s [67]	validation_0-logloss:0.00540
280s [68]	validation_0-logloss:0.00537
280s [69]	validation_0-logloss:0.00534
280s [70]	validation_0-logloss:0.00531
280s [71]	validation_0-logloss:0.00528
280s [72]	validation_0-logloss:0.00525
280s [73]	validation_0-logloss:0.00523
280s [74]	validation_0-logloss:0.00520
280s [75]	validation_0-logloss:0.00517
280s [76]	validation_0-logloss:0.00515
280s [77]	validation_0-logloss:0.00512
280s [78]	validation_0-logloss:0.00510
280s [79]	validation_0-logloss:0.00507
280s [80]	validation_0-logloss:0.00505
280s [81]	validation_0-logloss:0.00502
280s [82]	validation_0-logloss:0.00500
280s [83]	validation_0-logloss:0.00498
280s [84]	validation_0-logloss:0.00496
280s [85]	validation_0-logloss:0.00493
280s [86]	validation_0-logloss:0.00491
280s [87]	validation_0-logloss:0.00489
280s [88]	validation_0-logloss:0.00486
280s [89]	validation_0-logloss:0.00484
280s [90]	validation_0-logloss:0.00482
280s [91]	validation_0-logloss:0.00480
280s [92]	validation_0-logloss:0.00478
280s [93]	validation_0-logloss:0.00476
280s [94]	validation_0-logloss:0.00474
280s [95]	validation_0-logloss:0.00472
280s [96]	validation_0-logloss:0.00470
280s [97]	validation_0-logloss:0.00468
280s [98]	validation_0-logloss:0.00466
280s [99]	validation_0-logloss:0.00464
280s [100]	validation_0-logloss:0.00463
280s [101]	validation_0-logloss:0.00461
280s [102]	validation_0-logloss:0.00459
280s [103]	validation_0-logloss:0.00457
280s [104]	validation_0-logloss:0.00456
280s [105]	validation_0-logloss:0.00454
280s [106]	validation_0-logloss:0.00452
280s [107]	validation_0-logloss:0.00451
280s [108]	validation_0-logloss:0.00449
280s [109]	validation_0-logloss:0.00448
280s [110]	validation_0-logloss:0.00446
280s [111]	validation_0-logloss:0.00444
280s [112]	validation_0-logloss:0.00443
280s [113]	validation_0-logloss:0.00441
280s [114]	validation_0-logloss:0.00440
280s [115]	validation_0-logloss:0.00438
280s [116]	validation_0-logloss:0.00437
280s [117]	validation_0-logloss:0.00435
280s [118]	validation_0-logloss:0.00434
280s [119]	validation_0-logloss:0.00433
280s [120]	validation_0-logloss:0.00431
280s [121]	validation_0-logloss:0.00430
280s [122]	validation_0-logloss:0.00429
280s [123]	validation_0-logloss:0.00427
280s [124]	validation_0-logloss:0.00426
280s [125]	validation_0-logloss:0.00425
280s [126]	validation_0-logloss:0.00423
280s [127]	validation_0-logloss:0.00422
280s [128]	validation_0-logloss:0.00421
280s [129]	validation_0-logloss:0.00420
280s [130]	validation_0-logloss:0.00419
281s [131]	validation_0-logloss:0.00417
281s [132]	validation_0-logloss:0.00416
281s [133]	validation_0-logloss:0.00415
281s [134]	validation_0-logloss:0.00414
281s [135]	validation_0-logloss:0.00413
281s [136]	validation_0-logloss:0.00412
281s [137]	validation_0-logloss:0.00411
281s [138]	validation_0-logloss:0.00410
281s [139]	validation_0-logloss:0.00409
281s [140]	validation_0-logloss:0.00408
281s [141]	validation_0-logloss:0.00407
281s [142]	validation_0-logloss:0.00406
281s [143]	validation_0-logloss:0.00405
281s [144]	validation_0-logloss:0.00404
281s [145]	validation_0-logloss:0.00403
281s [146]	validation_0-logloss:0.00402
281s [147]	validation_0-logloss:0.00401
281s [148]	validation_0-logloss:0.00400
281s [149]	validation_0-logloss:0.00399
281s [150]	validation_0-logloss:0.00398
281s [151]	validation_0-logloss:0.00397
281s [152]	validation_0-logloss:0.00396
281s [153]	validation_0-logloss:0.00396
281s [154]	validation_0-logloss:0.00395
281s [155]	validation_0-logloss:0.00394
281s [156]	validation_0-logloss:0.00393
281s [157]	validation_0-logloss:0.00392
281s [158]	validation_0-logloss:0.00391
281s [159]	validation_0-logloss:0.00391
281s [160]	validation_0-logloss:0.00390
281s [161]	validation_0-logloss:0.00389
281s [162]	validation_0-logloss:0.00388
281s [163]	validation_0-logloss:0.00388
281s [164]	validation_0-logloss:0.00387
281s [165]	validation_0-logloss:0.00386
281s [166]	validation_0-logloss:0.00385
281s [167]	validation_0-logloss:0.00385
281s [168]	validation_0-logloss:0.00384
281s [169]	validation_0-logloss:0.00383
281s [170]	validation_0-logloss:0.00383
281s [171]	validation_0-logloss:0.00382
281s [172]	validation_0-logloss:0.00381
281s [173]	validation_0-logloss:0.00381
281s [174]	validation_0-logloss:0.00380
281s [175]	validation_0-logloss:0.00380
281s [176]	validation_0-logloss:0.00379
281s [177]	validation_0-logloss:0.00379
281s [178]	validation_0-logloss:0.00378
281s [179]	validation_0-logloss:0.00378
281s [180]	validation_0-logloss:0.00377
281s [181]	validation_0-logloss:0.00377
281s [182]	validation_0-logloss:0.00376
281s [183]	validation_0-logloss:0.00376
281s [184]	validation_0-logloss:0.00375
281s [185]	validation_0-logloss:0.00375
281s [186]	validation_0-logloss:0.00374
281s [187]	validation_0-logloss:0.00374
281s [188]	validation_0-logloss:0.00373
281s [189]	validation_0-logloss:0.00373
281s [190]	validation_0-logloss:0.00373
281s [191]	validation_0-logloss:0.00372
281s [192]	validation_0-logloss:0.00372
281s [193]	validation_0-logloss:0.00372
281s [194]	validation_0-logloss:0.00371
281s [195]	validation_0-logloss:0.00371
281s [196]	validation_0-logloss:0.00371
281s [197]	validation_0-logloss:0.00371
281s [198]	validation_0-logloss:0.00371
281s Total boosted rounds: 195
281s [0]	validation_0-logloss:0.43281
281s [1]	validation_0-logloss:0.30816
281s [2]	validation_0-logloss:0.22816
281s [3]	validation_0-logloss:0.17470
281s [4]	validation_0-logloss:0.13438
281s [5]	validation_0-logloss:0.10538
281s [6]	validation_0-logloss:0.08467
281s [7]	validation_0-logloss:0.06909
281s [8]	validation_0-logloss:0.05766
281s [9]	validation_0-logloss:0.04842
281s [10]	validation_0-logloss:0.04121
281s [11]	validation_0-logloss:0.03545
281s [12]	validation_0-logloss:0.03077
281s [13]	validation_0-logloss:0.02742
281s [14]	validation_0-logloss:0.02444
281s [15]	validation_0-logloss:0.02208
281s [16]	validation_0-logloss:0.01993
281s [17]	validation_0-logloss:0.01819
281s [18]	validation_0-logloss:0.01676
281s [19]	validation_0-logloss:0.01575
281s [20]	validation_0-logloss:0.01461
281s [21]	validation_0-logloss:0.01383
281s [22]	validation_0-logloss:0.01304
281s [23]	validation_0-logloss:0.01243
281s [24]	validation_0-logloss:0.01179
281s [25]	validation_0-logloss:0.01142
281s [26]	validation_0-logloss:0.01103
281s [27]	validation_0-logloss:0.01066
281s [28]	validation_0-logloss:0.01037
281s [29]	validation_0-logloss:0.00993
281s [30]	validation_0-logloss:0.00966
281s [31]	validation_0-logloss:0.00920
281s [32]	validation_0-logloss:0.00900
281s [33]	validation_0-logloss:0.00876
281s [34]	validation_0-logloss:0.00852
281s [35]	validation_0-logloss:0.00835
281s [36]	validation_0-logloss:0.00810
281s [37]	validation_0-logloss:0.00791
281s [38]	validation_0-logloss:0.00764
281s [39]	validation_0-logloss:0.00753
281s [40]	validation_0-logloss:0.00739
281s [41]	validation_0-logloss:0.00723
281s [42]	validation_0-logloss:0.00706
281s [43]	validation_0-logloss:0.00695
281s [44]	validation_0-logloss:0.00688
281s [45]	validation_0-logloss:0.00671
281s [46]	validation_0-logloss:0.00662
281s [47]	validation_0-logloss:0.00650
281s [48]	validation_0-logloss:0.00637
281s [49]	validation_0-logloss:0.00628
281s [50]	validation_0-logloss:0.00623
281s [51]	validation_0-logloss:0.00618
281s [52]	validation_0-logloss:0.00614
281s [53]	validation_0-logloss:0.00609
281s [54]	validation_0-logloss:0.00600
281s [55]	validation_0-logloss:0.00590
281s [56]	validation_0-logloss:0.00582
281s [57]	validation_0-logloss:0.00578
281s [58]	validation_0-logloss:0.00570
281s [59]	validation_0-logloss:0.00566
281s [60]	validation_0-logloss:0.00563
281s [61]	validation_0-logloss:0.00559
281s [62]	validation_0-logloss:0.00556
281s [63]	validation_0-logloss:0.00553
281s [64]	validation_0-logloss:0.00549
281s [65]	validation_0-logloss:0.00546
281s [66]	validation_0-logloss:0.00543
281s [67]	validation_0-logloss:0.00540
281s [68]	validation_0-logloss:0.00537
281s [69]	validation_0-logloss:0.00534
281s [70]	validation_0-logloss:0.00531
281s [71]	validation_0-logloss:0.00528
281s [72]	validation_0-logloss:0.00525
281s [73]	validation_0-logloss:0.00523
281s [74]	validation_0-logloss:0.00520
281s [75]	validation_0-logloss:0.00517
281s [76]	validation_0-logloss:0.00515
281s [77]	validation_0-logloss:0.00512
281s [78]	validation_0-logloss:0.00510
281s [79]	validation_0-logloss:0.00507
281s [80]	validation_0-logloss:0.00505
281s [81]	validation_0-logloss:0.00502
281s [82]	validation_0-logloss:0.00500
281s [83]	validation_0-logloss:0.00498
281s [84]	validation_0-logloss:0.00496
281s [85]	validation_0-logloss:0.00493
281s [86]	validation_0-logloss:0.00491
281s [87]	validation_0-logloss:0.00489
281s [88]	validation_0-logloss:0.00486
281s [89]	validation_0-logloss:0.00484
281s [90]	validation_0-logloss:0.00482
281s [91]	validation_0-logloss:0.00480
281s [92]	validation_0-logloss:0.00478
281s [93]	validation_0-logloss:0.00476
281s [94]	validation_0-logloss:0.00474
281s [95]	validation_0-logloss:0.00472
281s [96]	validation_0-logloss:0.00470
281s [97]	validation_0-logloss:0.00468
281s [98]	validation_0-logloss:0.00466
281s [99]	validation_0-logloss:0.00464
281s [100]	validation_0-logloss:0.00463
281s [101]	validation_0-logloss:0.00461
281s [102]	validation_0-logloss:0.00459
281s [103]	validation_0-logloss:0.00457
281s [104]	validation_0-logloss:0.00456
281s [105]	validation_0-logloss:0.00454
281s [106]	validation_0-logloss:0.00452
281s [107]	validation_0-logloss:0.00451
281s [108]	validation_0-logloss:0.00449
281s [109]	validation_0-logloss:0.00448
281s [110]	validation_0-logloss:0.00446
281s [111]	validation_0-logloss:0.00444
281s [112]	validation_0-logloss:0.00443
281s [113]	validation_0-logloss:0.00441
281s [114]	validation_0-logloss:0.00440
281s [115]	validation_0-logloss:0.00438
281s [116]	validation_0-logloss:0.00437
281s [117]	validation_0-logloss:0.00435
281s [118]	validation_0-logloss:0.00434
281s [119]	validation_0-logloss:0.00433
281s [120]	validation_0-logloss:0.00431
281s [121]	validation_0-logloss:0.00430
281s [122]	validation_0-logloss:0.00429
281s [123]	validation_0-logloss:0.00427
281s [124]	validation_0-logloss:0.00426
281s [125]	validation_0-logloss:0.00425
281s [126]	validation_0-logloss:0.00423
281s [127]	validation_0-logloss:0.00422
281s [0]	validation_0-logloss:0.00421
281s [1]	validation_0-logloss:0.00420
281s [2]	validation_0-logloss:0.00419
281s [3]	validation_0-logloss:0.00417
281s [4]	validation_0-logloss:0.00416
281s [5]	validation_0-logloss:0.00415
281s [6]	validation_0-logloss:0.00414
281s [7]	validation_0-logloss:0.00413
281s [8]	validation_0-logloss:0.00412
281s [9]	validation_0-logloss:0.00411
281s [10]	validation_0-logloss:0.00410
281s [11]	validation_0-logloss:0.00409
281s [12]	validation_0-logloss:0.00408
281s [13]	validation_0-logloss:0.00407
281s [14]	validation_0-logloss:0.00406
281s [15]	validation_0-logloss:0.00405
281s [16]	validation_0-logloss:0.00404
281s [17]	validation_0-logloss:0.00403
281s [18]	validation_0-logloss:0.00402
281s [19]	validation_0-logloss:0.00401
281s [20]	validation_0-logloss:0.00400
281s [21]	validation_0-logloss:0.00399
281s [22]	validation_0-logloss:0.00398
281s [23]	validation_0-logloss:0.00397
281s [24]	validation_0-logloss:0.00396
281s [25]	validation_0-logloss:0.00396
281s [26]	validation_0-logloss:0.00395
281s [27]	validation_0-logloss:0.00394
281s [28]	validation_0-logloss:0.00393
281s [29]	validation_0-logloss:0.00392
281s [30]	validation_0-logloss:0.00391
281s [31]	validation_0-logloss:0.00391
281s [32]	validation_0-logloss:0.00390
281s [33]	validation_0-logloss:0.00389
281s [34]	validation_0-logloss:0.00388
281s [35]	validation_0-logloss:0.00388
281s [36]	validation_0-logloss:0.00387
281s [37]	validation_0-logloss:0.00386
281s [38]	validation_0-logloss:0.00385
281s [39]	validation_0-logloss:0.00385
281s [40]	validation_0-logloss:0.00384
281s [41]	validation_0-logloss:0.00383
281s [42]	validation_0-logloss:0.00383
281s [43]	validation_0-logloss:0.00382
281s [44]	validation_0-logloss:0.00381
281s [45]	validation_0-logloss:0.00381
281s [46]	validation_0-logloss:0.00380
281s [47]	validation_0-logloss:0.00380
281s [48]	validation_0-logloss:0.00379
281s [49]	validation_0-logloss:0.00379
281s [50]	validation_0-logloss:0.00378
281s [51]	validation_0-logloss:0.00378
281s [52]	validation_0-logloss:0.00377
281s [53]	validation_0-logloss:0.00377
281s [54]	validation_0-logloss:0.00376
281s [55]	validation_0-logloss:0.00376
281s [56]	validation_0-logloss:0.00375
281s [57]	validation_0-logloss:0.00375
281s [58]	validation_0-logloss:0.00374
281s [59]	validation_0-logloss:0.00374
281s [60]	validation_0-logloss:0.00373
281s [61]	validation_0-logloss:0.00373
281s [62]	validation_0-logloss:0.00373
281s [63]	validation_0-logloss:0.00372
281s [64]	validation_0-logloss:0.00372
281s [65]	validation_0-logloss:0.00372
281s [66]	validation_0-logloss:0.00371
281s [67]	validation_0-logloss:0.00371
281s [68]	validation_0-logloss:0.00371
281s [69]	validation_0-logloss:0.00371
281s [70]	validation_0-logloss:0.00371
281s Total boosted rounds: 195
281s [0]	validation_0-logloss:0.43281
281s [1]	validation_0-logloss:0.30816
281s [2]	validation_0-logloss:0.22816
281s [3]	validation_0-logloss:0.17470
281s [4]	validation_0-logloss:0.13438
281s [5]	validation_0-logloss:0.10538
281s [6]	validation_0-logloss:0.08467
281s [7]	validation_0-logloss:0.06909
281s [8]	validation_0-logloss:0.05766
281s [9]	validation_0-logloss:0.04842
281s [10]	validation_0-logloss:0.04121
281s [11]	validation_0-logloss:0.03545
281s [12]	validation_0-logloss:0.03077
281s [13]	validation_0-logloss:0.02742
281s [14]	validation_0-logloss:0.02444
281s [15]	validation_0-logloss:0.02208
281s [16]	validation_0-logloss:0.01993
281s [17]	validation_0-logloss:0.01819
281s [18]	validation_0-logloss:0.01676
281s [19]	validation_0-logloss:0.01575
281s [20]	validation_0-logloss:0.01461
281s [21]	validation_0-logloss:0.01383
281s [22]	validation_0-logloss:0.01304
281s [23]	validation_0-logloss:0.01243
281s [24]	validation_0-logloss:0.01179
281s [25]	validation_0-logloss:0.01142
281s [26]	validation_0-logloss:0.01103
281s [27]	validation_0-logloss:0.01066
281s [28]	validation_0-logloss:0.01037
281s [29]	validation_0-logloss:0.00993
281s [30]	validation_0-logloss:0.00966
281s [31]	validation_0-logloss:0.00920
281s [32]	validation_0-logloss:0.00900
281s [33]	validation_0-logloss:0.00876
281s [34]	validation_0-logloss:0.00852
281s [35]	validation_0-logloss:0.00835
281s [36]	validation_0-logloss:0.00810
281s [37]	validation_0-logloss:0.00791
281s [38]	validation_0-logloss:0.00764
281s [39]	validation_0-logloss:0.00753
281s [40]	validation_0-logloss:0.00739
281s [41]	validation_0-logloss:0.00723
281s [42]	validation_0-logloss:0.00706
281s [43]	validation_0-logloss:0.00695
281s [44]	validation_0-logloss:0.00688
281s [45]	validation_0-logloss:0.00671
281s [46]	validation_0-logloss:0.00662
281s [47]	validation_0-logloss:0.00650
281s [48]	validation_0-logloss:0.00637
281s [49]	validation_0-logloss:0.00628
281s [50]	validation_0-logloss:0.00623
281s [51]	validation_0-logloss:0.00618
281s [52]	validation_0-logloss:0.00614
281s [53]	validation_0-logloss:0.00609
281s [54]	validation_0-logloss:0.00600
281s [55]	validation_0-logloss:0.00590
281s [56]	validation_0-logloss:0.00582
281s [57]	validation_0-logloss:0.00578
281s [58]	validation_0-logloss:0.00570
281s [59]	validation_0-logloss:0.00566
281s [60]	validation_0-logloss:0.00563
281s [61]	validation_0-logloss:0.00559
281s [62]	validation_0-logloss:0.00556
281s [63]	validation_0-logloss:0.00553
281s [64]	validation_0-logloss:0.00549
281s [65]	validation_0-logloss:0.00546
281s [66]	validation_0-logloss:0.00543
281s [67]	validation_0-logloss:0.00540
281s [68]	validation_0-logloss:0.00537
281s [69]	validation_0-logloss:0.00534
281s [70]	validation_0-logloss:0.00531
281s [71]	validation_0-logloss:0.00528
281s [72]	validation_0-logloss:0.00525
281s [73]	validation_0-logloss:0.00523
281s [74]	validation_0-logloss:0.00520
281s [75]	validation_0-logloss:0.00517
281s [76]	validation_0-logloss:0.00515
281s [77]	validation_0-logloss:0.00512
281s [78]	validation_0-logloss:0.00510
281s [79]	validation_0-logloss:0.00507
281s [80]	validation_0-logloss:0.00505
281s [81]	validation_0-logloss:0.00502
281s [82]	validation_0-logloss:0.00500
281s [83]	validation_0-logloss:0.00498
281s [84]	validation_0-logloss:0.00496
281s [85]	validation_0-logloss:0.00493
281s [86]	validation_0-logloss:0.00491
281s [87]	validation_0-logloss:0.00489
281s [88]	validation_0-logloss:0.00486
281s [89]	validation_0-logloss:0.00484
281s [90]	validation_0-logloss:0.00482
281s [91]	validation_0-logloss:0.00480
281s [92]	validation_0-logloss:0.00478
281s [93]	validation_0-logloss:0.00476
281s [94]	validation_0-logloss:0.00474
281s [95]	validation_0-logloss:0.00472
281s [96]	validation_0-logloss:0.00470
281s [97]	validation_0-logloss:0.00468
281s [98]	validation_0-logloss:0.00466
281s [99]	validation_0-logloss:0.00464
281s [100]	validation_0-logloss:0.00463
281s [101]	validation_0-logloss:0.00461
281s [102]	validation_0-logloss:0.00459
281s [103]	validation_0-logloss:0.00457
281s [104]	validation_0-logloss:0.00456
281s [105]	validation_0-logloss:0.00454
281s [106]	validation_0-logloss:0.00452
281s [107]	validation_0-logloss:0.00451
281s [108]	validation_0-logloss:0.00449
281s [109]	validation_0-logloss:0.00448
281s [110]	validation_0-logloss:0.00446
281s [111]	validation_0-logloss:0.00444
281s [112]	validation_0-logloss:0.00443
281s [113]	validation_0-logloss:0.00441
281s [114]	validation_0-logloss:0.00440
281s [115]	validation_0-logloss:0.00438
281s [116]	validation_0-logloss:0.00437
281s [117]	validation_0-logloss:0.00435
281s [118]	validation_0-logloss:0.00434
281s [119]	validation_0-logloss:0.00433
281s [120]	validation_0-logloss:0.00431
281s [121]	validation_0-logloss:0.00430
281s [122]	validation_0-logloss:0.00429
281s [123]	validation_0-logloss:0.00427
281s [124]	validation_0-logloss:0.00426
281s [125]	validation_0-logloss:0.00425
281s [126]	validation_0-logloss:0.00423
281s [127]	validation_0-logloss:0.00422
281s [128]	validation_0-logloss:0.00421
281s [129]	validation_0-logloss:0.00420
281s [130]	validation_0-logloss:0.00419
281s [131]	validation_0-logloss:0.00417
281s [132]	validation_0-logloss:0.00416
281s [133]	validation_0-logloss:0.00415
281s [134]	validation_0-logloss:0.00414
281s [135]	validation_0-logloss:0.00413
281s [136]	validation_0-logloss:0.00412
281s [137]	validation_0-logloss:0.00411
281s [138]	validation_0-logloss:0.00410
281s [139]	validation_0-logloss:0.00409
281s [140]	validation_0-logloss:0.00408
281s [141]	validation_0-logloss:0.00407
281s [142]	validation_0-logloss:0.00406
281s [143]	validation_0-logloss:0.00405
281s [144]	validation_0-logloss:0.00404
281s [145]	validation_0-logloss:0.00403
281s [146]	validation_0-logloss:0.00402
281s [147]	validation_0-logloss:0.00401
281s [148]	validation_0-logloss:0.00400
281s [149]	validation_0-logloss:0.00399
281s [150]	validation_0-logloss:0.00398
281s [151]	validation_0-logloss:0.00397
281s [152]	validation_0-logloss:0.00396
281s [153]	validation_0-logloss:0.00396
281s [154]	validation_0-logloss:0.00395
281s [155]	validation_0-logloss:0.00394
281s [156]	validation_0-logloss:0.00393
281s [157]	validation_0-logloss:0.00392
281s [158]	validation_0-logloss:0.00391
281s [159]	validation_0-logloss:0.00391
281s [160]	validation_0-logloss:0.00390
281s [161]	validation_0-logloss:0.00389
281s [162]	validation_0-logloss:0.00388
281s [163]	validation_0-logloss:0.00388
281s [164]	validation_0-logloss:0.00387
281s [165]	validation_0-logloss:0.00386
281s [166]	validation_0-logloss:0.00385
281s [167]	validation_0-logloss:0.00385
281s [168]	validation_0-logloss:0.00384
281s [169]	validation_0-logloss:0.00383
281s [170]	validation_0-logloss:0.00383
281s [171]	validation_0-logloss:0.00382
281s [172]	validation_0-logloss:0.00381
281s [173]	validation_0-logloss:0.00381
281s [174]	validation_0-logloss:0.00380
281s [175]	validation_0-logloss:0.00380
281s [176]	validation_0-logloss:0.00379
281s [177]	validation_0-logloss:0.00379
281s [178]	validation_0-logloss:0.00378
281s [179]	validation_0-logloss:0.00378
281s [180]	validation_0-logloss:0.00377
281s [181]	validation_0-logloss:0.00377
281s [182]	validation_0-logloss:0.00376
281s [183]	validation_0-logloss:0.00376
281s [184]	validation_0-logloss:0.00375
281s [185]	validation_0-logloss:0.00375
281s [186]	validation_0-logloss:0.00374
281s [187]	validation_0-logloss:0.00374
281s [188]	validation_0-logloss:0.00373
281s [189]	validation_0-logloss:0.00373
281s [190]	validation_0-logloss:0.00373
281s [191]	validation_0-logloss:0.00372
281s [192]	validation_0-logloss:0.00372
281s [193]	validation_0-logloss:0.00372
281s [194]	validation_0-logloss:0.00371
281s [195]	validation_0-logloss:0.00371
281s [196]	validation_0-logloss:0.00371
281s [197]	validation_0-logloss:0.00371
281s [198]	validation_0-logloss:0.00371
281s [199]	validation_0-logloss:0.00371
281s Total boosted rounds: 195
281s [0]	validation_0-logloss:0.43281
281s [1]	validation_0-logloss:0.30816
281s [2]	validation_0-logloss:0.22816
281s [3]	validation_0-logloss:0.17470
281s [4]	validation_0-logloss:0.13438
281s [5]	validation_0-logloss:0.10538
281s [6]	validation_0-logloss:0.08467
281s [7]	validation_0-logloss:0.06909
281s [8]	validation_0-logloss:0.05766
281s [9]	validation_0-logloss:0.04842
281s [10]	validation_0-logloss:0.04121
281s [11]	validation_0-logloss:0.03545
281s [12]	validation_0-logloss:0.03077
281s [13]	validation_0-logloss:0.02742
281s [14]	validation_0-logloss:0.02444
281s [15]	validation_0-logloss:0.02208
281s [16]	validation_0-logloss:0.01993
281s [17]	validation_0-logloss:0.01819
281s [18]	validation_0-logloss:0.01676
281s [19]	validation_0-logloss:0.01575
281s [20]	validation_0-logloss:0.01461
281s [21]	validation_0-logloss:0.01383
281s [22]	validation_0-logloss:0.01304
281s [23]	validation_0-logloss:0.01243
281s [24]	validation_0-logloss:0.01179
281s [25]	validation_0-logloss:0.01142
281s [26]	validation_0-logloss:0.01103
281s [27]	validation_0-logloss:0.01066
281s [28]	validation_0-logloss:0.01037
281s [29]	validation_0-logloss:0.00993
281s [30]	validation_0-logloss:0.00966
281s [31]	validation_0-logloss:0.00920
281s [32]	validation_0-logloss:0.00900
281s [33]	validation_0-logloss:0.00876
281s [34]	validation_0-logloss:0.00852
281s [35]	validation_0-logloss:0.00835
281s [36]	validation_0-logloss:0.00810
281s [37]	validation_0-logloss:0.00791
281s [38]	validation_0-logloss:0.00764
281s [39]	validation_0-logloss:0.00753
281s [40]	validation_0-logloss:0.00739
281s [41]	validation_0-logloss:0.00723
281s [42]	validation_0-logloss:0.00706
281s [43]	validation_0-logloss:0.00695
281s [44]	validation_0-logloss:0.00688
281s [45]	validation_0-logloss:0.00671
281s [46]	validation_0-logloss:0.00662
281s [47]	validation_0-logloss:0.00650
281s [48]	validation_0-logloss:0.00637
281s [49]	validation_0-logloss:0.00628
281s [50]	validation_0-logloss:0.00623
281s [51]	validation_0-logloss:0.00618
281s [52]	validation_0-logloss:0.00614
281s [53]	validation_0-logloss:0.00609
281s [54]	validation_0-logloss:0.00600
281s [55]	validation_0-logloss:0.00590
281s [56]	validation_0-logloss:0.00582
281s [57]	validation_0-logloss:0.00578
281s [58]	validation_0-logloss:0.00570
281s [59]	validation_0-logloss:0.00566
281s [60]	validation_0-logloss:0.00563
281s [61]	validation_0-logloss:0.00559
281s [62]	validation_0-logloss:0.00556
281s [63]	validation_0-logloss:0.00553
281s [64]	validation_0-logloss:0.00549
281s [65]	validation_0-logloss:0.00546
281s [66]	validation_0-logloss:0.00543
281s [67]	validation_0-logloss:0.00540
281s [68]	validation_0-logloss:0.00537
281s [69]	validation_0-logloss:0.00534
281s [70]	validation_0-logloss:0.00531
281s [71]	validation_0-logloss:0.00528
281s [72]	validation_0-logloss:0.00525
281s [73]	validation_0-logloss:0.00523
281s [74]	validation_0-logloss:0.00520
281s [75]	validation_0-logloss:0.00517
281s [76]	validation_0-logloss:0.00515
281s [77]	validation_0-logloss:0.00512
281s [78]	validation_0-logloss:0.00510
281s [79]	validation_0-logloss:0.00507
281s [80]	validation_0-logloss:0.00505
281s [81]	validation_0-logloss:0.00502
281s [82]	validation_0-logloss:0.00500
281s [83]	validation_0-logloss:0.00498
281s [84]	validation_0-logloss:0.00496
281s [85]	validation_0-logloss:0.00493
281s [86]	validation_0-logloss:0.00491
281s [87]	validation_0-logloss:0.00489
281s [88]	validation_0-logloss:0.00486
281s [89]	validation_0-logloss:0.00484
281s [90]	validation_0-logloss:0.00482
281s [91]	validation_0-logloss:0.00480
281s [92]	validation_0-logloss:0.00478
281s [93]	validation_0-logloss:0.00476
281s [94]	validation_0-logloss:0.00474
281s [95]	validation_0-logloss:0.00472
281s [96]	validation_0-logloss:0.00470
281s [97]	validation_0-logloss:0.00468
281s [98]	validation_0-logloss:0.00466
281s [99]	validation_0-logloss:0.00464
281s [100]	validation_0-logloss:0.00463
281s [101]	validation_0-logloss:0.00461
281s [102]	validation_0-logloss:0.00459
281s [103]	validation_0-logloss:0.00457
281s [104]	validation_0-logloss:0.00456
281s [105]	validation_0-logloss:0.00454
281s [106]	validation_0-logloss:0.00452
281s [107]	validation_0-logloss:0.00451
281s [108]	validation_0-logloss:0.00449
281s [109]	validation_0-logloss:0.00448
281s [110]	validation_0-logloss:0.00446
281s [111]	validation_0-logloss:0.00444
281s [112]	validation_0-logloss:0.00443
281s [113]	validation_0-logloss:0.00441
281s [114]	validation_0-logloss:0.00440
281s [115]	validation_0-logloss:0.00438
281s [116]	validation_0-logloss:0.00437
281s [117]	validation_0-logloss:0.00435
281s [118]	validation_0-logloss:0.00434
281s [119]	validation_0-logloss:0.00433
281s [120]	validation_0-logloss:0.00431
281s [121]	validation_0-logloss:0.00430
281s [122]	validation_0-logloss:0.00429
281s [123]	validation_0-logloss:0.00427
281s [124]	validation_0-logloss:0.00426
281s [125]	validation_0-logloss:0.00425
281s [126]	validation_0-logloss:0.00423
281s [127]	validation_0-logloss:0.00422
281s [0]	validation_0-logloss:0.00421
281s [1]	validation_0-logloss:0.00420
281s [2]	validation_0-logloss:0.00419
281s [3]	validation_0-logloss:0.00417
281s [4]	validation_0-logloss:0.00416
281s [5]	validation_0-logloss:0.00415
281s [6]	validation_0-logloss:0.00414
281s [7]	validation_0-logloss:0.00413
281s [8]	validation_0-logloss:0.00412
281s [9]	validation_0-logloss:0.00411
281s [10]	validation_0-logloss:0.00410
281s [11]	validation_0-logloss:0.00409
281s [12]	validation_0-logloss:0.00408
281s [13]	validation_0-logloss:0.00407
281s [14]	validation_0-logloss:0.00406
281s [15]	validation_0-logloss:0.00405
281s [16]	validation_0-logloss:0.00404
281s [17]	validation_0-logloss:0.00403
281s [18]	validation_0-logloss:0.00402
281s [19]	validation_0-logloss:0.00401
281s [20]	validation_0-logloss:0.00400
281s [21]	validation_0-logloss:0.00399
281s [22]	validation_0-logloss:0.00398
281s [23]	validation_0-logloss:0.00397
281s [24]	validation_0-logloss:0.00396
281s [25]	validation_0-logloss:0.00396
281s [26]	validation_0-logloss:0.00395
281s [27]	validation_0-logloss:0.00394
281s [28]	validation_0-logloss:0.00393
281s [29]	validation_0-logloss:0.00392
281s [30]	validation_0-logloss:0.00391
281s [31]	validation_0-logloss:0.00391
281s [32]	validation_0-logloss:0.00390
281s [33]	validation_0-logloss:0.00389
281s [34]	validation_0-logloss:0.00388
281s [35]	validation_0-logloss:0.00388
281s [36]	validation_0-logloss:0.00387
281s [37]	validation_0-logloss:0.00386
281s [38]	validation_0-logloss:0.00385
281s [39]	validation_0-logloss:0.00385
281s [40]	validation_0-logloss:0.00384
281s [41]	validation_0-logloss:0.00383
281s [42]	validation_0-logloss:0.00383
281s [43]	validation_0-logloss:0.00382
281s [44]	validation_0-logloss:0.00381
281s [45]	validation_0-logloss:0.00381
281s [46]	validation_0-logloss:0.00380
281s [47]	validation_0-logloss:0.00380
281s [48]	validation_0-logloss:0.00379
281s [49]	validation_0-logloss:0.00379
281s [50]	validation_0-logloss:0.00378
281s [51]	validation_0-logloss:0.00378
281s [52]	validation_0-logloss:0.00377
281s [53]	validation_0-logloss:0.00377
281s [54]	validation_0-logloss:0.00376
281s [55]	validation_0-logloss:0.00376
281s [56]	validation_0-logloss:0.00375
281s [57]	validation_0-logloss:0.00375
281s [58]	validation_0-logloss:0.00374
281s [59]	validation_0-logloss:0.00374
281s [60]	validation_0-logloss:0.00373
281s [61]	validation_0-logloss:0.00373
281s [62]	validation_0-logloss:0.00373
281s [63]	validation_0-logloss:0.00372
281s [64]	validation_0-logloss:0.00372
281s [65]	validation_0-logloss:0.00372
281s [66]	validation_0-logloss:0.00371
281s [67]	validation_0-logloss:0.00371
281s [68]	validation_0-logloss:0.00371
281s [69]	validation_0-logloss:0.00371
281s [70]	validation_0-logloss:0.00371
281s Total boosted rounds: 195
281s [0]	validation_0-logloss:0.43281
281s [1]	validation_0-logloss:0.30816
281s [2]	validation_0-logloss:0.22816
281s [3]	validation_0-logloss:0.17470
281s [4]	validation_0-logloss:0.13438
281s [5]	validation_0-logloss:0.10538
281s [6]	validation_0-logloss:0.08467
281s [7]	validation_0-logloss:0.06909
281s [8]	validation_0-logloss:0.05766
281s [9]	validation_0-logloss:0.04842
281s [10]	validation_0-logloss:0.04121
281s [11]	validation_0-logloss:0.03545
281s [12]	validation_0-logloss:0.03077
281s [13]	validation_0-logloss:0.02742
281s [14]	validation_0-logloss:0.02444
281s [15]	validation_0-logloss:0.02208
281s [16]	validation_0-logloss:0.01993
281s [17]	validation_0-logloss:0.01819
281s [18]	validation_0-logloss:0.01676
281s [19]	validation_0-logloss:0.01575
281s [20]	validation_0-logloss:0.01461
282s [21]	validation_0-logloss:0.01383
282s [22]	validation_0-logloss:0.01304
282s [23]	validation_0-logloss:0.01243
282s [24]	validation_0-logloss:0.01179
282s [25]	validation_0-logloss:0.01142
282s [26]	validation_0-logloss:0.01103
282s [27]	validation_0-logloss:0.01066
282s [28]	validation_0-logloss:0.01037
282s [29]	validation_0-logloss:0.00993
282s [30]	validation_0-logloss:0.00966
282s [31]	validation_0-logloss:0.00920
282s [32]	validation_0-logloss:0.00900
282s [33]	validation_0-logloss:0.00876
282s [34]	validation_0-logloss:0.00852
282s [35]	validation_0-logloss:0.00835
282s [36]	validation_0-logloss:0.00810
282s [37]	validation_0-logloss:0.00791
282s [38]	validation_0-logloss:0.00764
282s [39]	validation_0-logloss:0.00753
282s [40]	validation_0-logloss:0.00739
282s [41]	validation_0-logloss:0.00723
282s [42]	validation_0-logloss:0.00706
282s [43]	validation_0-logloss:0.00695
282s [44]	validation_0-logloss:0.00688
282s [45]	validation_0-logloss:0.00671
282s [46]	validation_0-logloss:0.00662
282s [47]	validation_0-logloss:0.00650
282s [48]	validation_0-logloss:0.00637
282s [49]	validation_0-logloss:0.00628
282s [50]	validation_0-logloss:0.00623
282s [51]	validation_0-logloss:0.00618
282s [52]	validation_0-logloss:0.00614
282s [53]	validation_0-logloss:0.00609
282s [54]	validation_0-logloss:0.00600
282s [55]	validation_0-logloss:0.00590
282s [56]	validation_0-logloss:0.00582
282s [57]	validation_0-logloss:0.00578
282s [58]	validation_0-logloss:0.00570
282s [59]	validation_0-logloss:0.00566
282s [60]	validation_0-logloss:0.00563
282s [61]	validation_0-logloss:0.00559
282s [62]	validation_0-logloss:0.00556
282s [63]	validation_0-logloss:0.00553
282s [64]	validation_0-logloss:0.00549
282s [65]	validation_0-logloss:0.00546
282s [66]	validation_0-logloss:0.00543
282s [67]	validation_0-logloss:0.00540
282s [68]	validation_0-logloss:0.00537
282s [69]	validation_0-logloss:0.00534
282s [70]	validation_0-logloss:0.00531
282s [71]	validation_0-logloss:0.00528
282s [72]	validation_0-logloss:0.00525
282s [73]	validation_0-logloss:0.00523
282s [74]	validation_0-logloss:0.00520
282s [75]	validation_0-logloss:0.00517
282s [76]	validation_0-logloss:0.00515
282s [77]	validation_0-logloss:0.00512
282s [78]	validation_0-logloss:0.00510
282s [79]	validation_0-logloss:0.00507
282s [80]	validation_0-logloss:0.00505
282s [81]	validation_0-logloss:0.00502
282s [82]	validation_0-logloss:0.00500
282s [83]	validation_0-logloss:0.00498
282s [84]	validation_0-logloss:0.00496
282s [85]	validation_0-logloss:0.00493
282s [86]	validation_0-logloss:0.00491
282s [87]	validation_0-logloss:0.00489
282s [88]	validation_0-logloss:0.00486
282s [89]	validation_0-logloss:0.00484
282s [90]	validation_0-logloss:0.00482
282s [91]	validation_0-logloss:0.00480
282s [92]	validation_0-logloss:0.00478
282s [93]	validation_0-logloss:0.00476
282s [94]	validation_0-logloss:0.00474
282s [95]	validation_0-logloss:0.00472
282s [96]	validation_0-logloss:0.00470
282s [97]	validation_0-logloss:0.00468
282s [98]	validation_0-logloss:0.00466
282s [99]	validation_0-logloss:0.00464
282s [100]	validation_0-logloss:0.00463
282s [101]	validation_0-logloss:0.00461
282s [102]	validation_0-logloss:0.00459
282s [103]	validation_0-logloss:0.00457
282s [104]	validation_0-logloss:0.00456
282s [105]	validation_0-logloss:0.00454
282s [106]	validation_0-logloss:0.00452
282s [107]	validation_0-logloss:0.00451
282s [108]	validation_0-logloss:0.00449
282s [109]	validation_0-logloss:0.00448
282s [110]	validation_0-logloss:0.00446
282s [111]	validation_0-logloss:0.00444
282s [112]	validation_0-logloss:0.00443
282s [113]	validation_0-logloss:0.00441
282s [114]	validation_0-logloss:0.00440
282s [115]	validation_0-logloss:0.00438
282s [116]	validation_0-logloss:0.00437
282s [117]	validation_0-logloss:0.00435
282s [118]	validation_0-logloss:0.00434
282s [119]	validation_0-logloss:0.00433
282s [120]	validation_0-logloss:0.00431
282s [121]	validation_0-logloss:0.00430
282s [122]	validation_0-logloss:0.00429
282s [123]	validation_0-logloss:0.00427
282s [124]	validation_0-logloss:0.00426
282s [125]	validation_0-logloss:0.00425
282s [126]	validation_0-logloss:0.00423
282s [127]	validation_0-logloss:0.00422
282s Total boosted rounds: 128
282s [0]	validation_0-logloss:0.43281
282s [1]	validation_0-logloss:0.30816
282s [2]	validation_0-logloss:0.22816
282s [3]	validation_0-logloss:0.17470
282s [4]	validation_0-logloss:0.13438
282s [5]	validation_0-logloss:0.10538
282s [6]	validation_0-logloss:0.08467
282s [7]	validation_0-logloss:0.06909
282s [8]	validation_0-logloss:0.05766
282s [9]	validation_0-logloss:0.04842
282s [10]	validation_0-logloss:0.04121
282s [11]	validation_0-logloss:0.03545
282s [12]	validation_0-logloss:0.03077
282s [13]	validation_0-logloss:0.02742
282s [14]	validation_0-logloss:0.02444
282s [15]	validation_0-logloss:0.02208
282s [16]	validation_0-logloss:0.01993
282s [17]	validation_0-logloss:0.01819
282s [18]	validation_0-logloss:0.01676
282s [19]	validation_0-logloss:0.01575
282s [20]	validation_0-logloss:0.01461
282s [21]	validation_0-logloss:0.01383
282s [22]	validation_0-logloss:0.01304
282s [23]	validation_0-logloss:0.01243
282s [24]	validation_0-logloss:0.01179
282s [25]	validation_0-logloss:0.01142
282s [26]	validation_0-logloss:0.01103
282s [27]	validation_0-logloss:0.01066
282s [28]	validation_0-logloss:0.01037
282s [29]	validation_0-logloss:0.00993
282s [30]	validation_0-logloss:0.00966
282s [31]	validation_0-logloss:0.00920
282s [0]	validation_0-logloss:0.00900
282s [1]	validation_0-logloss:0.00876
282s [2]	validation_0-logloss:0.00852
282s [3]	validation_0-logloss:0.00835
282s [4]	validation_0-logloss:0.00810
282s [5]	validation_0-logloss:0.00791
282s [6]	validation_0-logloss:0.00764
282s [7]	validation_0-logloss:0.00753
282s [8]	validation_0-logloss:0.00739
282s [9]	validation_0-logloss:0.00723
282s [10]	validation_0-logloss:0.00706
282s [11]	validation_0-logloss:0.00695
282s [12]	validation_0-logloss:0.00688
282s [13]	validation_0-logloss:0.00671
282s [14]	validation_0-logloss:0.00662
282s [15]	validation_0-logloss:0.00650
282s [16]	validation_0-logloss:0.00637
282s [17]	validation_0-logloss:0.00628
282s [18]	validation_0-logloss:0.00623
282s [19]	validation_0-logloss:0.00618
282s [20]	validation_0-logloss:0.00614
282s [21]	validation_0-logloss:0.00609
282s [22]	validation_0-logloss:0.00600
282s [23]	validation_0-logloss:0.00590
282s [24]	validation_0-logloss:0.00582
282s [25]	validation_0-logloss:0.00578
282s [26]	validation_0-logloss:0.00570
282s [27]	validation_0-logloss:0.00566
282s [28]	validation_0-logloss:0.00563
282s [29]	validation_0-logloss:0.00559
282s [30]	validation_0-logloss:0.00556
282s [31]	validation_0-logloss:0.00553
282s [32]	validation_0-logloss:0.00549
282s [33]	validation_0-logloss:0.00546
282s [34]	validation_0-logloss:0.00543
282s [35]	validation_0-logloss:0.00540
282s [36]	validation_0-logloss:0.00537
282s [37]	validation_0-logloss:0.00534
282s [38]	validation_0-logloss:0.00531
282s [39]	validation_0-logloss:0.00528
282s [40]	validation_0-logloss:0.00525
282s [41]	validation_0-logloss:0.00523
282s [42]	validation_0-logloss:0.00520
282s [43]	validation_0-logloss:0.00517
282s [44]	validation_0-logloss:0.00515
282s [45]	validation_0-logloss:0.00512
282s [46]	validation_0-logloss:0.00510
282s [47]	validation_0-logloss:0.00507
282s [48]	validation_0-logloss:0.00505
282s [49]	validation_0-logloss:0.00502
282s [50]	validation_0-logloss:0.00500
282s [51]	validation_0-logloss:0.00498
282s [52]	validation_0-logloss:0.00496
282s [53]	validation_0-logloss:0.00493
282s [54]	validation_0-logloss:0.00491
282s [55]	validation_0-logloss:0.00489
282s [56]	validation_0-logloss:0.00486
282s [57]	validation_0-logloss:0.00484
282s [58]	validation_0-logloss:0.00482
282s [59]	validation_0-logloss:0.00480
282s [60]	validation_0-logloss:0.00478
282s [61]	validation_0-logloss:0.00476
282s [62]	validation_0-logloss:0.00474
282s [63]	validation_0-logloss:0.00472
282s [64]	validation_0-logloss:0.00470
282s [65]	validation_0-logloss:0.00468
282s [66]	validation_0-logloss:0.00466
282s [67]	validation_0-logloss:0.00464
282s [68]	validation_0-logloss:0.00463
282s [69]	validation_0-logloss:0.00461
282s [70]	validation_0-logloss:0.00459
282s [71]	validation_0-logloss:0.00457
282s [72]	validation_0-logloss:0.00456
282s [73]	validation_0-logloss:0.00454
282s [74]	validation_0-logloss:0.00452
282s [75]	validation_0-logloss:0.00451
282s [76]	validation_0-logloss:0.00449
282s [77]	validation_0-logloss:0.00448
282s [78]	validation_0-logloss:0.00446
282s [79]	validation_0-logloss:0.00444
282s [80]	validation_0-logloss:0.00443
282s [81]	validation_0-logloss:0.00441
282s [82]	validation_0-logloss:0.00440
282s [83]	validation_0-logloss:0.00438
282s [84]	validation_0-logloss:0.00437
282s [85]	validation_0-logloss:0.00435
282s [86]	validation_0-logloss:0.00434
282s [87]	validation_0-logloss:0.00433
282s [88]	validation_0-logloss:0.00431
282s [89]	validation_0-logloss:0.00430
282s [90]	validation_0-logloss:0.00429
282s [91]	validation_0-logloss:0.00427
282s [92]	validation_0-logloss:0.00426
282s [93]	validation_0-logloss:0.00425
282s [94]	validation_0-logloss:0.00423
282s [95]	validation_0-logloss:0.00422
282s Total boosted rounds: 128
282s [0]	validation_0-logloss:0.43281
282s [1]	validation_0-logloss:0.30816
282s [2]	validation_0-logloss:0.22816
282s [3]	validation_0-logloss:0.17470
282s [4]	validation_0-logloss:0.13438
282s [5]	validation_0-logloss:0.10538
282s [6]	validation_0-logloss:0.08467
282s [7]	validation_0-logloss:0.06909
282s [8]	validation_0-logloss:0.05766
282s [9]	validation_0-logloss:0.04842
282s [10]	validation_0-logloss:0.04121
282s [11]	validation_0-logloss:0.03545
282s [12]	validation_0-logloss:0.03077
282s [13]	validation_0-logloss:0.02742
282s [14]	validation_0-logloss:0.02444
282s [15]	validation_0-logloss:0.02208
282s [16]	validation_0-logloss:0.01993
282s [17]	validation_0-logloss:0.01819
282s [18]	validation_0-logloss:0.01676
282s [19]	validation_0-logloss:0.01575
282s [20]	validation_0-logloss:0.01461
282s [21]	validation_0-logloss:0.01383
282s [22]	validation_0-logloss:0.01304
282s [23]	validation_0-logloss:0.01243
282s [24]	validation_0-logloss:0.01179
282s [25]	validation_0-logloss:0.01142
282s [26]	validation_0-logloss:0.01103
282s [27]	validation_0-logloss:0.01066
282s [28]	validation_0-logloss:0.01037
282s [29]	validation_0-logloss:0.00993
282s [30]	validation_0-logloss:0.00966
282s [31]	validation_0-logloss:0.00920
282s [32]	validation_0-logloss:0.00900
282s [33]	validation_0-logloss:0.00876
282s [34]	validation_0-logloss:0.00852
282s [35]	validation_0-logloss:0.00835
282s [36]	validation_0-logloss:0.00810
282s [37]	validation_0-logloss:0.00791
282s [38]	validation_0-logloss:0.00764
282s [39]	validation_0-logloss:0.00753
282s [40]	validation_0-logloss:0.00739
282s [41]	validation_0-logloss:0.00723
282s [42]	validation_0-logloss:0.00706
282s [43]	validation_0-logloss:0.00695
282s [44]	validation_0-logloss:0.00688
282s [45]	validation_0-logloss:0.00671
282s [46]	validation_0-logloss:0.00662
282s [47]	validation_0-logloss:0.00650
282s [48]	validation_0-logloss:0.00637
282s [49]	validation_0-logloss:0.00628
282s [50]	validation_0-logloss:0.00623
282s [51]	validation_0-logloss:0.00618
282s [52]	validation_0-logloss:0.00614
282s [53]	validation_0-logloss:0.00609
282s [54]	validation_0-logloss:0.00600
282s [55]	validation_0-logloss:0.00590
282s [56]	validation_0-logloss:0.00582
282s [57]	validation_0-logloss:0.00578
282s [58]	validation_0-logloss:0.00570
282s [59]	validation_0-logloss:0.00566
282s [60]	validation_0-logloss:0.00563
282s [61]	validation_0-logloss:0.00559
282s [62]	validation_0-logloss:0.00556
282s [63]	validation_0-logloss:0.00553
282s [64]	validation_0-logloss:0.00549
282s [65]	validation_0-logloss:0.00546
282s [66]	validation_0-logloss:0.00543
282s [67]	validation_0-logloss:0.00540
282s [68]	validation_0-logloss:0.00537
282s [69]	validation_0-logloss:0.00534
282s [70]	validation_0-logloss:0.00531
282s [71]	validation_0-logloss:0.00528
282s [72]	validation_0-logloss:0.00525
282s [73]	validation_0-logloss:0.00523
282s [74]	validation_0-logloss:0.00520
282s [75]	validation_0-logloss:0.00517
282s [76]	validation_0-logloss:0.00515
282s [77]	validation_0-logloss:0.00512
282s [78]	validation_0-logloss:0.00510
282s [79]	validation_0-logloss:0.00507
282s [80]	validation_0-logloss:0.00505
282s [81]	validation_0-logloss:0.00502
282s [82]	validation_0-logloss:0.00500
282s [83]	validation_0-logloss:0.00498
282s [84]	validation_0-logloss:0.00496
282s [85]	validation_0-logloss:0.00493
282s [86]	validation_0-logloss:0.00491
282s [87]	validation_0-logloss:0.00489
282s [88]	validation_0-logloss:0.00486
282s [89]	validation_0-logloss:0.00484
282s [90]	validation_0-logloss:0.00482
282s [91]	validation_0-logloss:0.00480
282s [92]	validation_0-logloss:0.00478
282s [93]	validation_0-logloss:0.00476
282s [94]	validation_0-logloss:0.00474
282s [95]	validation_0-logloss:0.00472
282s [96]	validation_0-logloss:0.00470
282s [97]	validation_0-logloss:0.00468
282s [98]	validation_0-logloss:0.00466
282s [99]	validation_0-logloss:0.00464
282s [100]	validation_0-logloss:0.00463
282s [101]	validation_0-logloss:0.00461
282s [102]	validation_0-logloss:0.00459
282s [103]	validation_0-logloss:0.00457
282s [104]	validation_0-logloss:0.00456
282s [105]	validation_0-logloss:0.00454
282s [106]	validation_0-logloss:0.00452
282s [107]	validation_0-logloss:0.00451
282s [108]	validation_0-logloss:0.00449
282s [109]	validation_0-logloss:0.00448
282s [110]	validation_0-logloss:0.00446
282s [111]	validation_0-logloss:0.00444
282s [112]	validation_0-logloss:0.00443
282s [113]	validation_0-logloss:0.00441
282s [114]	validation_0-logloss:0.00440
282s [115]	validation_0-logloss:0.00438
282s [116]	validation_0-logloss:0.00437
282s [117]	validation_0-logloss:0.00435
282s [118]	validation_0-logloss:0.00434
282s [119]	validation_0-logloss:0.00433
282s [120]	validation_0-logloss:0.00431
282s [121]	validation_0-logloss:0.00430
282s [122]	validation_0-logloss:0.00429
282s [123]	validation_0-logloss:0.00427
282s [124]	validation_0-logloss:0.00426
282s [125]	validation_0-logloss:0.00425
282s [126]	validation_0-logloss:0.00423
282s [127]	validation_0-logloss:0.00422
282s Total boosted rounds: 128
282s [0]	validation_0-logloss:0.43281
282s [1]	validation_0-logloss:0.30816
282s [2]	validation_0-logloss:0.22816
282s [3]	validation_0-logloss:0.17470
282s [4]	validation_0-logloss:0.13438
282s [5]	validation_0-logloss:0.10538
282s [6]	validation_0-logloss:0.08467
282s [7]	validation_0-logloss:0.06909
282s [8]	validation_0-logloss:0.05766
282s [9]	validation_0-logloss:0.04842
282s [10]	validation_0-logloss:0.04121
282s [11]	validation_0-logloss:0.03545
282s [12]	validation_0-logloss:0.03077
282s [13]	validation_0-logloss:0.02742
282s [14]	validation_0-logloss:0.02444
282s [15]	validation_0-logloss:0.02208
282s [16]	validation_0-logloss:0.01993
282s [17]	validation_0-logloss:0.01819
282s [18]	validation_0-logloss:0.01676
282s [19]	validation_0-logloss:0.01575
282s [20]	validation_0-logloss:0.01461
282s [21]	validation_0-logloss:0.01383
282s [22]	validation_0-logloss:0.01304
282s [23]	validation_0-logloss:0.01243
282s [24]	validation_0-logloss:0.01179
282s [25]	validation_0-logloss:0.01142
282s [26]	validation_0-logloss:0.01103
282s [27]	validation_0-logloss:0.01066
282s [28]	validation_0-logloss:0.01037
282s [29]	validation_0-logloss:0.00993
282s [30]	validation_0-logloss:0.00966
282s [31]	validation_0-logloss:0.00920
282s [0]	validation_0-logloss:0.00900
282s [1]	validation_0-logloss:0.00876
282s [2]	validation_0-logloss:0.00852
282s [3]	validation_0-logloss:0.00835
282s [4]	validation_0-logloss:0.00810
282s [5]	validation_0-logloss:0.00791
282s [6]	validation_0-logloss:0.00764
282s [7]	validation_0-logloss:0.00753
282s [8]	validation_0-logloss:0.00739
282s [9]	validation_0-logloss:0.00723
282s [10]	validation_0-logloss:0.00706
282s [11]	validation_0-logloss:0.00695
282s [12]	validation_0-logloss:0.00688
282s [13]	validation_0-logloss:0.00671
282s [14]	validation_0-logloss:0.00662
282s [15]	validation_0-logloss:0.00650
282s [16]	validation_0-logloss:0.00637
282s [17]	validation_0-logloss:0.00628
282s [18]	validation_0-logloss:0.00623
282s [19]	validation_0-logloss:0.00618
282s [20]	validation_0-logloss:0.00614
282s [21]	validation_0-logloss:0.00609
282s [22]	validation_0-logloss:0.00600
282s [23]	validation_0-logloss:0.00590
282s [24]	validation_0-logloss:0.00582
282s [25]	validation_0-logloss:0.00578
282s [26]	validation_0-logloss:0.00570
282s [27]	validation_0-logloss:0.00566
282s [28]	validation_0-logloss:0.00563
282s [29]	validation_0-logloss:0.00559
282s [30]	validation_0-logloss:0.00556
282s [31]	validation_0-logloss:0.00553
282s [32]	validation_0-logloss:0.00549
282s [33]	validation_0-logloss:0.00546
282s [34]	validation_0-logloss:0.00543
282s [35]	validation_0-logloss:0.00540
282s [36]	validation_0-logloss:0.00537
282s [37]	validation_0-logloss:0.00534
282s [38]	validation_0-logloss:0.00531
282s [39]	validation_0-logloss:0.00528
282s [40]	validation_0-logloss:0.00525
282s [41]	validation_0-logloss:0.00523
282s [42]	validation_0-logloss:0.00520
282s [43]	validation_0-logloss:0.00517
282s [44]	validation_0-logloss:0.00515
282s [45]	validation_0-logloss:0.00512
282s [46]	validation_0-logloss:0.00510
282s [47]	validation_0-logloss:0.00507
282s [48]	validation_0-logloss:0.00505
282s [49]	validation_0-logloss:0.00502
282s [50]	validation_0-logloss:0.00500
282s [51]	validation_0-logloss:0.00498
282s [52]	validation_0-logloss:0.00496
282s [53]	validation_0-logloss:0.00493
282s [54]	validation_0-logloss:0.00491
282s [55]	validation_0-logloss:0.00489
282s [56]	validation_0-logloss:0.00486
282s [57]	validation_0-logloss:0.00484
282s [58]	validation_0-logloss:0.00482
282s [59]	validation_0-logloss:0.00480
282s [60]	validation_0-logloss:0.00478
282s [61]	validation_0-logloss:0.00476
282s [62]	validation_0-logloss:0.00474
282s [63]	validation_0-logloss:0.00472
282s [64]	validation_0-logloss:0.00470
282s [65]	validation_0-logloss:0.00468
282s [66]	validation_0-logloss:0.00466
282s [67]	validation_0-logloss:0.00464
282s [68]	validation_0-logloss:0.00463
282s [69]	validation_0-logloss:0.00461
282s [70]	validation_0-logloss:0.00459
282s [71]	validation_0-logloss:0.00457
282s [72]	validation_0-logloss:0.00456
282s [73]	validation_0-logloss:0.00454
282s [74]	validation_0-logloss:0.00452
282s [75]	validation_0-logloss:0.00451
282s [76]	validation_0-logloss:0.00449
282s [77]	validation_0-logloss:0.00448
282s [78]	validation_0-logloss:0.00446
282s [79]	validation_0-logloss:0.00444
282s [80]	validation_0-logloss:0.00443
282s [81]	validation_0-logloss:0.00441
282s [82]	validation_0-logloss:0.00440
282s [83]	validation_0-logloss:0.00438
282s [84]	validation_0-logloss:0.00437
282s [85]	validation_0-logloss:0.00435
282s [86]	validation_0-logloss:0.00434
282s [87]	validation_0-logloss:0.00433
282s [88]	validation_0-logloss:0.00431
282s [89]	validation_0-logloss:0.00430
282s [90]	validation_0-logloss:0.00429
282s [91]	validation_0-logloss:0.00427
282s [92]	validation_0-logloss:0.00426
282s [93]	validation_0-logloss:0.00425
282s [94]	validation_0-logloss:0.00423
282s [95]	validation_0-logloss:0.00422
282s Total boosted rounds: 128
283s ==========================================
283s Running case cross_validation.py...
284s running cross validation
284s [0]	train-error:0.05067+0.00920	test-error:0.05573+0.01589
285s [1]	train-error:0.02130+0.00206	test-error:0.02119+0.00365
285s running cross validation, disable standard deviation display
285s [0]	train-error:0.05067	test-error:0.05573
285s [1]	train-error:0.02130	test-error:0.02119
285s [2]	train-error:0.00994	test-error:0.00998
285s [3]	train-error:0.01413	test-error:0.01443
285s [4]	train-error:0.00599	test-error:0.00630
285s [5]	train-error:0.00203	test-error:0.00169
285s [6]	train-error:0.00123	test-error:0.00123
285s [7]	train-error:0.00123	test-error:0.00123
285s [8]	train-error:0.00092	test-error:0.00123
285s /usr/lib/python3/dist-packages/xgboost/training.py:38: UserWarning: `feval` is deprecated, use `custom_metric` instead.  They have different behavior when custom objective is also used.See https://xgboost.readthedocs.io/en/latest/tutorials/custom_metric_obj.html for details on the `custom_metric`.
285s   warnings.warn(
285s    train-error-mean  train-error-std  test-error-mean  test-error-std
285s 0          0.050668         0.009201         0.055732        0.015889
285s 1          0.021303         0.002055         0.021188        0.003653
285s 2          0.009942         0.006076         0.009979        0.004828
285s 3          0.014126         0.001706         0.014433        0.003517
285s 4          0.005988         0.001878         0.006295        0.003123
285s 5          0.002034         0.001469         0.001689        0.000574
285s 6          0.001228         0.000260         0.001228        0.001041
285s running cross validation, with preprocessing function
285s running cross validation, with customized loss function
286s ==========================================
286s Running case custom_rmsle.py...
286s /tmp/autopkgtest.fqUgNt/build.EqA/src/demo/guide-python/custom_rmsle.py:139: SyntaxWarning: invalid escape sequence '\s'
286s   :math:`\sqrt{\frac{1}{N}[log(pred + 1) - log(label + 1)]^2}`
288s Squared Error
288s [0]	dtrain-rmse:682.95908	dtest-rmse:745.95555
288s [1]	dtrain-rmse:627.66199	dtest-rmse:751.49583
288s [2]	dtrain-rmse:596.74396	dtest-rmse:766.33054
288s [3]	dtrain-rmse:555.92371	dtest-rmse:776.92703
288s [4]	dtrain-rmse:519.58613	dtest-rmse:789.74145
288s [5]	dtrain-rmse:501.26007	dtest-rmse:805.22881
288s [6]	dtrain-rmse:453.81757	dtest-rmse:810.70817
288s [7]	dtrain-rmse:423.51474	dtest-rmse:822.61798
288s [8]	dtrain-rmse:383.34479	dtest-rmse:826.43243
288s [9]	dtrain-rmse:371.08179	dtest-rmse:827.23674
288s [10]	dtrain-rmse:353.11776	dtest-rmse:828.84174
288s [11]	dtrain-rmse:316.42149	dtest-rmse:832.98904
288s [12]	dtrain-rmse:300.24359	dtest-rmse:834.90637
288s [13]	dtrain-rmse:285.81935	dtest-rmse:836.55001
288s [14]	dtrain-rmse:278.47432	dtest-rmse:838.29965
288s [15]	dtrain-rmse:266.08310	dtest-rmse:840.16158
288s [16]	dtrain-rmse:261.48875	dtest-rmse:841.45332
288s [17]	dtrain-rmse:253.15765	dtest-rmse:841.96773
288s [18]	dtrain-rmse:246.41335	dtest-rmse:842.26433
288s [19]	dtrain-rmse:242.90377	dtest-rmse:843.24280
288s Finished Squared Error in: 0.09464859962463379 
288s 
288s Squared Log Error
288s [0]	dtrain-rmsle:1.31939	dtest-rmsle:1.26056
288s [1]	dtrain-rmsle:1.22093	dtest-rmsle:1.16061
288s [2]	dtrain-rmsle:1.13670	dtest-rmsle:1.07549
288s [3]	dtrain-rmsle:1.06691	dtest-rmsle:1.00568
288s [4]	dtrain-rmsle:1.01079	dtest-rmsle:0.95190
288s [5]	dtrain-rmsle:0.96709	dtest-rmsle:0.91206
288s [6]	dtrain-rmsle:0.93453	dtest-rmsle:0.88458
288s [7]	dtrain-rmsle:0.90925	dtest-rmsle:0.86580
288s [8]	dtrain-rmsle:0.89139	dtest-rmsle:0.85326
288s [9]	dtrain-rmsle:0.87620	dtest-rmsle:0.84621
288s [10]	dtrain-rmsle:0.86538	dtest-rmsle:0.84136
288s [11]	dtrain-rmsle:0.85715	dtest-rmsle:0.83849
288s [12]	dtrain-rmsle:0.84866	dtest-rmsle:0.83767
288s [13]	dtrain-rmsle:0.84230	dtest-rmsle:0.83693
288s [14]	dtrain-rmsle:0.83639	dtest-rmsle:0.83785
288s [15]	dtrain-rmsle:0.83076	dtest-rmsle:0.83853
288s [16]	dtrain-rmsle:0.82671	dtest-rmsle:0.83887
288s [17]	dtrain-rmsle:0.82297	dtest-rmsle:0.83883
288s [18]	dtrain-rmsle:0.81919	dtest-rmsle:0.83945
288s [19]	dtrain-rmsle:0.81638	dtest-rmsle:0.83981
288s Finished Squared Log Error in: 0.07914948463439941
288s [0]	dtrain-PyRMSLE:1.37154	dtest-PyRMSLE:1.31491
288s [1]	dtrain-PyRMSLE:1.26642	dtest-PyRMSLE:1.20792
288s [2]	dtrain-PyRMSLE:1.17525	dtest-PyRMSLE:1.11539
288s [3]	dtrain-PyRMSLE:1.09848	dtest-PyRMSLE:1.03800
288s [4]	dtrain-PyRMSLE:1.03565	dtest-PyRMSLE:0.97673
288s [5]	dtrain-PyRMSLE:0.98595	dtest-PyRMSLE:0.93063
288s [6]	dtrain-PyRMSLE:0.94774	dtest-PyRMSLE:0.89723
288s [7]	dtrain-PyRMSLE:0.91977	dtest-PyRMSLE:0.87448
288s [8]	dtrain-PyRMSLE:0.89796	dtest-PyRMSLE:0.85932
288s [9]	dtrain-PyRMSLE:0.88141	dtest-PyRMSLE:0.85028
288s [10]	dtrain-PyRMSLE:0.86816	dtest-PyRMSLE:0.84450
288s [11]	dtrain-PyRMSLE:0.85991	dtest-PyRMSLE:0.84015
288s [12]	dtrain-PyRMSLE:0.85120	dtest-PyRMSLE:0.83900
288s [13]	dtrain-PyRMSLE:0.84384	dtest-PyRMSLE:0.83775
288s [14]	dtrain-PyRMSLE:0.83741	dtest-PyRMSLE:0.83732
288s [15]	dtrain-PyRMSLE:0.83253	dtest-PyRMSLE:0.83800
288s [16]	dtrain-PyRMSLE:0.82842	dtest-PyRMSLE:0.83827
288s [17]	dtrain-PyRMSLE:0.82535	dtest-PyRMSLE:0.83844
288s [18]	dtrain-PyRMSLE:0.82169	dtest-PyRMSLE:0.83953
288s [19]	dtrain-PyRMSLE:0.81857	dtest-PyRMSLE:0.84046
289s ==========================================
289s Running case custom_softmax.py...
291s /tmp/autopkgtest.fqUgNt/build.EqA/src/demo/guide-python/custom_softmax.py:76: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
291s   grad[r, c] = g
291s [0]	train-PyMError:0.14000
291s [1]	train-PyMError:0.00000
291s [2]	train-PyMError:0.01000
291s [3]	train-PyMError:0.00000
291s [4]	train-PyMError:0.00000
292s [5]	train-PyMError:0.00000
292s [6]	train-PyMError:0.00000
292s [7]	train-PyMError:0.00000
292s [8]	train-PyMError:0.00000
292s [9]	train-PyMError:0.00000
292s [0]	train-merror:0.14000
292s [1]	train-merror:0.00000
292s [2]	train-merror:0.01000
292s [3]	train-merror:0.00000
292s [4]	train-merror:0.00000
293s [5]	train-merror:0.00000
293s [6]	train-merror:0.00000
293s [7]	train-merror:0.00000
293s [8]	train-merror:0.00000
293s [9]	train-merror:0.00000
293s ==========================================
293s Running case evals_result.py...
295s /usr/lib/python3/dist-packages/xgboost/core.py:723: FutureWarning: Pass `evals` as keyword args.
295s   warnings.warn(msg, FutureWarning)
295s [0]	eval-logloss:0.47977	eval-error:0.04283	train-logloss:0.48196	train-error:0.04652
295s [1]	eval-logloss:0.35740	eval-error:0.04283	train-logloss:0.35919	train-error:0.04652
295s Access logloss metric directly from evals_result:
295s [0.4797663698279288, 0.35739665886839306]
295s 
295s Access metrics through a loop:
295s - eval
295s    - logloss
295s       - [0.4797663698279288, 0.35739665886839306]
295s    - error
295s       - [0.04283054003724395, 0.04283054003724395]
295s - train
295s    - logloss
295s       - [0.4819583435789261, 0.35919429156594646]
295s    - error
295s       - [0.04652233993551359, 0.04652233993551359]
295s 
295s Access complete dictionary:
295s {'eval': OrderedDict({'logloss': [0.4797663698279288, 0.35739665886839306], 'error': [0.04283054003724395, 0.04283054003724395]}), 'train': OrderedDict({'logloss': [0.4819583435789261, 0.35919429156594646], 'error': [0.04652233993551359, 0.04652233993551359]})}
295s ==========================================
295s Running case external_memory.py...
297s [0]	Train-rmse:170.67905
297s [1]	Train-rmse:166.88130
297s [2]	Train-rmse:163.67251
297s [3]	Train-rmse:160.83024
297s [4]	Train-rmse:158.26351
297s [5]	Train-rmse:155.91569
297s [6]	Train-rmse:153.74380
297s [7]	Train-rmse:151.74583
297s [8]	Train-rmse:149.92400
297s [9]	Train-rmse:148.14658
298s ==========================================
298s Running case feature_weights.py...
300s [0]	d-rmse:1.00430
300s [1]	d-rmse:0.99638
300s [2]	d-rmse:0.98161
300s [3]	d-rmse:0.97086
300s [4]	d-rmse:0.96269
300s [5]	d-rmse:0.94829
300s [6]	d-rmse:0.93914
300s [7]	d-rmse:0.93187
300s [8]	d-rmse:0.92274
300s [9]	d-rmse:0.91749
300s ==========================================
300s Skip case gamma_regression.py...
300s ==========================================
300s Running case generalized_linear_model.py...
302s /usr/lib/python3/dist-packages/xgboost/core.py:723: FutureWarning: Pass `evals` as keyword args.
302s   warnings.warn(msg, FutureWarning)
302s [0]	eval-logloss:0.57104	train-logloss:0.56837
302s [1]	eval-logloss:0.52971	train-logloss:0.52607
302s [2]	eval-logloss:0.51418	train-logloss:0.51017
302s [3]	eval-logloss:0.50805	train-logloss:0.50390
302s error=0.119181
302s ==========================================
302s Running case individual_trees.py...
304s ==========================================
304s Skip case learning_to_rank.py...
304s ==========================================
304s Running case multioutput_regression.py...
308s [0]	validation_0-rmse:0.29417
308s [1]	validation_0-rmse:0.26360
308s [2]	validation_0-rmse:0.23619
308s [3]	validation_0-rmse:0.22068
308s [4]	validation_0-rmse:0.20681
308s [5]	validation_0-rmse:0.19295
308s [6]	validation_0-rmse:0.17849
308s [7]	validation_0-rmse:0.16562
308s [8]	validation_0-rmse:0.15492
308s [9]	validation_0-rmse:0.14493
308s [10]	validation_0-rmse:0.13892
308s [11]	validation_0-rmse:0.13172
308s [12]	validation_0-rmse:0.12253
308s [13]	validation_0-rmse:0.11744
308s [14]	validation_0-rmse:0.10981
308s [15]	validation_0-rmse:0.10176
308s [16]	validation_0-rmse:0.09476
308s [17]	validation_0-rmse:0.08947
308s [18]	validation_0-rmse:0.08399
308s [19]	validation_0-rmse:0.07952
308s [20]	validation_0-rmse:0.07442
308s [21]	validation_0-rmse:0.07048
308s [22]	validation_0-rmse:0.06749
308s [23]	validation_0-rmse:0.06505
308s [24]	validation_0-rmse:0.06060
308s [25]	validation_0-rmse:0.05737
308s [26]	validation_0-rmse:0.05539
308s [27]	validation_0-rmse:0.05326
308s [28]	validation_0-rmse:0.05026
308s [29]	validation_0-rmse:0.04692
308s [30]	validation_0-rmse:0.04501
308s [31]	validation_0-rmse:0.04175
308s [32]	validation_0-rmse:0.03970
308s [33]	validation_0-rmse:0.03683
308s [34]	validation_0-rmse:0.03430
308s [35]	validation_0-rmse:0.03219
308s [36]	validation_0-rmse:0.03058
308s [37]	validation_0-rmse:0.02914
308s [38]	validation_0-rmse:0.02778
308s [39]	validation_0-rmse:0.02611
308s [40]	validation_0-rmse:0.02504
308s [41]	validation_0-rmse:0.02322
308s [42]	validation_0-rmse:0.02212
308s [43]	validation_0-rmse:0.02129
308s [44]	validation_0-rmse:0.01992
308s [45]	validation_0-rmse:0.01930
308s [46]	validation_0-rmse:0.01864
308s [47]	validation_0-rmse:0.01744
308s [48]	validation_0-rmse:0.01618
308s [49]	validation_0-rmse:0.01521
308s [50]	validation_0-rmse:0.01428
308s [51]	validation_0-rmse:0.01346
308s [52]	validation_0-rmse:0.01276
308s [53]	validation_0-rmse:0.01209
308s [54]	validation_0-rmse:0.01154
308s [55]	validation_0-rmse:0.01094
308s [56]	validation_0-rmse:0.01023
308s [57]	validation_0-rmse:0.00979
308s [58]	validation_0-rmse:0.00934
308s [59]	validation_0-rmse:0.00879
308s [60]	validation_0-rmse:0.00845
308s [61]	validation_0-rmse:0.00822
308s [62]	validation_0-rmse:0.00790
308s [63]	validation_0-rmse:0.00742
308s [64]	validation_0-rmse:0.00711
308s [65]	validation_0-rmse:0.00682
308s [66]	validation_0-rmse:0.00644
308s [67]	validation_0-rmse:0.00615
308s [68]	validation_0-rmse:0.00577
308s [69]	validation_0-rmse:0.00553
308s [70]	validation_0-rmse:0.00514
308s [71]	validation_0-rmse:0.00493
308s [72]	validation_0-rmse:0.00468
308s [73]	validation_0-rmse:0.00443
308s [74]	validation_0-rmse:0.00426
308s [75]	validation_0-rmse:0.00389
308s [76]	validation_0-rmse:0.00362
308s [77]	validation_0-rmse:0.00340
308s [78]	validation_0-rmse:0.00323
308s [79]	validation_0-rmse:0.00303
308s [80]	validation_0-rmse:0.00288
308s [81]	validation_0-rmse:0.00275
308s [82]	validation_0-rmse:0.00264
308s [83]	validation_0-rmse:0.00253
308s [84]	validation_0-rmse:0.00240
308s [85]	validation_0-rmse:0.00230
308s [86]	validation_0-rmse:0.00219
308s [87]	validation_0-rmse:0.00208
308s [88]	validation_0-rmse:0.00198
308s [89]	validation_0-rmse:0.00191
308s [90]	validation_0-rmse:0.00183
308s [91]	validation_0-rmse:0.00173
308s [92]	validation_0-rmse:0.00169
308s [93]	validation_0-rmse:0.00161
308s [94]	validation_0-rmse:0.00154
308s [95]	validation_0-rmse:0.00148
308s [96]	validation_0-rmse:0.00145
308s [97]	validation_0-rmse:0.00141
308s [98]	validation_0-rmse:0.00138
308s [99]	validation_0-rmse:0.00134
308s [100]	validation_0-rmse:0.00131
308s [101]	validation_0-rmse:0.00128
308s [102]	validation_0-rmse:0.00122
308s [103]	validation_0-rmse:0.00121
308s [104]	validation_0-rmse:0.00119
308s [105]	validation_0-rmse:0.00117
308s [106]	validation_0-rmse:0.00113
308s [107]	validation_0-rmse:0.00111
308s [108]	validation_0-rmse:0.00108
308s [109]	validation_0-rmse:0.00104
308s [110]	validation_0-rmse:0.00104
308s [111]	validation_0-rmse:0.00102
308s [112]	validation_0-rmse:0.00100
308s [113]	validation_0-rmse:0.00100
308s [114]	validation_0-rmse:0.00098
308s [115]	validation_0-rmse:0.00098
308s [116]	validation_0-rmse:0.00097
308s [117]	validation_0-rmse:0.00097
308s [118]	validation_0-rmse:0.00097
308s [119]	validation_0-rmse:0.00097
308s [120]	validation_0-rmse:0.00097
308s [121]	validation_0-rmse:0.00096
308s [122]	validation_0-rmse:0.00096
308s [123]	validation_0-rmse:0.00095
308s [124]	validation_0-rmse:0.00093
308s [125]	validation_0-rmse:0.00093
308s [126]	validation_0-rmse:0.00093
308s [127]	validation_0-rmse:0.00092
308s [0]	validation_0-rmse:0.29633
308s [1]	validation_0-rmse:0.27038
308s [2]	validation_0-rmse:0.24670
308s [3]	validation_0-rmse:0.22485
308s [4]	validation_0-rmse:0.20795
308s [5]	validation_0-rmse:0.19109
308s [6]	validation_0-rmse:0.17936
308s [7]	validation_0-rmse:0.17053
308s [8]	validation_0-rmse:0.16198
308s [9]	validation_0-rmse:0.15406
308s [10]	validation_0-rmse:0.14510
308s [11]	validation_0-rmse:0.13641
308s [12]	validation_0-rmse:0.12550
308s [13]	validation_0-rmse:0.11761
308s [14]	validation_0-rmse:0.11132
308s [15]	validation_0-rmse:0.10186
308s [16]	validation_0-rmse:0.09376
308s [17]	validation_0-rmse:0.08897
308s [18]	validation_0-rmse:0.08226
308s [19]	validation_0-rmse:0.07742
308s [20]	validation_0-rmse:0.07209
308s [21]	validation_0-rmse:0.06959
308s [22]	validation_0-rmse:0.06703
308s [23]	validation_0-rmse:0.06274
308s [24]	validation_0-rmse:0.05932
308s [25]	validation_0-rmse:0.05540
308s [26]	validation_0-rmse:0.05157
308s [27]	validation_0-rmse:0.04830
308s [28]	validation_0-rmse:0.04540
308s [29]	validation_0-rmse:0.04313
308s [30]	validation_0-rmse:0.04098
308s [31]	validation_0-rmse:0.03869
308s [32]	validation_0-rmse:0.03728
308s [33]	validation_0-rmse:0.03536
308s [34]	validation_0-rmse:0.03372
308s [35]	validation_0-rmse:0.03235
308s [36]	validation_0-rmse:0.03093
308s [37]	validation_0-rmse:0.02889
308s [38]	validation_0-rmse:0.02686
308s [39]	validation_0-rmse:0.02547
308s [40]	validation_0-rmse:0.02372
308s [41]	validation_0-rmse:0.02209
308s [42]	validation_0-rmse:0.02130
308s [43]	validation_0-rmse:0.02008
308s [44]	validation_0-rmse:0.01901
308s [45]	validation_0-rmse:0.01851
308s [46]	validation_0-rmse:0.01714
308s [47]	validation_0-rmse:0.01644
308s [48]	validation_0-rmse:0.01585
308s [49]	validation_0-rmse:0.01493
308s [50]	validation_0-rmse:0.01370
308s [51]	validation_0-rmse:0.01309
308s [52]	validation_0-rmse:0.01257
308s [53]	validation_0-rmse:0.01193
308s [54]	validation_0-rmse:0.01136
308s [55]	validation_0-rmse:0.01080
308s [56]	validation_0-rmse:0.01010
308s [57]	validation_0-rmse:0.00947
308s [58]	validation_0-rmse:0.00871
308s [59]	validation_0-rmse:0.00818
308s [60]	validation_0-rmse:0.00766
308s [61]	validation_0-rmse:0.00737
308s [62]	validation_0-rmse:0.00695
308s [63]	validation_0-rmse:0.00658
308s [64]	validation_0-rmse:0.00616
308s [65]	validation_0-rmse:0.00595
308s [66]	validation_0-rmse:0.00566
308s [67]	validation_0-rmse:0.00526
308s [68]	validation_0-rmse:0.00487
308s [69]	validation_0-rmse:0.00469
308s [70]	validation_0-rmse:0.00446
308s [71]	validation_0-rmse:0.00422
308s [72]	validation_0-rmse:0.00403
308s [73]	validation_0-rmse:0.00381
308s [74]	validation_0-rmse:0.00360
308s [75]	validation_0-rmse:0.00346
308s [76]	validation_0-rmse:0.00330
308s [77]	validation_0-rmse:0.00312
308s [78]	validation_0-rmse:0.00296
308s [79]	validation_0-rmse:0.00284
308s [80]	validation_0-rmse:0.00275
308s [81]	validation_0-rmse:0.00264
308s [82]	validation_0-rmse:0.00251
308s [83]	validation_0-rmse:0.00242
308s [84]	validation_0-rmse:0.00231
308s [85]	validation_0-rmse:0.00222
308s [86]	validation_0-rmse:0.00212
308s [87]	validation_0-rmse:0.00203
308s [88]	validation_0-rmse:0.00192
308s [89]	validation_0-rmse:0.00181
308s [90]	validation_0-rmse:0.00174
308s [91]	validation_0-rmse:0.00168
308s [92]	validation_0-rmse:0.00159
308s [93]	validation_0-rmse:0.00153
308s [94]	validation_0-rmse:0.00147
308s [95]	validation_0-rmse:0.00142
308s [96]	validation_0-rmse:0.00138
308s [97]	validation_0-rmse:0.00130
308s [98]	validation_0-rmse:0.00123
308s [99]	validation_0-rmse:0.00118
308s [100]	validation_0-rmse:0.00114
308s [101]	validation_0-rmse:0.00112
308s [102]	validation_0-rmse:0.00110
308s [103]	validation_0-rmse:0.00106
308s [104]	validation_0-rmse:0.00103
308s [105]	validation_0-rmse:0.00102
308s [106]	validation_0-rmse:0.00099
308s [107]	validation_0-rmse:0.00096
308s [108]	validation_0-rmse:0.00094
308s [109]	validation_0-rmse:0.00093
308s [110]	validation_0-rmse:0.00091
308s [111]	validation_0-rmse:0.00087
308s [112]	validation_0-rmse:0.00086
308s [113]	validation_0-rmse:0.00084
308s [114]	validation_0-rmse:0.00084
308s [115]	validation_0-rmse:0.00083
308s [116]	validation_0-rmse:0.00083
308s [117]	validation_0-rmse:0.00082
308s [118]	validation_0-rmse:0.00082
308s [119]	validation_0-rmse:0.00081
308s [120]	validation_0-rmse:0.00080
308s [121]	validation_0-rmse:0.00079
308s [122]	validation_0-rmse:0.00079
308s [123]	validation_0-rmse:0.00078
308s [124]	validation_0-rmse:0.00078
308s [125]	validation_0-rmse:0.00077
308s [126]	validation_0-rmse:0.00077
308s [127]	validation_0-rmse:0.00076
308s [0]	Train-rmse:0.28597	Train-PyRMSE:4.04424
308s [1]	Train-rmse:0.25494	Train-PyRMSE:3.60534
308s [2]	Train-rmse:0.23359	Train-PyRMSE:3.30341
308s [3]	Train-rmse:0.21640	Train-PyRMSE:3.06038
308s [4]	Train-rmse:0.20574	Train-PyRMSE:2.90962
308s [5]	Train-rmse:0.19311	Train-PyRMSE:2.73098
308s [6]	Train-rmse:0.18435	Train-PyRMSE:2.60710
308s [7]	Train-rmse:0.17502	Train-PyRMSE:2.47516
308s [8]	Train-rmse:0.16830	Train-PyRMSE:2.38017
308s [9]	Train-rmse:0.15957	Train-PyRMSE:2.25667
308s [10]	Train-rmse:0.15430	Train-PyRMSE:2.18211
308s [11]	Train-rmse:0.14604	Train-PyRMSE:2.06533
308s [12]	Train-rmse:0.13629	Train-PyRMSE:1.92740
308s [13]	Train-rmse:0.13249	Train-PyRMSE:1.87376
308s [14]	Train-rmse:0.12557	Train-PyRMSE:1.77588
308s [15]	Train-rmse:0.12198	Train-PyRMSE:1.72505
308s [16]	Train-rmse:0.11972	Train-PyRMSE:1.69314
308s [17]	Train-rmse:0.11345	Train-PyRMSE:1.60444
308s [18]	Train-rmse:0.10926	Train-PyRMSE:1.54524
308s [19]	Train-rmse:0.10367	Train-PyRMSE:1.46616
308s [20]	Train-rmse:0.09938	Train-PyRMSE:1.40550
308s [21]	Train-rmse:0.09543	Train-PyRMSE:1.34963
308s [22]	Train-rmse:0.09302	Train-PyRMSE:1.31552
308s [23]	Train-rmse:0.08848	Train-PyRMSE:1.25132
308s [24]	Train-rmse:0.08575	Train-PyRMSE:1.21274
308s [25]	Train-rmse:0.08280	Train-PyRMSE:1.17092
308s [26]	Train-rmse:0.07694	Train-PyRMSE:1.08803
308s [27]	Train-rmse:0.07375	Train-PyRMSE:1.04299
308s [28]	Train-rmse:0.07137	Train-PyRMSE:1.00927
308s [29]	Train-rmse:0.06737	Train-PyRMSE:0.95281
308s [30]	Train-rmse:0.06433	Train-PyRMSE:0.90978
308s [31]	Train-rmse:0.06239	Train-PyRMSE:0.88235
308s [32]	Train-rmse:0.06093	Train-PyRMSE:0.86164
308s [33]	Train-rmse:0.05800	Train-PyRMSE:0.82031
308s [34]	Train-rmse:0.05568	Train-PyRMSE:0.78745
308s [35]	Train-rmse:0.05430	Train-PyRMSE:0.76797
308s [36]	Train-rmse:0.05124	Train-PyRMSE:0.72468
308s [37]	Train-rmse:0.04849	Train-PyRMSE:0.68580
308s [38]	Train-rmse:0.04754	Train-PyRMSE:0.67231
308s [39]	Train-rmse:0.04704	Train-PyRMSE:0.66519
308s [40]	Train-rmse:0.04449	Train-PyRMSE:0.62916
308s [41]	Train-rmse:0.04374	Train-PyRMSE:0.61865
308s [42]	Train-rmse:0.04281	Train-PyRMSE:0.60545
308s [43]	Train-rmse:0.04101	Train-PyRMSE:0.58000
308s [44]	Train-rmse:0.03921	Train-PyRMSE:0.55448
308s [45]	Train-rmse:0.03761	Train-PyRMSE:0.53186
308s [46]	Train-rmse:0.03628	Train-PyRMSE:0.51314
308s [47]	Train-rmse:0.03566	Train-PyRMSE:0.50431
308s [48]	Train-rmse:0.03379	Train-PyRMSE:0.47782
308s [49]	Train-rmse:0.03265	Train-PyRMSE:0.46180
308s [50]	Train-rmse:0.03208	Train-PyRMSE:0.45373
308s [51]	Train-rmse:0.03132	Train-PyRMSE:0.44294
308s [52]	Train-rmse:0.03024	Train-PyRMSE:0.42768
308s [53]	Train-rmse:0.02897	Train-PyRMSE:0.40968
308s [54]	Train-rmse:0.02838	Train-PyRMSE:0.40136
308s [55]	Train-rmse:0.02777	Train-PyRMSE:0.39273
308s [56]	Train-rmse:0.02668	Train-PyRMSE:0.37727
308s [57]	Train-rmse:0.02579	Train-PyRMSE:0.36475
308s [58]	Train-rmse:0.02436	Train-PyRMSE:0.34444
308s [59]	Train-rmse:0.02411	Train-PyRMSE:0.34092
308s [60]	Train-rmse:0.02344	Train-PyRMSE:0.33144
308s [61]	Train-rmse:0.02296	Train-PyRMSE:0.32477
308s [62]	Train-rmse:0.02203	Train-PyRMSE:0.31151
308s [63]	Train-rmse:0.02109	Train-PyRMSE:0.29828
308s [64]	Train-rmse:0.02058	Train-PyRMSE:0.29102
308s [65]	Train-rmse:0.02017	Train-PyRMSE:0.28528
308s [66]	Train-rmse:0.01945	Train-PyRMSE:0.27500
308s [67]	Train-rmse:0.01861	Train-PyRMSE:0.26320
308s [68]	Train-rmse:0.01835	Train-PyRMSE:0.25955
308s [69]	Train-rmse:0.01763	Train-PyRMSE:0.24935
308s [70]	Train-rmse:0.01697	Train-PyRMSE:0.24001
308s [71]	Train-rmse:0.01633	Train-PyRMSE:0.23098
308s [72]	Train-rmse:0.01582	Train-PyRMSE:0.22368
308s [73]	Train-rmse:0.01562	Train-PyRMSE:0.22096
308s [74]	Train-rmse:0.01507	Train-PyRMSE:0.21311
308s [75]	Train-rmse:0.01488	Train-PyRMSE:0.21037
308s [76]	Train-rmse:0.01417	Train-PyRMSE:0.20036
308s [77]	Train-rmse:0.01362	Train-PyRMSE:0.19265
308s [78]	Train-rmse:0.01314	Train-PyRMSE:0.18588
308s [79]	Train-rmse:0.01263	Train-PyRMSE:0.17868
308s [80]	Train-rmse:0.01246	Train-PyRMSE:0.17623
308s [81]	Train-rmse:0.01228	Train-PyRMSE:0.17369
309s [82]	Train-rmse:0.01171	Train-PyRMSE:0.16556
309s [83]	Train-rmse:0.01120	Train-PyRMSE:0.15845
309s [84]	Train-rmse:0.01081	Train-PyRMSE:0.15289
309s [85]	Train-rmse:0.01031	Train-PyRMSE:0.14579
309s [86]	Train-rmse:0.00992	Train-PyRMSE:0.14032
309s [87]	Train-rmse:0.00976	Train-PyRMSE:0.13809
309s [88]	Train-rmse:0.00950	Train-PyRMSE:0.13438
309s [89]	Train-rmse:0.00914	Train-PyRMSE:0.12930
309s [90]	Train-rmse:0.00878	Train-PyRMSE:0.12417
309s [91]	Train-rmse:0.00845	Train-PyRMSE:0.11946
309s [92]	Train-rmse:0.00833	Train-PyRMSE:0.11779
309s [93]	Train-rmse:0.00816	Train-PyRMSE:0.11542
309s [94]	Train-rmse:0.00786	Train-PyRMSE:0.11115
309s [95]	Train-rmse:0.00751	Train-PyRMSE:0.10622
309s [96]	Train-rmse:0.00742	Train-PyRMSE:0.10500
309s [97]	Train-rmse:0.00718	Train-PyRMSE:0.10148
309s [98]	Train-rmse:0.00707	Train-PyRMSE:0.10001
309s [99]	Train-rmse:0.00685	Train-PyRMSE:0.09681
309s [100]	Train-rmse:0.00676	Train-PyRMSE:0.09558
309s [101]	Train-rmse:0.00654	Train-PyRMSE:0.09255
309s [102]	Train-rmse:0.00628	Train-PyRMSE:0.08888
309s [103]	Train-rmse:0.00601	Train-PyRMSE:0.08495
309s [104]	Train-rmse:0.00583	Train-PyRMSE:0.08240
309s [105]	Train-rmse:0.00576	Train-PyRMSE:0.08150
309s [106]	Train-rmse:0.00568	Train-PyRMSE:0.08027
309s [107]	Train-rmse:0.00542	Train-PyRMSE:0.07665
309s [108]	Train-rmse:0.00521	Train-PyRMSE:0.07373
309s [109]	Train-rmse:0.00502	Train-PyRMSE:0.07100
309s [110]	Train-rmse:0.00486	Train-PyRMSE:0.06869
309s [111]	Train-rmse:0.00468	Train-PyRMSE:0.06612
309s [112]	Train-rmse:0.00452	Train-PyRMSE:0.06399
309s [113]	Train-rmse:0.00447	Train-PyRMSE:0.06324
309s [114]	Train-rmse:0.00429	Train-PyRMSE:0.06062
309s [115]	Train-rmse:0.00414	Train-PyRMSE:0.05856
309s [116]	Train-rmse:0.00403	Train-PyRMSE:0.05697
309s [117]	Train-rmse:0.00389	Train-PyRMSE:0.05498
309s [118]	Train-rmse:0.00377	Train-PyRMSE:0.05330
309s [119]	Train-rmse:0.00371	Train-PyRMSE:0.05251
309s [120]	Train-rmse:0.00358	Train-PyRMSE:0.05058
309s [121]	Train-rmse:0.00349	Train-PyRMSE:0.04940
309s [122]	Train-rmse:0.00336	Train-PyRMSE:0.04751
309s [123]	Train-rmse:0.00332	Train-PyRMSE:0.04702
309s [124]	Train-rmse:0.00324	Train-PyRMSE:0.04584
309s [125]	Train-rmse:0.00321	Train-PyRMSE:0.04542
309s [126]	Train-rmse:0.00318	Train-PyRMSE:0.04502
309s [127]	Train-rmse:0.00308	Train-PyRMSE:0.04355
309s [0]	Train-rmse:0.29790	Train-PyRMSE:4.21300
309s [1]	Train-rmse:0.26995	Train-PyRMSE:3.81773
309s [2]	Train-rmse:0.24596	Train-PyRMSE:3.47845
309s [3]	Train-rmse:0.22962	Train-PyRMSE:3.24727
309s [4]	Train-rmse:0.22042	Train-PyRMSE:3.11716
309s [5]	Train-rmse:0.20740	Train-PyRMSE:2.93305
309s [6]	Train-rmse:0.20148	Train-PyRMSE:2.84940
309s [7]	Train-rmse:0.19043	Train-PyRMSE:2.69310
309s [8]	Train-rmse:0.18596	Train-PyRMSE:2.62991
309s [9]	Train-rmse:0.17844	Train-PyRMSE:2.52354
309s [10]	Train-rmse:0.17484	Train-PyRMSE:2.47255
309s [11]	Train-rmse:0.15904	Train-PyRMSE:2.24910
309s [12]	Train-rmse:0.15243	Train-PyRMSE:2.15566
309s [13]	Train-rmse:0.14346	Train-PyRMSE:2.02886
309s [14]	Train-rmse:0.13921	Train-PyRMSE:1.96873
309s [15]	Train-rmse:0.13760	Train-PyRMSE:1.94597
309s [16]	Train-rmse:0.13004	Train-PyRMSE:1.83909
309s [17]	Train-rmse:0.12588	Train-PyRMSE:1.78025
309s [18]	Train-rmse:0.12472	Train-PyRMSE:1.76382
309s [19]	Train-rmse:0.11921	Train-PyRMSE:1.68592
309s [20]	Train-rmse:0.11146	Train-PyRMSE:1.57621
309s [21]	Train-rmse:0.10750	Train-PyRMSE:1.52031
309s [22]	Train-rmse:0.10276	Train-PyRMSE:1.45326
309s [23]	Train-rmse:0.10194	Train-PyRMSE:1.44162
309s [24]	Train-rmse:0.09842	Train-PyRMSE:1.39186
309s [25]	Train-rmse:0.09715	Train-PyRMSE:1.37398
309s [26]	Train-rmse:0.09312	Train-PyRMSE:1.31692
309s [27]	Train-rmse:0.09226	Train-PyRMSE:1.30482
309s [28]	Train-rmse:0.08662	Train-PyRMSE:1.22503
309s [29]	Train-rmse:0.08231	Train-PyRMSE:1.16407
309s [30]	Train-rmse:0.08159	Train-PyRMSE:1.15381
309s [31]	Train-rmse:0.07851	Train-PyRMSE:1.11031
309s [32]	Train-rmse:0.07481	Train-PyRMSE:1.05796
309s [33]	Train-rmse:0.07150	Train-PyRMSE:1.01120
309s [34]	Train-rmse:0.07080	Train-PyRMSE:1.00132
309s [35]	Train-rmse:0.06830	Train-PyRMSE:0.96591
309s [36]	Train-rmse:0.06769	Train-PyRMSE:0.95733
309s [37]	Train-rmse:0.06484	Train-PyRMSE:0.91694
309s [38]	Train-rmse:0.06165	Train-PyRMSE:0.87181
309s [39]	Train-rmse:0.05937	Train-PyRMSE:0.83965
309s [40]	Train-rmse:0.05873	Train-PyRMSE:0.83051
309s [41]	Train-rmse:0.05667	Train-PyRMSE:0.80140
309s [42]	Train-rmse:0.05596	Train-PyRMSE:0.79141
309s [43]	Train-rmse:0.05416	Train-PyRMSE:0.76589
309s [44]	Train-rmse:0.05299	Train-PyRMSE:0.74934
309s [45]	Train-rmse:0.05052	Train-PyRMSE:0.71453
310s [46]	Train-rmse:0.04922	Train-PyRMSE:0.69609
310s [47]	Train-rmse:0.04883	Train-PyRMSE:0.69062
310s [48]	Train-rmse:0.04610	Train-PyRMSE:0.65199
310s [49]	Train-rmse:0.04417	Train-PyRMSE:0.62469
310s [50]	Train-rmse:0.04190	Train-PyRMSE:0.59254
310s [51]	Train-rmse:0.04114	Train-PyRMSE:0.58181
310s [52]	Train-rmse:0.03957	Train-PyRMSE:0.55954
310s [53]	Train-rmse:0.03922	Train-PyRMSE:0.55469
310s [54]	Train-rmse:0.03852	Train-PyRMSE:0.54478
310s [55]	Train-rmse:0.03717	Train-PyRMSE:0.52562
310s [56]	Train-rmse:0.03584	Train-PyRMSE:0.50680
310s [57]	Train-rmse:0.03429	Train-PyRMSE:0.48498
310s [58]	Train-rmse:0.03400	Train-PyRMSE:0.48083
310s [59]	Train-rmse:0.03295	Train-PyRMSE:0.46597
310s [60]	Train-rmse:0.03237	Train-PyRMSE:0.45775
310s [61]	Train-rmse:0.03091	Train-PyRMSE:0.43707
310s [62]	Train-rmse:0.02998	Train-PyRMSE:0.42399
310s [63]	Train-rmse:0.02849	Train-PyRMSE:0.40286
310s [64]	Train-rmse:0.02729	Train-PyRMSE:0.38595
310s [65]	Train-rmse:0.02692	Train-PyRMSE:0.38069
310s [66]	Train-rmse:0.02618	Train-PyRMSE:0.37018
310s [67]	Train-rmse:0.02588	Train-PyRMSE:0.36600
310s [68]	Train-rmse:0.02491	Train-PyRMSE:0.35229
310s [69]	Train-rmse:0.02428	Train-PyRMSE:0.34344
310s [70]	Train-rmse:0.02398	Train-PyRMSE:0.33907
310s [71]	Train-rmse:0.02309	Train-PyRMSE:0.32650
310s [72]	Train-rmse:0.02219	Train-PyRMSE:0.31381
310s [73]	Train-rmse:0.02094	Train-PyRMSE:0.29616
310s [74]	Train-rmse:0.02079	Train-PyRMSE:0.29398
310s [75]	Train-rmse:0.02028	Train-PyRMSE:0.28685
310s [76]	Train-rmse:0.01931	Train-PyRMSE:0.27311
310s [77]	Train-rmse:0.01919	Train-PyRMSE:0.27140
310s [78]	Train-rmse:0.01862	Train-PyRMSE:0.26336
310s [79]	Train-rmse:0.01743	Train-PyRMSE:0.24652
310s [80]	Train-rmse:0.01699	Train-PyRMSE:0.24033
310s [81]	Train-rmse:0.01644	Train-PyRMSE:0.23256
310s [82]	Train-rmse:0.01565	Train-PyRMSE:0.22127
310s [83]	Train-rmse:0.01526	Train-PyRMSE:0.21582
310s [84]	Train-rmse:0.01503	Train-PyRMSE:0.21258
310s [85]	Train-rmse:0.01450	Train-PyRMSE:0.20508
310s [86]	Train-rmse:0.01410	Train-PyRMSE:0.19936
311s [87]	Train-rmse:0.01349	Train-PyRMSE:0.19080
311s [88]	Train-rmse:0.01288	Train-PyRMSE:0.18211
311s [89]	Train-rmse:0.01278	Train-PyRMSE:0.18071
311s [90]	Train-rmse:0.01220	Train-PyRMSE:0.17252
311s [91]	Train-rmse:0.01179	Train-PyRMSE:0.16679
311s [92]	Train-rmse:0.01166	Train-PyRMSE:0.16490
311s [93]	Train-rmse:0.01132	Train-PyRMSE:0.16008
311s [94]	Train-rmse:0.01088	Train-PyRMSE:0.15388
311s [95]	Train-rmse:0.01060	Train-PyRMSE:0.14993
311s [96]	Train-rmse:0.01006	Train-PyRMSE:0.14229
311s [97]	Train-rmse:0.00998	Train-PyRMSE:0.14109
311s [98]	Train-rmse:0.00954	Train-PyRMSE:0.13496
311s [99]	Train-rmse:0.00948	Train-PyRMSE:0.13406
311s [100]	Train-rmse:0.00926	Train-PyRMSE:0.13098
311s [101]	Train-rmse:0.00901	Train-PyRMSE:0.12747
311s [102]	Train-rmse:0.00885	Train-PyRMSE:0.12510
311s [103]	Train-rmse:0.00847	Train-PyRMSE:0.11979
311s [104]	Train-rmse:0.00833	Train-PyRMSE:0.11784
311s [105]	Train-rmse:0.00791	Train-PyRMSE:0.11187
311s [106]	Train-rmse:0.00787	Train-PyRMSE:0.11125
311s [107]	Train-rmse:0.00755	Train-PyRMSE:0.10682
311s [108]	Train-rmse:0.00724	Train-PyRMSE:0.10245
311s [109]	Train-rmse:0.00705	Train-PyRMSE:0.09976
311s [110]	Train-rmse:0.00683	Train-PyRMSE:0.09662
311s [111]	Train-rmse:0.00656	Train-PyRMSE:0.09274
311s [112]	Train-rmse:0.00641	Train-PyRMSE:0.09058
311s [113]	Train-rmse:0.00631	Train-PyRMSE:0.08921
311s [114]	Train-rmse:0.00606	Train-PyRMSE:0.08569
311s [115]	Train-rmse:0.00583	Train-PyRMSE:0.08241
311s [116]	Train-rmse:0.00578	Train-PyRMSE:0.08175
311s [117]	Train-rmse:0.00562	Train-PyRMSE:0.07946
311s [118]	Train-rmse:0.00553	Train-PyRMSE:0.07818
311s [119]	Train-rmse:0.00533	Train-PyRMSE:0.07539
311s [120]	Train-rmse:0.00514	Train-PyRMSE:0.07262
311s [121]	Train-rmse:0.00510	Train-PyRMSE:0.07211
311s [122]	Train-rmse:0.00501	Train-PyRMSE:0.07088
312s [123]	Train-rmse:0.00489	Train-PyRMSE:0.06912
312s [124]	Train-rmse:0.00475	Train-PyRMSE:0.06722
312s [125]	Train-rmse:0.00473	Train-PyRMSE:0.06690
312s [126]	Train-rmse:0.00467	Train-PyRMSE:0.06603
312s [127]	Train-rmse:0.00443	Train-PyRMSE:0.06259
312s ==========================================
312s Running case predict_first_ntree.py...
314s /usr/lib/python3/dist-packages/xgboost/core.py:723: FutureWarning: Pass `evals` as keyword args.
314s   warnings.warn(msg, FutureWarning)
314s [0]	eval-logloss:0.22646	train-logloss:0.23316
314s [1]	eval-logloss:0.13776	train-logloss:0.13654
314s [2]	eval-logloss:0.08036	train-logloss:0.08243
314s start testing prediction from first n trees
314s error of ypred1=0.042831
314s error of ypred2=0.006207
314s [0]	validation_0-logloss:0.22646
314s [1]	validation_0-logloss:0.13776
314s [2]	validation_0-logloss:0.08036
314s start testing prediction from first n trees
314s error of ypred1=0.042831
314s error of ypred2=0.006207
315s ==========================================
315s Running case predict_leaf_indices.py...
316s /usr/lib/python3/dist-packages/xgboost/core.py:723: FutureWarning: Pass `evals` as keyword args.
316s   warnings.warn(msg, FutureWarning)
316s [0]	eval-logloss:0.22646	train-logloss:0.23316
317s [1]	eval-logloss:0.13776	train-logloss:0.13654
317s [2]	eval-logloss:0.08036	train-logloss:0.08243
317s start testing predict the leaf indices
317s (1611, 2, 1, 1)
317s [[[[5.]]
317s 
317s   [[4.]]]
317s 
317s 
317s  [[[6.]]
317s 
317s   [[4.]]]
317s 
317s 
317s  [[[5.]]
317s 
317s   [[4.]]]
317s 
317s 
317s  ...
317s 
317s 
317s  [[[6.]]
317s 
317s   [[4.]]]
317s 
317s 
317s  [[[4.]]
317s 
317s   [[3.]]]
317s 
317s 
317s  [[[6.]]
317s 
317s   [[4.]]]]
317s (1611, 3)
317s ==========================================
317s Skip case quantile_data_iterator.py...
317s ==========================================
317s Running case quantile_regression.py...
319s [0]	Train-quantile:1.50159	Test-quantile:1.45489
319s [1]	Train-quantile:1.41395	Test-quantile:1.36960
319s [2]	Train-quantile:1.33178	Test-quantile:1.28702
319s [3]	Train-quantile:1.25429	Test-quantile:1.21133
319s [4]	Train-quantile:1.18373	Test-quantile:1.13959
319s [5]	Train-quantile:1.11898	Test-quantile:1.07261
319s [6]	Train-quantile:1.05770	Test-quantile:1.01264
319s [7]	Train-quantile:1.00142	Test-quantile:0.96139
319s [8]	Train-quantile:0.94844	Test-quantile:0.91339
319s [9]	Train-quantile:0.89917	Test-quantile:0.86934
319s [10]	Train-quantile:0.85692	Test-quantile:0.82830
319s [11]	Train-quantile:0.81823	Test-quantile:0.79270
319s [12]	Train-quantile:0.78400	Test-quantile:0.75817
319s [13]	Train-quantile:0.75333	Test-quantile:0.72983
319s [14]	Train-quantile:0.72555	Test-quantile:0.70335
319s [15]	Train-quantile:0.69885	Test-quantile:0.67960
319s [16]	Train-quantile:0.67482	Test-quantile:0.65947
319s [17]	Train-quantile:0.65359	Test-quantile:0.64055
319s [18]	Train-quantile:0.63363	Test-quantile:0.62346
319s [19]	Train-quantile:0.61495	Test-quantile:0.60855
319s [20]	Train-quantile:0.59783	Test-quantile:0.59489
319s [21]	Train-quantile:0.58197	Test-quantile:0.58130
319s [22]	Train-quantile:0.56682	Test-quantile:0.56949
319s [23]	Train-quantile:0.55237	Test-quantile:0.55744
319s [24]	Train-quantile:0.53809	Test-quantile:0.54622
319s [25]	Train-quantile:0.52441	Test-quantile:0.53571
319s [26]	Train-quantile:0.51174	Test-quantile:0.52520
319s [27]	Train-quantile:0.49974	Test-quantile:0.51546
319s [28]	Train-quantile:0.48865	Test-quantile:0.50628
319s [29]	Train-quantile:0.47833	Test-quantile:0.49784
319s [30]	Train-quantile:0.46895	Test-quantile:0.48966
319s [31]	Train-quantile:0.45900	Test-quantile:0.48302
319s [0]	Train-rmse:4.32523	Test-rmse:4.63143
319s [1]	Train-rmse:4.21367	Test-rmse:4.53399
319s [2]	Train-rmse:4.10813	Test-rmse:4.44222
319s [3]	Train-rmse:4.00795	Test-rmse:4.35559
319s [4]	Train-rmse:3.91314	Test-rmse:4.27507
319s [5]	Train-rmse:3.82342	Test-rmse:4.19994
319s [6]	Train-rmse:3.73860	Test-rmse:4.12864
319s [7]	Train-rmse:3.65855	Test-rmse:4.06333
319s [8]	Train-rmse:3.58302	Test-rmse:3.99920
319s [9]	Train-rmse:3.51166	Test-rmse:3.94100
319s [10]	Train-rmse:3.44443	Test-rmse:3.88581
319s [11]	Train-rmse:3.38085	Test-rmse:3.83491
319s [12]	Train-rmse:3.32121	Test-rmse:3.78659
319s [13]	Train-rmse:3.26491	Test-rmse:3.74137
319s [14]	Train-rmse:3.21217	Test-rmse:3.69918
319s [15]	Train-rmse:3.16233	Test-rmse:3.66047
319s [16]	Train-rmse:3.11625	Test-rmse:3.62292
319s [17]	Train-rmse:3.07250	Test-rmse:3.58980
319s [18]	Train-rmse:3.03120	Test-rmse:3.55971
319s [19]	Train-rmse:2.99260	Test-rmse:3.53039
319s [20]	Train-rmse:2.95471	Test-rmse:3.50273
319s [21]	Train-rmse:2.92082	Test-rmse:3.47765
319s [22]	Train-rmse:2.88707	Test-rmse:3.45409
319s [23]	Train-rmse:2.85719	Test-rmse:3.43196
319s [24]	Train-rmse:2.82955	Test-rmse:3.41116
319s [25]	Train-rmse:2.80145	Test-rmse:3.39262
319s [26]	Train-rmse:2.77526	Test-rmse:3.37544
319s [27]	Train-rmse:2.75237	Test-rmse:3.35703
319s [28]	Train-rmse:2.73071	Test-rmse:3.34065
319s [29]	Train-rmse:2.70895	Test-rmse:3.32714
319s [30]	Train-rmse:2.69007	Test-rmse:3.31295
319s [31]	Train-rmse:2.67125	Test-rmse:3.30119
320s ==========================================
320s Running case sklearn_evals_result.py...
321s [0]	validation_0-logloss:0.63169	validation_1-logloss:0.65974
321s [1]	validation_0-logloss:0.58449	validation_1-logloss:0.62161
321s Access logloss metric directly from validation_0:
321s [0.6316909282654524, 0.5844871088303626]
321s 
321s Access metrics through a loop:
321s - validation_0
321s    - logloss
321s       - [0.6316909282654524, 0.5844871088303626]
321s - validation_1
321s    - logloss
321s       - [0.6597448766976595, 0.6216080508381129]
321s 
321s Access complete dict:
321s {'validation_0': OrderedDict({'logloss': [0.6316909282654524, 0.5844871088303626]}), 'validation_1': OrderedDict({'logloss': [0.6597448766976595, 0.6216080508381129]})}
322s ==========================================
322s Running case sklearn_examples.py...
327s Zeros and Ones from the Digits dataset: binary classification
327s [[87  0]
327s  [ 1 92]]
327s [[91  0]
327s  [ 3 86]]
327s Iris: multiclass classification
327s [[19  0  0]
327s  [ 1 31  2]
327s  [ 0  3 19]]
327s [[31  0  0]
327s  [ 0 16  0]
327s  [ 0  1 27]]
327s California Housing: regression
327s 0.2310805601814026
327s 0.23533764411819863
327s Parameter optimization
327s Fitting 3 folds for each of 4 candidates, totalling 12 fits
327s 0.6838972456687431
327s {'max_depth': 4, 'n_estimators': 100}
327s Pickling sklearn API models
327s True
327s [0]	validation_0-auc:0.99020
327s [1]	validation_0-auc:0.99975
327s [2]	validation_0-auc:0.99975
327s [3]	validation_0-auc:0.99975
327s [4]	validation_0-auc:0.99975
327s [5]	validation_0-auc:0.99975
327s [6]	validation_0-auc:1.00000
327s [7]	validation_0-auc:1.00000
327s [8]	validation_0-auc:1.00000
327s [9]	validation_0-auc:1.00000
328s [10]	validation_0-auc:1.00000
328s [11]	validation_0-auc:1.00000
328s [12]	validation_0-auc:1.00000
328s [13]	validation_0-auc:1.00000
328s [14]	validation_0-auc:1.00000
328s [15]	validation_0-auc:1.00000
328s [16]	validation_0-auc:1.00000
328s ==========================================
328s Running case sklearn_parallel.py...
329s Parallel Parameter optimization
329s Fitting 5 folds for each of 9 candidates, totalling 45 fits
343s 0.688555675183378
343s {'max_depth': 4, 'n_estimators': 50}
344s ==========================================
344s Skip case spark_estimator_examples.py...
344s ==========================================
344s Skip case update_process.py...
344s ==========================================
344s All cases passed.
345s /tmp/autopkgtest.fqUgNt/wrapper.sh: Killing leaked background processes: 2375 2376 
345s     PID TTY      STAT   TIME COMMAND
345s    2375 ?        R      0:00 /usr/bin/python3 -c from joblib.externals.loky.backend.resource_tracker import main; main(3, False)
345s /tmp/autopkgtest.fqUgNt/wrapper.sh: 235: kill: No such process
345s 
345s /tmp/autopkgtest.fqUgNt/wrapper.sh: 237: kill: No such process
345s 
345s autopkgtest [01:40:03]: test run-demos: -----------------------]
352s autopkgtest [01:40:10]: test run-demos:  - - - - - - - - - - results - - - - - - - - - -
352s run-demos            PASS
357s autopkgtest [01:40:15]: @@@@@@@@@@@@@@@@@@@@ summary
357s run-demos            PASS