[REVIEW] Rossmann: Getting closer to SoTA results

rerun tests

!!! Couldn't read commit file !!!

rerun tests

Its a bit hard to check diffs on notebooks, can you describe at a high level what the changes made were (besides the addition of the license and logo, which are a nice touch)? The results certainly look good.
One thing I'll note is that the only difference that I can notice between the last 2 TF cells is that the learning rate is different. If 1e-4 is the better rate, then let's just assign that to the LEARNING_RATE variable and just do training once for each framework.

!!!
Running as SYSTEM
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to PENDING with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/NVTabular Tests
using credential infra_1

git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
git --version # timeout=10
using GIT_SSH to set credentials creds for infrastructure pipeline on public nvtabular repo
git fetch --tags --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/9/:refs/remotes/origin/pr/9/ # timeout=10
git rev-parse 2c85b06f9a9575a8a871cb0825e5b07bcfc829de^{commit} # timeout=10
Checking out Revision 2c85b06f9a9575a8a871cb0825e5b07bcfc829de (detached)
git config core.sparsecheckout # timeout=10
git checkout -f 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
Commit message: "modify embedding size"
git rev-list --no-walk 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
[NVTabular Tests] $ /bin/bash /tmp/jenkins7060828907989777624.sh
All done! ��� ���� ���
23 files would be left unchanged.
Skipped 3 files
============================= test session starts ==============================
platform linux -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: /var/jenkins_home/workspace/nvtabular, inifile: setup.cfg
plugins: hypothesis-5.13.1, cov-2.8.1
collected 268 items

tests/unit/test_encoder.py ..............................                [ 11%]
tests/unit/test_groupby.py ............................................. [ 27%]
...                                                                      [ 29%]
tests/unit/test_io.py ...                                                [ 30%]
tests/unit/test_ops.py ................................................. [ 48%]
............                                                             [ 52%]
tests/unit/test_tf_dataloader.py ......                                  [ 55%]
tests/unit/test_torch_dataloader.py .................................... [ 68%]
......                                                                   [ 70%]
tests/unit/test_workflow.py ............................................ [ 87%]
..................................                                       [100%]
----------- coverage: platform linux, python 3.7.6-final-0 -----------
Name                            Stmts   Miss Branch BrPart  Cover   Missing
nvtabular/init.py               6      0      0      0   100%
nvtabular/ds_writer.py             85      5     34      6    91%   26-27, 66->67, 67, 73->81, 98->99, 99-100, 103->105, 108->106, 117->116
nvtabular/encoder.py              153     25     56     11    77%   75->76, 76, 78->79, 79, 81->82, 82, 84->85, 85, 96->97, 97, 111->114, 138->139, 139, 141->142, 142, 150->153, 153, 162->163, 163, 266-271, 275-288, 304->308, 308
nvtabular/groupby.py              155     25     88     14    82%   75->76, 76, 79->80, 80, 86->87, 87, 90->91, 91, 94->96, 135->136, 136, 176->179, 183->exit, 202->205, 205, 216->219, 219, 236->242, 242-269, 272->273, 273-274, 275->276, 276-277, 291->292, 292-293
nvtabular/io.py                   263     73    104     11    68%   48->49, 49, 53->56, 56, 91, 113->119, 136->137, 137, 140->exit, 167->170, 187->198, 195->197, 272->273, 273, 281-287, 322->323, 323, 324->325, 325, 427-450, 453-468, 473-486, 489-511, 514-517, 521-529
nvtabular/ops.py                  441     93    108     12    75%   62->61, 93-97, 112->114, 393->396, 396, 475->476, 476, 479->480, 480-485, 511-512, 557-562, 566-567, 585->586, 586, 612->613, 613, 642->643, 643, 650->649, 693->694, 694, 724->725, 725, 785-794, 797-843, 848-850, 853, 856-857, 860-862, 925-932, 936, 949-957, 1040->1041, 1041, 1053-1057, 1060, 1065-1069
nvtabular/tf_dataloader.py        118     26     44     10    72%   17->19, 28-29, 32->35, 35-37, 72-77, 182->183, 183-184, 192->193, 193, 195->198, 198-201, 202->205, 205, 213->214, 214-217, 226->230, 257->258, 258, 263-264, 275->276, 276, 308
nvtabular/torch_dataloader.py     154     22     64     14    80%   47, 70->71, 71, 73->74, 74-75, 82-85, 91->92, 92-93, 101-102, 106->107, 107, 124->126, 130-134, 162->164, 164->166, 166->exit, 171->172, 172, 192->193, 193, 195->198, 238, 274->276, 276->277, 277, 278->279, 279, 294, 299
nvtabular/workflow.py             464     73    244     25    82%   32-33, 143->149, 149, 152-160, 188-190, 204-206, 220-222, 236-238, 263->264, 264, 315->317, 335->337, 347->348, 348, 384-394, 403->404, 404, 427->424, 484->485, 485, 494->495, 495-496, 503->506, 506, 536->539, 539, 550-553, 568->564, 573->574, 574, 597->598, 598, 682->683, 683-690, 736->738, 738->740, 740->741, 741-742, 743->753, 753, 761->763, 763->764, 764, 816->817, 817, 821->822, 822-828, 834->839, 839-842, 848->851, 851, 955-959
setup.py                            2      2      0      0     0%   18-20
TOTAL                            1841    344    742    103    78%
Coverage XML written to file coverage.xml
Required test coverage of 70% reached. Total coverage: 77.74%
======================= 268 passed in 150.84s (0:02:30) ========================
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to SUCCESS with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Success
'
Using context: Jenkins Unit Test Run

rerun tests

GitHub pull request #9 of commit 2c85b06f9a9575a8a871cb0825e5b07bcfc829de, no merge conflicts.
Running as SYSTEM
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to PENDING with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/25 and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/NVTabular Tests
using credential infra_1

git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
git --version # timeout=10
using GIT_SSH to set credentials creds for infrastructure pipeline on public nvtabular repo
git fetch --tags --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/9/:refs/remotes/origin/pr/9/ # timeout=10
git rev-parse 2c85b06f9a9575a8a871cb0825e5b07bcfc829de^{commit} # timeout=10
Checking out Revision 2c85b06f9a9575a8a871cb0825e5b07bcfc829de (detached)
git config core.sparsecheckout # timeout=10
git checkout -f 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
Commit message: "modify embedding size"
git rev-list --no-walk bbd1d2a7f41fa2b6a9a2eacda919da0a073ddc33 # timeout=10
[NVTabular Tests] $ /bin/bash /tmp/jenkins318540331826975079.sh
All done! ��� ���� ���
23 files would be left unchanged.
Skipped 3 files
============================= test session starts ==============================
platform linux -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: /var/jenkins_home/workspace/nvtabular, inifile: setup.cfg
plugins: hypothesis-5.13.1, cov-2.8.1
collected 268 items

tests/unit/test_encoder.py ..............................                [ 11%]
tests/unit/test_groupby.py ............................................. [ 27%]
...                                                                      [ 29%]
tests/unit/test_io.py ...                                                [ 30%]
tests/unit/test_ops.py ................................................. [ 48%]
............                                                             [ 52%]
tests/unit/test_tf_dataloader.py ......                                  [ 55%]
tests/unit/test_torch_dataloader.py .................................... [ 68%]
......                                                                   [ 70%]
tests/unit/test_workflow.py ............................................ [ 87%]
..................................                                       [100%]
----------- coverage: platform linux, python 3.7.6-final-0 -----------
Name                            Stmts   Miss Branch BrPart  Cover   Missing
nvtabular/init.py               6      0      0      0   100%
nvtabular/ds_writer.py             85      5     34      6    91%   26-27, 66->67, 67, 73->81, 98->99, 99-100, 103->105, 108->106, 117->116
nvtabular/encoder.py              153     25     56     11    77%   75->76, 76, 78->79, 79, 81->82, 82, 84->85, 85, 96->97, 97, 111->114, 138->139, 139, 141->142, 142, 150->153, 153, 162->163, 163, 266-271, 275-288, 304->308, 308
nvtabular/groupby.py              155     25     88     14    82%   75->76, 76, 79->80, 80, 86->87, 87, 90->91, 91, 94->96, 135->136, 136, 176->179, 183->exit, 202->205, 205, 216->219, 219, 236->242, 242-269, 272->273, 273-274, 275->276, 276-277, 291->292, 292-293
nvtabular/io.py                   263     73    104     11    68%   48->49, 49, 53->56, 56, 91, 113->119, 136->137, 137, 140->exit, 167->170, 187->198, 195->197, 272->273, 273, 281-287, 322->323, 323, 324->325, 325, 427-450, 453-468, 473-486, 489-511, 514-517, 521-529
nvtabular/ops.py                  441     93    108     12    75%   62->61, 93-97, 112->114, 393->396, 396, 475->476, 476, 479->480, 480-485, 511-512, 557-562, 566-567, 585->586, 586, 612->613, 613, 642->643, 643, 650->649, 693->694, 694, 724->725, 725, 785-794, 797-843, 848-850, 853, 856-857, 860-862, 925-932, 936, 949-957, 1040->1041, 1041, 1053-1057, 1060, 1065-1069
nvtabular/tf_dataloader.py        118     26     44     10    72%   17->19, 28-29, 32->35, 35-37, 72-77, 182->183, 183-184, 192->193, 193, 195->198, 198-201, 202->205, 205, 213->214, 214-217, 226->230, 257->258, 258, 263-264, 275->276, 276, 308
nvtabular/torch_dataloader.py     154     22     64     14    80%   47, 70->71, 71, 73->74, 74-75, 82-85, 91->92, 92-93, 101-102, 106->107, 107, 124->126, 130-134, 162->164, 164->166, 166->exit, 171->172, 172, 192->193, 193, 195->198, 238, 274->276, 276->277, 277, 278->279, 279, 294, 299
nvtabular/workflow.py             464     73    244     25    82%   32-33, 143->149, 149, 152-160, 188-190, 204-206, 220-222, 236-238, 263->264, 264, 315->317, 335->337, 347->348, 348, 384-394, 403->404, 404, 427->424, 484->485, 485, 494->495, 495-496, 503->506, 506, 536->539, 539, 550-553, 568->564, 573->574, 574, 597->598, 598, 682->683, 683-690, 736->738, 738->740, 740->741, 741-742, 743->753, 753, 761->763, 763->764, 764, 816->817, 817, 821->822, 822-828, 834->839, 839-842, 848->851, 851, 955-959
setup.py                            2      2      0      0     0%   18-20
TOTAL                            1841    344    742    103    78%
Coverage XML written to file coverage.xml
Required test coverage of 70% reached. Total coverage: 77.74%
======================= 268 passed in 150.28s (0:02:30) ========================
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script  : #!/bin/bash
s_test=$(cat /var/jenkins_home/jobs/NVTabular Tests/builds/25/log)
body=Click to view CI Results$s_test
curl "https://api.GitHub.com/repos/NVIDIA/NVTabular/statuses/2c85b06f9a9575a8a871cb0825e5b07bcfc829de"
-H "Content-Type: application/json"  -H "Authorization: token e7b965d4570816ade0e2f03f34f6672e5c346669 "
-X POST
-d '{"body": "$body"}'
[NVTabular Tests] $ /bin/bash /tmp/jenkins2392389725377293022.sh
cat: /var/jenkins_home/jobs/NVTabular: No such file or directory
cat: Tests/builds/25/log: No such file or directory
/tmp/jenkins2392389725377293022.sh: line 3: syntax error near unexpected token <' /tmp/jenkins2392389725377293022.sh: line 3: body=Click to view CI Results$s_test'
POST BUILD TASK : FAILURE
END OF POST BUILD TASK : 0
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to SUCCESS with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/25 and message: 'Success
'
Using context: Jenkins Unit Test Run

rerun tests

GitHub pull request #9 of commit 2c85b06f9a9575a8a871cb0825e5b07bcfc829de, no merge conflicts.
Running as SYSTEM
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to PENDING with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/28 and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/NVTabular Tests
using credential infra_1

git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
git --version # timeout=10
using GIT_SSH to set credentials creds for infrastructure pipeline on public nvtabular repo
git fetch --tags --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/9/:refs/remotes/origin/pr/9/ # timeout=10
git rev-parse 2c85b06f9a9575a8a871cb0825e5b07bcfc829de^{commit} # timeout=10
Checking out Revision 2c85b06f9a9575a8a871cb0825e5b07bcfc829de (detached)
git config core.sparsecheckout # timeout=10
git checkout -f 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
Commit message: "modify embedding size"
git rev-list --no-walk d4821f87d51a0a6c4ac9e70881c191eca10d969e # timeout=10
[NVTabular Tests] $ /bin/bash /tmp/jenkins4745040676670853151.sh
All done! ��� ���� ���
23 files would be left unchanged.
Skipped 3 files
============================= test session starts ==============================
platform linux -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: /var/jenkins_home/workspace/nvtabular, inifile: setup.cfg
plugins: hypothesis-5.13.1, cov-2.8.1
collected 268 items

tests/unit/test_encoder.py ..............................                [ 11%]
tests/unit/test_groupby.py ............................................. [ 27%]
...                                                                      [ 29%]
tests/unit/test_io.py ...                                                [ 30%]
tests/unit/test_ops.py ................................................. [ 48%]
............                                                             [ 52%]
tests/unit/test_tf_dataloader.py ......                                  [ 55%]
tests/unit/test_torch_dataloader.py .................................... [ 68%]
......                                                                   [ 70%]
tests/unit/test_workflow.py ............................................ [ 87%]
..................................                                       [100%]
----------- coverage: platform linux, python 3.7.6-final-0 -----------
Name                            Stmts   Miss Branch BrPart  Cover   Missing
nvtabular/init.py               6      0      0      0   100%
nvtabular/ds_writer.py             85      5     34      6    91%   26-27, 66->67, 67, 73->81, 98->99, 99-100, 103->105, 108->106, 117->116
nvtabular/encoder.py              153     25     56     11    77%   75->76, 76, 78->79, 79, 81->82, 82, 84->85, 85, 96->97, 97, 111->114, 138->139, 139, 141->142, 142, 150->153, 153, 162->163, 163, 266-271, 275-288, 304->308, 308
nvtabular/groupby.py              155     25     88     14    82%   75->76, 76, 79->80, 80, 86->87, 87, 90->91, 91, 94->96, 135->136, 136, 176->179, 183->exit, 202->205, 205, 216->219, 219, 236->242, 242-269, 272->273, 273-274, 275->276, 276-277, 291->292, 292-293
nvtabular/io.py                   263     73    104     11    68%   48->49, 49, 53->56, 56, 91, 113->119, 136->137, 137, 140->exit, 167->170, 187->198, 195->197, 272->273, 273, 281-287, 322->323, 323, 324->325, 325, 427-450, 453-468, 473-486, 489-511, 514-517, 521-529
nvtabular/ops.py                  441     93    108     12    75%   62->61, 93-97, 112->114, 393->396, 396, 475->476, 476, 479->480, 480-485, 511-512, 557-562, 566-567, 585->586, 586, 612->613, 613, 642->643, 643, 650->649, 693->694, 694, 724->725, 725, 785-794, 797-843, 848-850, 853, 856-857, 860-862, 925-932, 936, 949-957, 1040->1041, 1041, 1053-1057, 1060, 1065-1069
nvtabular/tf_dataloader.py        118     26     44     10    72%   17->19, 28-29, 32->35, 35-37, 72-77, 182->183, 183-184, 192->193, 193, 195->198, 198-201, 202->205, 205, 213->214, 214-217, 226->230, 257->258, 258, 263-264, 275->276, 276, 308
nvtabular/torch_dataloader.py     154     22     64     14    80%   47, 70->71, 71, 73->74, 74-75, 82-85, 91->92, 92-93, 101-102, 106->107, 107, 124->126, 130-134, 162->164, 164->166, 166->exit, 171->172, 172, 192->193, 193, 195->198, 238, 274->276, 276->277, 277, 278->279, 279, 294, 299
nvtabular/workflow.py             464     73    244     25    82%   32-33, 143->149, 149, 152-160, 188-190, 204-206, 220-222, 236-238, 263->264, 264, 315->317, 335->337, 347->348, 348, 384-394, 403->404, 404, 427->424, 484->485, 485, 494->495, 495-496, 503->506, 506, 536->539, 539, 550-553, 568->564, 573->574, 574, 597->598, 598, 682->683, 683-690, 736->738, 738->740, 740->741, 741-742, 743->753, 753, 761->763, 763->764, 764, 816->817, 817, 821->822, 822-828, 834->839, 839-842, 848->851, 851, 955-959
setup.py                            2      2      0      0     0%   18-20
TOTAL                            1841    344    742    103    78%
Coverage XML written to file coverage.xml
Required test coverage of 70% reached. Total coverage: 77.74%
======================= 268 passed in 150.35s (0:02:30) ========================
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script  : #!/bin/bash
s_test=$(cat /var/jenkins_home/jobs/NVTabular Tests/builds/28/log)
body="Click to view CI Results$s_test"
curl "https://api.GitHub.com/repos/NVIDIA/NVTabular/statuses/2c85b06f9a9575a8a871cb0825e5b07bcfc829de"
-H "Content-Type: application/json"  -H "Authorization: token e7b965d4570816ade0e2f03f34f6672e5c346669 "
-X POST
-d '{"body": "$body"}'
[NVTabular Tests] $ /bin/bash /tmp/jenkins8784545425745514469.sh
cat: /var/jenkins_home/jobs/NVTabular: No such file or directory
cat: Tests/builds/28/log: No such file or directory
% Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
Dload  Upload   Total   Spent    Left  Speed
0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
100   304  100   287  100    17    683     40 --:--:-- --:--:-- --:--:--   723
{
"message": "Validation Failed",
"errors": [
{
"resource": "Status",
"code": "custom",
"field": "state",
"message": "state is not included in the list"
}
],
"documentation_url": "https://developer.github.com/v3/repos/statuses/#create-a-status"
}
POST BUILD TASK : SUCCESS
END OF POST BUILD TASK : 0
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to SUCCESS with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/28 and message: 'Success
'
Using context: Jenkins Unit Test Run

rerun tests

$body

$body

$body

${body}

${echo body}

body

GitHub pull request #9 of commit 2c85b06f9a9575a8a871cb0825e5b07bcfc829de, no merge conflicts.
Running as SYSTEM
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to PENDING with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/NVTabular Tests
using credential infra_1

git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
git --version # timeout=10
using GIT_SSH to set credentials creds for infrastructure pipeline on public nvtabular repo
git fetch --tags --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/9/:refs/remotes/origin/pr/9/ # timeout=10
git rev-parse 2c85b06f9a9575a8a871cb0825e5b07bcfc829de^{commit} # timeout=10
Checking out Revision 2c85b06f9a9575a8a871cb0825e5b07bcfc829de (detached)
git config core.sparsecheckout # timeout=10
git checkout -f 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
Commit message: "modify embedding size"
git rev-list --no-walk 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
[NVTabular Tests] $ /bin/bash /tmp/jenkins7060828907989777624.sh
All done! ✨ 🍰 ✨
23 files would be left unchanged.
Skipped 3 files
============================= test session starts ==============================
platform linux -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: /var/jenkins_home/workspace/nvtabular, inifile: setup.cfg
plugins: hypothesis-5.13.1, cov-2.8.1
collected 268 items

tests/unit/test_encoder.py ..............................                [ 11%]
tests/unit/test_groupby.py ............................................. [ 27%]
...                                                                      [ 29%]
tests/unit/test_io.py ...                                                [ 30%]
tests/unit/test_ops.py ................................................. [ 48%]
............                                                             [ 52%]
tests/unit/test_tf_dataloader.py ......                                  [ 55%]
tests/unit/test_torch_dataloader.py .................................... [ 68%]
......                                                                   [ 70%]
tests/unit/test_workflow.py ............................................ [ 87%]
..................................                                       [100%]
----------- coverage: platform linux, python 3.7.6-final-0 -----------
Name                            Stmts   Miss Branch BrPart  Cover   Missing
nvtabular/init.py               6      0      0      0   100%
nvtabular/ds_writer.py             85      5     34      6    91%   26-27, 66->67, 67, 73->81, 98->99, 99-100, 103->105, 108->106, 117->116
nvtabular/encoder.py              153     25     56     11    77%   75->76, 76, 78->79, 79, 81->82, 82, 84->85, 85, 96->97, 97, 111->114, 138->139, 139, 141->142, 142, 150->153, 153, 162->163, 163, 266-271, 275-288, 304->308, 308
nvtabular/groupby.py              155     25     88     14    82%   75->76, 76, 79->80, 80, 86->87, 87, 90->91, 91, 94->96, 135->136, 136, 176->179, 183->exit, 202->205, 205, 216->219, 219, 236->242, 242-269, 272->273, 273-274, 275->276, 276-277, 291->292, 292-293
nvtabular/io.py                   263     73    104     11    68%   48->49, 49, 53->56, 56, 91, 113->119, 136->137, 137, 140->exit, 167->170, 187->198, 195->197, 272->273, 273, 281-287, 322->323, 323, 324->325, 325, 427-450, 453-468, 473-486, 489-511, 514-517, 521-529
nvtabular/ops.py                  441     93    108     12    75%   62->61, 93-97, 112->114, 393->396, 396, 475->476, 476, 479->480, 480-485, 511-512, 557-562, 566-567, 585->586, 586, 612->613, 613, 642->643, 643, 650->649, 693->694, 694, 724->725, 725, 785-794, 797-843, 848-850, 853, 856-857, 860-862, 925-932, 936, 949-957, 1040->1041, 1041, 1053-1057, 1060, 1065-1069
nvtabular/tf_dataloader.py        118     26     44     10    72%   17->19, 28-29, 32->35, 35-37, 72-77, 182->183, 183-184, 192->193, 193, 195->198, 198-201, 202->205, 205, 213->214, 214-217, 226->230, 257->258, 258, 263-264, 275->276, 276, 308
nvtabular/torch_dataloader.py     154     22     64     14    80%   47, 70->71, 71, 73->74, 74-75, 82-85, 91->92, 92-93, 101-102, 106->107, 107, 124->126, 130-134, 162->164, 164->166, 166->exit, 171->172, 172, 192->193, 193, 195->198, 238, 274->276, 276->277, 277, 278->279, 279, 294, 299
nvtabular/workflow.py             464     73    244     25    82%   32-33, 143->149, 149, 152-160, 188-190, 204-206, 220-222, 236-238, 263->264, 264, 315->317, 335->337, 347->348, 348, 384-394, 403->404, 404, 427->424, 484->485, 485, 494->495, 495-496, 503->506, 506, 536->539, 539, 550-553, 568->564, 573->574, 574, 597->598, 598, 682->683, 683-690, 736->738, 738->740, 740->741, 741-742, 743->753, 753, 761->763, 763->764, 764, 816->817, 817, 821->822, 822-828, 834->839, 839-842, 848->851, 851, 955-959
setup.py                            2      2      0      0     0%   18-20
TOTAL                            1841    344    742    103    78%
Coverage XML written to file coverage.xml
Required test coverage of 70% reached. Total coverage: 77.74%
======================= 268 passed in 150.84s (0:02:30) ========================
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to SUCCESS with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Success
'
Using context: Jenkins Unit Test Run
GitHub pull request #9 of commit 2c85b06f9a9575a8a871cb0825e5b07bcfc829de, no merge conflicts.
Running as SYSTEM
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to PENDING with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/NVTabular Tests
using credential infra_1

git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
git --version # timeout=10
using GIT_SSH to set credentials creds for infrastructure pipeline on public nvtabular repo
git fetch --tags --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/9/:refs/remotes/origin/pr/9/ # timeout=10
git rev-parse 2c85b06f9a9575a8a871cb0825e5b07bcfc829de^{commit} # timeout=10
Checking out Revision 2c85b06f9a9575a8a871cb0825e5b07bcfc829de (detached)
git config core.sparsecheckout # timeout=10
git checkout -f 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
Commit message: "modify embedding size"
git rev-list --no-walk 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
[NVTabular Tests] $ /bin/bash /tmp/jenkins7060828907989777624.sh
All done! ??? ???? ???
23 files would be left unchanged.
Skipped 3 files
============================= test session starts ==============================
platform linux -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: /var/jenkins_home/workspace/nvtabular, inifile: setup.cfg
plugins: hypothesis-5.13.1, cov-2.8.1
collected 268 items

tests/unit/test_encoder.py ..............................                [ 11%]
tests/unit/test_groupby.py ............................................. [ 27%]
...                                                                      [ 29%]
tests/unit/test_io.py ...                                                [ 30%]
tests/unit/test_ops.py ................................................. [ 48%]
............                                                             [ 52%]
tests/unit/test_tf_dataloader.py ......                                  [ 55%]
tests/unit/test_torch_dataloader.py .................................... [ 68%]
......                                                                   [ 70%]
tests/unit/test_workflow.py ............................................ [ 87%]
..................................                                       [100%]
----------- coverage: platform linux, python 3.7.6-final-0 -----------
Name                            Stmts   Miss Branch BrPart  Cover   Missing
nvtabular/init.py               6      0      0      0   100%
nvtabular/ds_writer.py             85      5     34      6    91%   26-27, 66->67, 67, 73->81, 98->99, 99-100, 103->105, 108->106, 117->116
nvtabular/encoder.py              153     25     56     11    77%   75->76, 76, 78->79, 79, 81->82, 82, 84->85, 85, 96->97, 97, 111->114, 138->139, 139, 141->142, 142, 150->153, 153, 162->163, 163, 266-271, 275-288, 304->308, 308
nvtabular/groupby.py              155     25     88     14    82%   75->76, 76, 79->80, 80, 86->87, 87, 90->91, 91, 94->96, 135->136, 136, 176->179, 183->exit, 202->205, 205, 216->219, 219, 236->242, 242-269, 272->273, 273-274, 275->276, 276-277, 291->292, 292-293
nvtabular/io.py                   263     73    104     11    68%   48->49, 49, 53->56, 56, 91, 113->119, 136->137, 137, 140->exit, 167->170, 187->198, 195->197, 272->273, 273, 281-287, 322->323, 323, 324->325, 325, 427-450, 453-468, 473-486, 489-511, 514-517, 521-529
nvtabular/ops.py                  441     93    108     12    75%   62->61, 93-97, 112->114, 393->396, 396, 475->476, 476, 479->480, 480-485, 511-512, 557-562, 566-567, 585->586, 586, 612->613, 613, 642->643, 643, 650->649, 693->694, 694, 724->725, 725, 785-794, 797-843, 848-850, 853, 856-857, 860-862, 925-932, 936, 949-957, 1040->1041, 1041, 1053-1057, 1060, 1065-1069
nvtabular/tf_dataloader.py        118     26     44     10    72%   17->19, 28-29, 32->35, 35-37, 72-77, 182->183, 183-184, 192->193, 193, 195->198, 198-201, 202->205, 205, 213->214, 214-217, 226->230, 257->258, 258, 263-264, 275->276, 276, 308
nvtabular/torch_dataloader.py     154     22     64     14    80%   47, 70->71, 71, 73->74, 74-75, 82-85, 91->92, 92-93, 101-102, 106->107, 107, 124->126, 130-134, 162->164, 164->166, 166->exit, 171->172, 172, 192->193, 193, 195->198, 238, 274->276, 276->277, 277, 278->279, 279, 294, 299
nvtabular/workflow.py             464     73    244     25    82%   32-33, 143->149, 149, 152-160, 188-190, 204-206, 220-222, 236-238, 263->264, 264, 315->317, 335->337, 347->348, 348, 384-394, 403->404, 404, 427->424, 484->485, 485, 494->495, 495-496, 503->506, 506, 536->539, 539, 550-553, 568->564, 573->574, 574, 597->598, 598, 682->683, 683-690, 736->738, 738->740, 740->741, 741-742, 743->753, 753, 761->763, 763->764, 764, 816->817, 817, 821->822, 822-828, 834->839, 839-842, 848->851, 851, 955-959
setup.py                            2      2      0      0     0%   18-20
TOTAL                            1841    344    742    103    78%
Coverage XML written to file coverage.xml
Required test coverage of 70% reached. Total coverage: 77.74%
======================= 268 passed in 150.84s (0:02:30) ========================
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to SUCCESS with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Success
'
Using context: Jenkins Unit Test Run
[WS-CLEANUP] Deleting project workspace...
[WS-CLEANUP] Deferred wipeout is used...
[WS-CLEANUP] done
Finished: SUCCESS

Click to view CI ResultsGitHub pull request #9 of commit 2c85b06f9a9575a8a871cb0825e5b07bcfc829de, no merge conflicts.
Running as SYSTEM
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to PENDING with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/NVTabular Tests
using credential infra_1
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
 > git --version # timeout=10
using GIT_SSH to set credentials creds for infrastructure pipeline on public nvtabular repo
 > git fetch --tags --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/9/*:refs/remotes/origin/pr/9/* # timeout=10
 > git rev-parse 2c85b06f9a9575a8a871cb0825e5b07bcfc829de^{commit} # timeout=10
Checking out Revision 2c85b06f9a9575a8a871cb0825e5b07bcfc829de (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
Commit message: "modify embedding size"
 > git rev-list --no-walk 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
[NVTabular Tests] $ /bin/bash /tmp/jenkins7060828907989777624.sh
All done! ✨ 🍰 ✨
23 files would be left unchanged.
Skipped 3 files
============================= test session starts ==============================
platform linux -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: /var/jenkins_home/workspace/nvtabular, inifile: setup.cfg
plugins: hypothesis-5.13.1, cov-2.8.1
collected 268 items
tests/unit/test_encoder.py ..............................                [ 11%]
tests/unit/test_groupby.py ............................................. [ 27%]
...                                                                      [ 29%]
tests/unit/test_io.py ...                                                [ 30%]
tests/unit/test_ops.py ................................................. [ 48%]
............                                                             [ 52%]
tests/unit/test_tf_dataloader.py ......                                  [ 55%]
tests/unit/test_torch_dataloader.py .................................... [ 68%]
......                                                                   [ 70%]
tests/unit/test_workflow.py ............................................ [ 87%]
..................................                                       [100%]
----------- coverage: platform linux, python 3.7.6-final-0 -----------
Name                            Stmts   Miss Branch BrPart  Cover   Missing
nvtabular/init.py               6      0      0      0   100%
nvtabular/ds_writer.py             85      5     34      6    91%   26-27, 66->67, 67, 73->81, 98->99, 99-100, 103->105, 108->106, 117->116
nvtabular/encoder.py              153     25     56     11    77%   75->76, 76, 78->79, 79, 81->82, 82, 84->85, 85, 96->97, 97, 111->114, 138->139, 139, 141->142, 142, 150->153, 153, 162->163, 163, 266-271, 275-288, 304->308, 308
nvtabular/groupby.py              155     25     88     14    82%   75->76, 76, 79->80, 80, 86->87, 87, 90->91, 91, 94->96, 135->136, 136, 176->179, 183->exit, 202->205, 205, 216->219, 219, 236->242, 242-269, 272->273, 273-274, 275->276, 276-277, 291->292, 292-293
nvtabular/io.py                   263     73    104     11    68%   48->49, 49, 53->56, 56, 91, 113->119, 136->137, 137, 140->exit, 167->170, 187->198, 195->197, 272->273, 273, 281-287, 322->323, 323, 324->325, 325, 427-450, 453-468, 473-486, 489-511, 514-517, 521-529
nvtabular/ops.py                  441     93    108     12    75%   62->61, 93-97, 112->114, 393->396, 396, 475->476, 476, 479->480, 480-485, 511-512, 557-562, 566-567, 585->586, 586, 612->613, 613, 642->643, 643, 650->649, 693->694, 694, 724->725, 725, 785-794, 797-843, 848-850, 853, 856-857, 860-862, 925-932, 936, 949-957, 1040->1041, 1041, 1053-1057, 1060, 1065-1069
nvtabular/tf_dataloader.py        118     26     44     10    72%   17->19, 28-29, 32->35, 35-37, 72-77, 182->183, 183-184, 192->193, 193, 195->198, 198-201, 202->205, 205, 213->214, 214-217, 226->230, 257->258, 258, 263-264, 275->276, 276, 308
nvtabular/torch_dataloader.py     154     22     64     14    80%   47, 70->71, 71, 73->74, 74-75, 82-85, 91->92, 92-93, 101-102, 106->107, 107, 124->126, 130-134, 162->164, 164->166, 166->exit, 171->172, 172, 192->193, 193, 195->198, 238, 274->276, 276->277, 277, 278->279, 279, 294, 299
nvtabular/workflow.py             464     73    244     25    82%   32-33, 143->149, 149, 152-160, 188-190, 204-206, 220-222, 236-238, 263->264, 264, 315->317, 335->337, 347->348, 348, 384-394, 403->404, 404, 427->424, 484->485, 485, 494->495, 495-496, 503->506, 506, 536->539, 539, 550-553, 568->564, 573->574, 574, 597->598, 598, 682->683, 683-690, 736->738, 738->740, 740->741, 741-742, 743->753, 753, 761->763, 763->764, 764, 816->817, 817, 821->822, 822-828, 834->839, 839-842, 848->851, 851, 955-959
setup.py                            2      2      0      0     0%   18-20
TOTAL                            1841    344    742    103    78%
Coverage XML written to file coverage.xml
Required test coverage of 70% reached. Total coverage: 77.74%
======================= 268 passed in 150.84s (0:02:30) ========================
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to SUCCESS with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Success
'
Using context: Jenkins Unit Test Run
GitHub pull request #9 of commit 2c85b06f9a9575a8a871cb0825e5b07bcfc829de, no merge conflicts.
Running as SYSTEM
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to PENDING with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/NVTabular Tests
using credential infra_1

git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
git --version # timeout=10
using GIT_SSH to set credentials creds for infrastructure pipeline on public nvtabular repo
git fetch --tags --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/9/:refs/remotes/origin/pr/9/ # timeout=10
git rev-parse 2c85b06f9a9575a8a871cb0825e5b07bcfc829de^{commit} # timeout=10
Checking out Revision 2c85b06f9a9575a8a871cb0825e5b07bcfc829de (detached)
git config core.sparsecheckout # timeout=10
git checkout -f 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
Commit message: "modify embedding size"
git rev-list --no-walk 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
[NVTabular Tests] $ /bin/bash /tmp/jenkins7060828907989777624.sh
All done! ??? ???? ???
23 files would be left unchanged.
Skipped 3 files
============================= test session starts ==============================
platform linux -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: /var/jenkins_home/workspace/nvtabular, inifile: setup.cfg
plugins: hypothesis-5.13.1, cov-2.8.1
collected 268 items

tests/unit/test_encoder.py ..............................                [ 11%]
tests/unit/test_groupby.py ............................................. [ 27%]
...                                                                      [ 29%]
tests/unit/test_io.py ...                                                [ 30%]
tests/unit/test_ops.py ................................................. [ 48%]
............                                                             [ 52%]
tests/unit/test_tf_dataloader.py ......                                  [ 55%]
tests/unit/test_torch_dataloader.py .................................... [ 68%]
......                                                                   [ 70%]
tests/unit/test_workflow.py ............................................ [ 87%]
..................................                                       [100%]
----------- coverage: platform linux, python 3.7.6-final-0 -----------
Name                            Stmts   Miss Branch BrPart  Cover   Missing
nvtabular/init.py               6      0      0      0   100%
nvtabular/ds_writer.py             85      5     34      6    91%   26-27, 66->67, 67, 73->81, 98->99, 99-100, 103->105, 108->106, 117->116
nvtabular/encoder.py              153     25     56     11    77%   75->76, 76, 78->79, 79, 81->82, 82, 84->85, 85, 96->97, 97, 111->114, 138->139, 139, 141->142, 142, 150->153, 153, 162->163, 163, 266-271, 275-288, 304->308, 308
nvtabular/groupby.py              155     25     88     14    82%   75->76, 76, 79->80, 80, 86->87, 87, 90->91, 91, 94->96, 135->136, 136, 176->179, 183->exit, 202->205, 205, 216->219, 219, 236->242, 242-269, 272->273, 273-274, 275->276, 276-277, 291->292, 292-293
nvtabular/io.py                   263     73    104     11    68%   48->49, 49, 53->56, 56, 91, 113->119, 136->137, 137, 140->exit, 167->170, 187->198, 195->197, 272->273, 273, 281-287, 322->323, 323, 324->325, 325, 427-450, 453-468, 473-486, 489-511, 514-517, 521-529
nvtabular/ops.py                  441     93    108     12    75%   62->61, 93-97, 112->114, 393->396, 396, 475->476, 476, 479->480, 480-485, 511-512, 557-562, 566-567, 585->586, 586, 612->613, 613, 642->643, 643, 650->649, 693->694, 694, 724->725, 725, 785-794, 797-843, 848-850, 853, 856-857, 860-862, 925-932, 936, 949-957, 1040->1041, 1041, 1053-1057, 1060, 1065-1069
nvtabular/tf_dataloader.py        118     26     44     10    72%   17->19, 28-29, 32->35, 35-37, 72-77, 182->183, 183-184, 192->193, 193, 195->198, 198-201, 202->205, 205, 213->214, 214-217, 226->230, 257->258, 258, 263-264, 275->276, 276, 308
nvtabular/torch_dataloader.py     154     22     64     14    80%   47, 70->71, 71, 73->74, 74-75, 82-85, 91->92, 92-93, 101-102, 106->107, 107, 124->126, 130-134, 162->164, 164->166, 166->exit, 171->172, 172, 192->193, 193, 195->198, 238, 274->276, 276->277, 277, 278->279, 279, 294, 299
nvtabular/workflow.py             464     73    244     25    82%   32-33, 143->149, 149, 152-160, 188-190, 204-206, 220-222, 236-238, 263->264, 264, 315->317, 335->337, 347->348, 348, 384-394, 403->404, 404, 427->424, 484->485, 485, 494->495, 495-496, 503->506, 506, 536->539, 539, 550-553, 568->564, 573->574, 574, 597->598, 598, 682->683, 683-690, 736->738, 738->740, 740->741, 741-742, 743->753, 753, 761->763, 763->764, 764, 816->817, 817, 821->822, 822-828, 834->839, 839-842, 848->851, 851, 955-959
setup.py                            2      2      0      0     0%   18-20
TOTAL                            1841    344    742    103    78%
Coverage XML written to file coverage.xml
Required test coverage of 70% reached. Total coverage: 77.74%
======================= 268 passed in 150.84s (0:02:30) ========================
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to SUCCESS with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Success
'
Using context: Jenkins Unit Test Run
[WS-CLEANUP] Deleting project workspace...
[WS-CLEANUP] Deferred wipeout is used...
[WS-CLEANUP] done
Finished: SUCCESS

@alecgunny  you can see some description in my previous PR https://github.com/NVIDIA/NVTabular/pull/6
at a high level, I discovered that data ordering highly affect final accuracy. Needed to shuffle the data. Also, match train/valid split methodology with fast.ai, so that the result is comparable. Also, few other minor things such as LR, multi-round fine tuning and certainly, the corporate logo and template.
Sorry I'm a bit tight on time and don't have time for the minor touch up. Pls feel free to edit further after the merge. Thanks.

Click to view CI ResultsGitHub pull request #9 of commit 2c85b06f9a9575a8a871cb0825e5b07bcfc829de, no merge conflicts.
Running as SYSTEM
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to PENDING with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/NVTabular Tests
using credential infra_1
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
 > git --version # timeout=10
using GIT_SSH to set credentials creds for infrastructure pipeline on public nvtabular repo
 > git fetch --tags --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/9/*:refs/remotes/origin/pr/9/* # timeout=10
 > git rev-parse 2c85b06f9a9575a8a871cb0825e5b07bcfc829de^{commit} # timeout=10
Checking out Revision 2c85b06f9a9575a8a871cb0825e5b07bcfc829de (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
Commit message: "modify embedding size"
 > git rev-list --no-walk 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
[NVTabular Tests] $ /bin/bash /tmp/jenkins7060828907989777624.sh
All done! ✨ 🍰 ✨
23 files would be left unchanged.
Skipped 3 files
============================= test session starts ==============================
platform linux -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: /var/jenkins_home/workspace/nvtabular, inifile: setup.cfg
plugins: hypothesis-5.13.1, cov-2.8.1
collected 268 items
tests/unit/test_encoder.py ..............................                [ 11%]
tests/unit/test_groupby.py ............................................. [ 27%]
...                                                                      [ 29%]
tests/unit/test_io.py ...                                                [ 30%]
tests/unit/test_ops.py ................................................. [ 48%]
............                                                             [ 52%]
tests/unit/test_tf_dataloader.py ......                                  [ 55%]
tests/unit/test_torch_dataloader.py .................................... [ 68%]
......                                                                   [ 70%]
tests/unit/test_workflow.py ............................................ [ 87%]
..................................                                       [100%]
----------- coverage: platform linux, python 3.7.6-final-0 -----------
Name                            Stmts   Miss Branch BrPart  Cover   Missing
nvtabular/init.py               6      0      0      0   100%
nvtabular/ds_writer.py             85      5     34      6    91%   26-27, 66->67, 67, 73->81, 98->99, 99-100, 103->105, 108->106, 117->116
nvtabular/encoder.py              153     25     56     11    77%   75->76, 76, 78->79, 79, 81->82, 82, 84->85, 85, 96->97, 97, 111->114, 138->139, 139, 141->142, 142, 150->153, 153, 162->163, 163, 266-271, 275-288, 304->308, 308
nvtabular/groupby.py              155     25     88     14    82%   75->76, 76, 79->80, 80, 86->87, 87, 90->91, 91, 94->96, 135->136, 136, 176->179, 183->exit, 202->205, 205, 216->219, 219, 236->242, 242-269, 272->273, 273-274, 275->276, 276-277, 291->292, 292-293
nvtabular/io.py                   263     73    104     11    68%   48->49, 49, 53->56, 56, 91, 113->119, 136->137, 137, 140->exit, 167->170, 187->198, 195->197, 272->273, 273, 281-287, 322->323, 323, 324->325, 325, 427-450, 453-468, 473-486, 489-511, 514-517, 521-529
nvtabular/ops.py                  441     93    108     12    75%   62->61, 93-97, 112->114, 393->396, 396, 475->476, 476, 479->480, 480-485, 511-512, 557-562, 566-567, 585->586, 586, 612->613, 613, 642->643, 643, 650->649, 693->694, 694, 724->725, 725, 785-794, 797-843, 848-850, 853, 856-857, 860-862, 925-932, 936, 949-957, 1040->1041, 1041, 1053-1057, 1060, 1065-1069
nvtabular/tf_dataloader.py        118     26     44     10    72%   17->19, 28-29, 32->35, 35-37, 72-77, 182->183, 183-184, 192->193, 193, 195->198, 198-201, 202->205, 205, 213->214, 214-217, 226->230, 257->258, 258, 263-264, 275->276, 276, 308
nvtabular/torch_dataloader.py     154     22     64     14    80%   47, 70->71, 71, 73->74, 74-75, 82-85, 91->92, 92-93, 101-102, 106->107, 107, 124->126, 130-134, 162->164, 164->166, 166->exit, 171->172, 172, 192->193, 193, 195->198, 238, 274->276, 276->277, 277, 278->279, 279, 294, 299
nvtabular/workflow.py             464     73    244     25    82%   32-33, 143->149, 149, 152-160, 188-190, 204-206, 220-222, 236-238, 263->264, 264, 315->317, 335->337, 347->348, 348, 384-394, 403->404, 404, 427->424, 484->485, 485, 494->495, 495-496, 503->506, 506, 536->539, 539, 550-553, 568->564, 573->574, 574, 597->598, 598, 682->683, 683-690, 736->738, 738->740, 740->741, 741-742, 743->753, 753, 761->763, 763->764, 764, 816->817, 817, 821->822, 822-828, 834->839, 839-842, 848->851, 851, 955-959
setup.py                            2      2      0      0     0%   18-20
TOTAL                            1841    344    742    103    78%
Coverage XML written to file coverage.xml
Required test coverage of 70% reached. Total coverage: 77.74%
======================= 268 passed in 150.84s (0:02:30) ========================
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to SUCCESS with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Success
'
Using context: Jenkins Unit Test Run
GitHub pull request #9 of commit 2c85b06f9a9575a8a871cb0825e5b07bcfc829de, no merge conflicts.
Running as SYSTEM
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to PENDING with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/NVTabular Tests
using credential infra_1

git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
git --version # timeout=10
using GIT_SSH to set credentials creds for infrastructure pipeline on public nvtabular repo
git fetch --tags --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/9/:refs/remotes/origin/pr/9/ # timeout=10
git rev-parse 2c85b06f9a9575a8a871cb0825e5b07bcfc829de^{commit} # timeout=10
Checking out Revision 2c85b06f9a9575a8a871cb0825e5b07bcfc829de (detached)
git config core.sparsecheckout # timeout=10
git checkout -f 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
Commit message: "modify embedding size"
git rev-list --no-walk 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
[NVTabular Tests] $ /bin/bash /tmp/jenkins7060828907989777624.sh
All done! ??? ???? ???
23 files would be left unchanged.
Skipped 3 files
============================= test session starts ==============================
platform linux -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: /var/jenkins_home/workspace/nvtabular, inifile: setup.cfg
plugins: hypothesis-5.13.1, cov-2.8.1
collected 268 items

tests/unit/test_encoder.py ..............................                [ 11%]
tests/unit/test_groupby.py ............................................. [ 27%]
...                                                                      [ 29%]
tests/unit/test_io.py ...                                                [ 30%]
tests/unit/test_ops.py ................................................. [ 48%]
............                                                             [ 52%]
tests/unit/test_tf_dataloader.py ......                                  [ 55%]
tests/unit/test_torch_dataloader.py .................................... [ 68%]
......                                                                   [ 70%]
tests/unit/test_workflow.py ............................................ [ 87%]
..................................                                       [100%]
----------- coverage: platform linux, python 3.7.6-final-0 -----------
Name                            Stmts   Miss Branch BrPart  Cover   Missing
nvtabular/init.py               6      0      0      0   100%
nvtabular/ds_writer.py             85      5     34      6    91%   26-27, 66->67, 67, 73->81, 98->99, 99-100, 103->105, 108->106, 117->116
nvtabular/encoder.py              153     25     56     11    77%   75->76, 76, 78->79, 79, 81->82, 82, 84->85, 85, 96->97, 97, 111->114, 138->139, 139, 141->142, 142, 150->153, 153, 162->163, 163, 266-271, 275-288, 304->308, 308
nvtabular/groupby.py              155     25     88     14    82%   75->76, 76, 79->80, 80, 86->87, 87, 90->91, 91, 94->96, 135->136, 136, 176->179, 183->exit, 202->205, 205, 216->219, 219, 236->242, 242-269, 272->273, 273-274, 275->276, 276-277, 291->292, 292-293
nvtabular/io.py                   263     73    104     11    68%   48->49, 49, 53->56, 56, 91, 113->119, 136->137, 137, 140->exit, 167->170, 187->198, 195->197, 272->273, 273, 281-287, 322->323, 323, 324->325, 325, 427-450, 453-468, 473-486, 489-511, 514-517, 521-529
nvtabular/ops.py                  441     93    108     12    75%   62->61, 93-97, 112->114, 393->396, 396, 475->476, 476, 479->480, 480-485, 511-512, 557-562, 566-567, 585->586, 586, 612->613, 613, 642->643, 643, 650->649, 693->694, 694, 724->725, 725, 785-794, 797-843, 848-850, 853, 856-857, 860-862, 925-932, 936, 949-957, 1040->1041, 1041, 1053-1057, 1060, 1065-1069
nvtabular/tf_dataloader.py        118     26     44     10    72%   17->19, 28-29, 32->35, 35-37, 72-77, 182->183, 183-184, 192->193, 193, 195->198, 198-201, 202->205, 205, 213->214, 214-217, 226->230, 257->258, 258, 263-264, 275->276, 276, 308
nvtabular/torch_dataloader.py     154     22     64     14    80%   47, 70->71, 71, 73->74, 74-75, 82-85, 91->92, 92-93, 101-102, 106->107, 107, 124->126, 130-134, 162->164, 164->166, 166->exit, 171->172, 172, 192->193, 193, 195->198, 238, 274->276, 276->277, 277, 278->279, 279, 294, 299
nvtabular/workflow.py             464     73    244     25    82%   32-33, 143->149, 149, 152-160, 188-190, 204-206, 220-222, 236-238, 263->264, 264, 315->317, 335->337, 347->348, 348, 384-394, 403->404, 404, 427->424, 484->485, 485, 494->495, 495-496, 503->506, 506, 536->539, 539, 550-553, 568->564, 573->574, 574, 597->598, 598, 682->683, 683-690, 736->738, 738->740, 740->741, 741-742, 743->753, 753, 761->763, 763->764, 764, 816->817, 817, 821->822, 822-828, 834->839, 839-842, 848->851, 851, 955-959
setup.py                            2      2      0      0     0%   18-20
TOTAL                            1841    344    742    103    78%
Coverage XML written to file coverage.xml
Required test coverage of 70% reached. Total coverage: 77.74%
======================= 268 passed in 150.84s (0:02:30) ========================
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to SUCCESS with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Success
'
Using context: Jenkins Unit Test Run
[WS-CLEANUP] Deleting project workspace...
[WS-CLEANUP] Deferred wipeout is used...
[WS-CLEANUP] done
Finished: SUCCESS

Click to view CI ResultsGitHub pull request #9 of commit 2c85b06f9a9575a8a871cb0825e5b07bcfc829de, no merge conflicts.
Running as SYSTEM
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to PENDING with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/NVTabular Tests
using credential infra_1
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
 > git --version # timeout=10
using GIT_SSH to set credentials creds for infrastructure pipeline on public nvtabular repo
 > git fetch --tags --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/9/*:refs/remotes/origin/pr/9/* # timeout=10
 > git rev-parse 2c85b06f9a9575a8a871cb0825e5b07bcfc829de^{commit} # timeout=10
Checking out Revision 2c85b06f9a9575a8a871cb0825e5b07bcfc829de (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
Commit message: "modify embedding size"
 > git rev-list --no-walk 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
[NVTabular Tests] $ /bin/bash /tmp/jenkins7060828907989777624.sh
All done! ✨ 🍰 ✨
23 files would be left unchanged.
Skipped 3 files
============================= test session starts ==============================
platform linux -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: /var/jenkins_home/workspace/nvtabular, inifile: setup.cfg
plugins: hypothesis-5.13.1, cov-2.8.1
collected 268 items
tests/unit/test_encoder.py ..............................                [ 11%]
tests/unit/test_groupby.py ............................................. [ 27%]
...                                                                      [ 29%]
tests/unit/test_io.py ...                                                [ 30%]
tests/unit/test_ops.py ................................................. [ 48%]
............                                                             [ 52%]
tests/unit/test_tf_dataloader.py ......                                  [ 55%]
tests/unit/test_torch_dataloader.py .................................... [ 68%]
......                                                                   [ 70%]
tests/unit/test_workflow.py ............................................ [ 87%]
..................................                                       [100%]
----------- coverage: platform linux, python 3.7.6-final-0 -----------
Name                            Stmts   Miss Branch BrPart  Cover   Missing
nvtabular/init.py               6      0      0      0   100%
nvtabular/ds_writer.py             85      5     34      6    91%   26-27, 66->67, 67, 73->81, 98->99, 99-100, 103->105, 108->106, 117->116
nvtabular/encoder.py              153     25     56     11    77%   75->76, 76, 78->79, 79, 81->82, 82, 84->85, 85, 96->97, 97, 111->114, 138->139, 139, 141->142, 142, 150->153, 153, 162->163, 163, 266-271, 275-288, 304->308, 308
nvtabular/groupby.py              155     25     88     14    82%   75->76, 76, 79->80, 80, 86->87, 87, 90->91, 91, 94->96, 135->136, 136, 176->179, 183->exit, 202->205, 205, 216->219, 219, 236->242, 242-269, 272->273, 273-274, 275->276, 276-277, 291->292, 292-293
nvtabular/io.py                   263     73    104     11    68%   48->49, 49, 53->56, 56, 91, 113->119, 136->137, 137, 140->exit, 167->170, 187->198, 195->197, 272->273, 273, 281-287, 322->323, 323, 324->325, 325, 427-450, 453-468, 473-486, 489-511, 514-517, 521-529
nvtabular/ops.py                  441     93    108     12    75%   62->61, 93-97, 112->114, 393->396, 396, 475->476, 476, 479->480, 480-485, 511-512, 557-562, 566-567, 585->586, 586, 612->613, 613, 642->643, 643, 650->649, 693->694, 694, 724->725, 725, 785-794, 797-843, 848-850, 853, 856-857, 860-862, 925-932, 936, 949-957, 1040->1041, 1041, 1053-1057, 1060, 1065-1069
nvtabular/tf_dataloader.py        118     26     44     10    72%   17->19, 28-29, 32->35, 35-37, 72-77, 182->183, 183-184, 192->193, 193, 195->198, 198-201, 202->205, 205, 213->214, 214-217, 226->230, 257->258, 258, 263-264, 275->276, 276, 308
nvtabular/torch_dataloader.py     154     22     64     14    80%   47, 70->71, 71, 73->74, 74-75, 82-85, 91->92, 92-93, 101-102, 106->107, 107, 124->126, 130-134, 162->164, 164->166, 166->exit, 171->172, 172, 192->193, 193, 195->198, 238, 274->276, 276->277, 277, 278->279, 279, 294, 299
nvtabular/workflow.py             464     73    244     25    82%   32-33, 143->149, 149, 152-160, 188-190, 204-206, 220-222, 236-238, 263->264, 264, 315->317, 335->337, 347->348, 348, 384-394, 403->404, 404, 427->424, 484->485, 485, 494->495, 495-496, 503->506, 506, 536->539, 539, 550-553, 568->564, 573->574, 574, 597->598, 598, 682->683, 683-690, 736->738, 738->740, 740->741, 741-742, 743->753, 753, 761->763, 763->764, 764, 816->817, 817, 821->822, 822-828, 834->839, 839-842, 848->851, 851, 955-959
setup.py                            2      2      0      0     0%   18-20
TOTAL                            1841    344    742    103    78%
Coverage XML written to file coverage.xml
Required test coverage of 70% reached. Total coverage: 77.74%
======================= 268 passed in 150.84s (0:02:30) ========================
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to SUCCESS with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Success
'
Using context: Jenkins Unit Test Run
GitHub pull request #9 of commit 2c85b06f9a9575a8a871cb0825e5b07bcfc829de, no merge conflicts.
Running as SYSTEM
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to PENDING with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/NVTabular Tests
using credential infra_1

git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
git --version # timeout=10
using GIT_SSH to set credentials creds for infrastructure pipeline on public nvtabular repo
git fetch --tags --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/9/:refs/remotes/origin/pr/9/ # timeout=10
git rev-parse 2c85b06f9a9575a8a871cb0825e5b07bcfc829de^{commit} # timeout=10
Checking out Revision 2c85b06f9a9575a8a871cb0825e5b07bcfc829de (detached)
git config core.sparsecheckout # timeout=10
git checkout -f 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
Commit message: "modify embedding size"
git rev-list --no-walk 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
[NVTabular Tests] $ /bin/bash /tmp/jenkins7060828907989777624.sh
All done! ??? ???? ???
23 files would be left unchanged.
Skipped 3 files
============================= test session starts ==============================
platform linux -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: /var/jenkins_home/workspace/nvtabular, inifile: setup.cfg
plugins: hypothesis-5.13.1, cov-2.8.1
collected 268 items

tests/unit/test_encoder.py ..............................                [ 11%]
tests/unit/test_groupby.py ............................................. [ 27%]
...                                                                      [ 29%]
tests/unit/test_io.py ...                                                [ 30%]
tests/unit/test_ops.py ................................................. [ 48%]
............                                                             [ 52%]
tests/unit/test_tf_dataloader.py ......                                  [ 55%]
tests/unit/test_torch_dataloader.py .................................... [ 68%]
......                                                                   [ 70%]
tests/unit/test_workflow.py ............................................ [ 87%]
..................................                                       [100%]
----------- coverage: platform linux, python 3.7.6-final-0 -----------
Name                            Stmts   Miss Branch BrPart  Cover   Missing
nvtabular/init.py               6      0      0      0   100%
nvtabular/ds_writer.py             85      5     34      6    91%   26-27, 66->67, 67, 73->81, 98->99, 99-100, 103->105, 108->106, 117->116
nvtabular/encoder.py              153     25     56     11    77%   75->76, 76, 78->79, 79, 81->82, 82, 84->85, 85, 96->97, 97, 111->114, 138->139, 139, 141->142, 142, 150->153, 153, 162->163, 163, 266-271, 275-288, 304->308, 308
nvtabular/groupby.py              155     25     88     14    82%   75->76, 76, 79->80, 80, 86->87, 87, 90->91, 91, 94->96, 135->136, 136, 176->179, 183->exit, 202->205, 205, 216->219, 219, 236->242, 242-269, 272->273, 273-274, 275->276, 276-277, 291->292, 292-293
nvtabular/io.py                   263     73    104     11    68%   48->49, 49, 53->56, 56, 91, 113->119, 136->137, 137, 140->exit, 167->170, 187->198, 195->197, 272->273, 273, 281-287, 322->323, 323, 324->325, 325, 427-450, 453-468, 473-486, 489-511, 514-517, 521-529
nvtabular/ops.py                  441     93    108     12    75%   62->61, 93-97, 112->114, 393->396, 396, 475->476, 476, 479->480, 480-485, 511-512, 557-562, 566-567, 585->586, 586, 612->613, 613, 642->643, 643, 650->649, 693->694, 694, 724->725, 725, 785-794, 797-843, 848-850, 853, 856-857, 860-862, 925-932, 936, 949-957, 1040->1041, 1041, 1053-1057, 1060, 1065-1069
nvtabular/tf_dataloader.py        118     26     44     10    72%   17->19, 28-29, 32->35, 35-37, 72-77, 182->183, 183-184, 192->193, 193, 195->198, 198-201, 202->205, 205, 213->214, 214-217, 226->230, 257->258, 258, 263-264, 275->276, 276, 308
nvtabular/torch_dataloader.py     154     22     64     14    80%   47, 70->71, 71, 73->74, 74-75, 82-85, 91->92, 92-93, 101-102, 106->107, 107, 124->126, 130-134, 162->164, 164->166, 166->exit, 171->172, 172, 192->193, 193, 195->198, 238, 274->276, 276->277, 277, 278->279, 279, 294, 299
nvtabular/workflow.py             464     73    244     25    82%   32-33, 143->149, 149, 152-160, 188-190, 204-206, 220-222, 236-238, 263->264, 264, 315->317, 335->337, 347->348, 348, 384-394, 403->404, 404, 427->424, 484->485, 485, 494->495, 495-496, 503->506, 506, 536->539, 539, 550-553, 568->564, 573->574, 574, 597->598, 598, 682->683, 683-690, 736->738, 738->740, 740->741, 741-742, 743->753, 753, 761->763, 763->764, 764, 816->817, 817, 821->822, 822-828, 834->839, 839-842, 848->851, 851, 955-959
setup.py                            2      2      0      0     0%   18-20
TOTAL                            1841    344    742    103    78%
Coverage XML written to file coverage.xml
Required test coverage of 70% reached. Total coverage: 77.74%
======================= 268 passed in 150.84s (0:02:30) ========================
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to SUCCESS with url https://<IP_ADDRESS>:8080/job/NVTabular Tests/23 and message: 'Success
'
Using context: Jenkins Unit Test Run
[WS-CLEANUP] Deleting project workspace...
[WS-CLEANUP] Deferred wipeout is used...
[WS-CLEANUP] done
Finished: SUCCESS

rerun tests

rerun tests

rerun tests

rerun tests

rerun tests

Click to view CI ResultsGitHub pull request #9 of commit 2c85b06f9a9575a8a871cb0825e5b07bcfc829de, no merge conflicts.
Running as SYSTEM
Setting status of 2c85b06f9a9575a8a871cb0825e5b07bcfc829de to PENDING with url http://<IP_ADDRESS>:8080/job/nvtabular_tests/4/ and message: 'Pending'
Using context: Jenkins Unit Test Run
Building in workspace /var/jenkins_home/workspace/nvtabular_tests
using credential infra_1
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA/NVTabular.git # timeout=10
Fetching upstream changes from https://github.com/NVIDIA/NVTabular.git
 > git --version # timeout=10
using GIT_SSH to set credentials creds for infrastructure pipeline on public nvtabular repo
 > git fetch --tags --progress -- https://github.com/NVIDIA/NVTabular.git +refs/pull/9/*:refs/remotes/origin/pr/9/* # timeout=10
 > git rev-parse 2c85b06f9a9575a8a871cb0825e5b07bcfc829de^{commit} # timeout=10
Checking out Revision 2c85b06f9a9575a8a871cb0825e5b07bcfc829de (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
Commit message: "modify embedding size"
 > git rev-list --no-walk 2c85b06f9a9575a8a871cb0825e5b07bcfc829de # timeout=10
[nvtabular_tests] $ /bin/bash /tmp/jenkins5666695475133043982.sh
No Path provided. Nothing to do 😴
Skipped 3 files
============================= test session starts ==============================
platform linux -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: /var/jenkins_home/workspace/nvtabular, inifile: setup.cfg
plugins: hypothesis-5.13.1, cov-2.8.1
collected 268 items
tests/unit/test_encoder.py ..............................                [ 11%]
tests/unit/test_groupby.py ............................................. [ 27%]
...                                                                      [ 29%]
tests/unit/test_io.py ...                                                [ 30%]
tests/unit/test_ops.py ................................................. [ 48%]
............                                                             [ 52%]
tests/unit/test_tf_dataloader.py ......                                  [ 55%]
tests/unit/test_torch_dataloader.py .................................... [ 68%]
......                                                                   [ 70%]
tests/unit/test_workflow.py ............................................ [ 87%]
..................................                                       [100%]
----------- coverage: platform linux, python 3.7.6-final-0 -----------
Name                            Stmts   Miss Branch BrPart  Cover   Missing
nvtabular/init.py               6      0      0      0   100%
nvtabular/ds_writer.py             85      5     34      6    91%   26-27, 66->67, 67, 73->81, 98->99, 99-100, 103->105, 108->106, 117->116
nvtabular/encoder.py              153     25     56     11    77%   75->76, 76, 78->79, 79, 81->82, 82, 84->85, 85, 96->97, 97, 111->114, 138->139, 139, 141->142, 142, 150->153, 153, 162->163, 163, 266-271, 275-288, 304->308, 308
nvtabular/groupby.py              155     25     88     14    82%   75->76, 76, 79->80, 80, 86->87, 87, 90->91, 91, 94->96, 135->136, 136, 176->179, 183->exit, 202->205, 205, 216->219, 219, 236->242, 242-269, 272->273, 273-274, 275->276, 276-277, 291->292, 292-293
nvtabular/io.py                   263     73    104     11    68%   48->49, 49, 53->56, 56, 91, 113->119, 136->137, 137, 140->exit, 167->170, 187->198, 195->197, 272->273, 273, 281-287, 322->323, 323, 324->325, 325, 427-450, 453-468, 473-486, 489-511, 514-517, 521-529
nvtabular/ops.py                  441     93    108     12    75%   62->61, 93-97, 112->114, 393->396, 396, 475->476, 476, 479->480, 480-485, 511-512, 557-562, 566-567, 585->586, 586, 612->613, 613, 642->643, 643, 650->649, 693->694, 694, 724->725, 725, 785-794, 797-843, 848-850, 853, 856-857, 860-862, 925-932, 936, 949-957, 1040->1041, 1041, 1053-1057, 1060, 1065-1069
nvtabular/tf_dataloader.py        118     26     44     10    72%   17->19, 28-29, 32->35, 35-37, 72-77, 182->183, 183-184, 192->193, 193, 195->198, 198-201, 202->205, 205, 213->214, 214-217, 226->230, 257->258, 258, 263-264, 275->276, 276, 308
nvtabular/torch_dataloader.py     154     22     64     14    80%   47, 70->71, 71, 73->74, 74-75, 82-85, 91->92, 92-93, 101-102, 106->107, 107, 124->126, 130-134, 162->164, 164->166, 166->exit, 171->172, 172, 192->193, 193, 195->198, 238, 274->276, 276->277, 277, 278->279, 279, 294, 299
nvtabular/workflow.py             464     73    244     25    82%   32-33, 143->149, 149, 152-160, 188-190, 204-206, 220-222, 236-238, 263->264, 264, 315->317, 335->337, 347->348, 348, 384-394, 403->404, 404, 427->424, 484->485, 485, 494->495, 495-496, 503->506, 506, 536->539, 539, 550-553, 568->564, 573->574, 574, 597->598, 598, 682->683, 683-690, 736->738, 738->740, 740->741, 741-742, 743->753, 753, 761->763, 763->764, 764, 816->817, 817, 821->822, 822-828, 834->839, 839-842, 848->851, 851, 955-959
setup.py                            2      2      0      0     0%   18-20
TOTAL                            1841    344    742    103    78%
Coverage XML written to file coverage.xml
Required test coverage of 70% reached. Total coverage: 77.74%
======================= 268 passed in 151.59s (0:02:31) ========================
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script  : #!/bin/bash
source activate rapids
cd /var/jenkins_home/
python test_res_push.py "https://api.GitHub.com/repos/NVIDIA/NVTabular/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[nvtabular_tests] $ /bin/bash /tmp/jenkins7320321154203096443.sh

rerun tests

rerun tests

rerun tests

I'm working on a pure PyTorch version of the Rossmann notebook so I had a chance to look through this.
Great work overall.
Here's a (possibly incomplete) list of changes:

The NVIDIA copyright + logo was added
The DATA_DIR was changed from /data to ./data
The batch size is reduced from 65536 to 512
Target limits are specified (the output of the model is restricted by using a sigmoid function and scaling that sigmoid function to certain limits)
The FastAI embedding-size rule is adopted (which differs from the current NVTabular rule)
The same training cell was run multiple times within the notebook using hard-coded constants rather than the previously-defined constants. So if someone runs this notebook, they will note achieve the displayed performance.

It's worth noting that

the batch size reduction is key to the better task performance
the batch size reduction hurts runtime performance (10x slower)

looks like a comprehensive list of changes. Thanks @rdipietro  :)
were you able to reproduce the results?

Thank you @vinhngx !
One more significant change: the preprocessing notebook was modified to make the training set larger and the validation set smaller (such that validation size = test size). I haven't yet experimented to see how significant this change is to the better result.
When I ran the notebook, the first 5 epochs got to 11% RMSPE, and the next 5 epochs did not improve the result further. In other words, the result after 5 epochs seems pretty solid, and I'm wondering if the next 5 epochs with a smaller learning rate are even needed.
I'll continue to look at this on Monday. The biggest question to be addressed is whether we can maintain low RMSPE without taking the runtime-performance hit (right now 10-20x slower)

I'm working on a pure PyTorch version of the Rossmann notebook so I had a chance to look through this.
Great work overall.
Here's a (possibly incomplete) list of changes:

The NVIDIA copyright + logo was added
The DATA_DIR was changed from /data to ./data
The batch size was reduced from 65536 to 512
Target limits were specified (the output of the model is restricted by using a sigmoid function and scaling that sigmoid function to certain limits)
The FastAI embedding-size rule was adopted (which differs from the current NVTabular rule)
Training is run for two 5-epoch cycles, once with a learning rate of 0.001 and once with a learning rate of 0.0001, using hard-coded constants rather than the previously-defined constants

It's worth noting that

the batch size reduction is key to better task performance
the batch size reduction hurts runtime performance (10x slower)

One extra change is calculation of exp_rmspe metric. @rdipietro is already noticed that I believe :)

I think the batch size reduction issue gets to the heart of the question of what we want these notebooks to be:

should they be sanity checks/proof that everything we're doing is mathematically correct?
should they be illustrative examples of GPU recommender training best practices?

The answer is obviously some combination of both, but deciding where to be on that spectrum is important. Personally, I would rather use larger batch sizes and see slower convergence (or even better, use learning rate scheduling to get parity at larger batch sizes) in order to reinforce the idea that good GPU DL training practices require using as large a batch size as you can, with the rest of the hyperparameters tuned to this batch size.

Ideally if we can find a training recipe for large batch size that can
retain good accuracy that would be the perfect scenario.
On Sat, 20 Jun 2020, 2:00 am Alec Gunny<EMAIL_ADDRESS>wrote:

I think the batch size reduction issue gets to the heart of the question
of what we want these notebooks to be:

should they be sanity checks/proof that everything we're doing is
mathematically correct?
should they be illustrative examples of GPU recommender training
best practices?

The answer is obviously some combination of both, but deciding where to be
on that spectrum is important. Personally, I would rather use larger batch
sizes and see slower convergence (or even better, use learning rate
scheduling to get parity at larger batch sizes) in order to reinforce the
idea that good GPU DL training practices require using as large a batch
size as you can, with the rest of the hyperparameters tuned to this batch
size.
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On a second thought, this is a tiny dataset by any standard, and training performance is probably not the top concern on anyone's mind, i.e. 2s or 20s isn't that much of a practical difference.
By demoing on this dataset, I think the focus is probably more about a sanity test re. functionality and correctness (i.e. final accuracy), with performance a bonus (if we can find the relevant hyper params). Thoughts?

So to your first point, I don't think the issue is necessarily how long people need to wait for this dataset to fit, and I agree that 2s vs. 20s is not a big deal for the person sitting at the notebook. The issue to me is indicating to them that that is not a good practice for GPU training since for a larger dataset, that 20s becomes 20h.
As for the sanity check on functionality and correctness, the top 10 score on the kaggle leaderboard isn't necessarily a function of the correctness of the math of nvtabular, but, as this discussion is indicating, a function of the choice of hyperparameters. You could have a fully correct library and still get a score outside the top 10. So if it's just a sanity check, wouldn't the issue be matching the same model on an already established library on the same hyperparameters? E.g. just running the original FastAI model with the same hps and making sure everything matches? At that point, the actual numbers themselves don't even matter.
Obviously I'm not suggesting that we don't show good scores, the numbers do matter, but that to me indicates that this is more than a sanity check. We want to show not only that GPU-based training works, but that it's valuable, especially because most people aren't going to expend the effort it takes to run the Criteo example.
That said, I'm not going to have the bandwidth to do the hp search, so if we're not ok with slightly lower scores and no one else does then I guess we'll have to live with the lower batch sizes. But my vote would be to keep the lower scores and impart better practices on the reader to exercise on the dataset that really matters: their own.

@alecgunny @vinhngx I've experimented quite a bit with this. I think we have the following two options:

Leave the code pretty much as is, achieving an RMSPE of approx. 11% by training for 10 epochs with a small batch size of 512

Takes about 20 seconds per epoch on a V100
Running this three times led to final RMSPEs of 10.9%, 11.0%, 11.0%

Modify the code to achieve a slightly worse RMSPE of approx. 12% by training for 50 epochs with a large batch size of 65536

Takes about 1 second per epoch on a V100 (approx. 4x faster overall)
Requires using Novograd instead of Adam
Running this three times led to final RMSPEs of 11.9%, 11.5%, 11.8%.

Like @alecgunny, I am hesitant to release a notebook that promotes potentially bad practice (small batch size), and so I tend to lean toward option 2. If we agree on this then I can push these small changes on top of @vinhngx 's work. Thoughts?
One final note: I'd be careful with using the original notebook to claim "Kaggle top 10": 10.8% RMSPE is top 10 on the private leaderboard, but 9.5% is top 10 on the public leaderboard. And since we can tune to this validation set, our results are more comparable with the public leaderboard.

Thanks @rdipietro. Very interesting experiment. How about we expose both options, i.e. small and large batch, with the corresponding best hyper param we've found?
I'd not label small batch as a "bad" practice per se. There are multiple criteria in evaluating Recsys and the user chooses the right options that suits their goal & scenario.  If they care most about squeezing more accuracy and can afford to wait longer they might find smaller batches suits their goal better. It's an act of balancing over a spectrum of options with advantage/disadvantages attached to each choice.

@vinhngx in my view, exposing multiple options would be too messy. These are introductory notebooks, and they're already complex enough (we're training/evaluating with 2 frameworks, soon to be 3: TensorFlow, FastAI, PyTorch).
IMO small batch size is generally bad practice, because NVTabular is designed more for real use cases than tiny datasets, but I should not be the final say here since I am relatively new to NVTabular and the intentions behind these notebooks. Any thoughts on this @alecgunny @benfred @jperez999 ?

This is a tiny dataset and to me it serves more of a sanity test rather
than to demonstrate great performance.  There is nothing impractical about
waiting for 20s vs 1s. The message here is that we are not sacrificing any
accuracy introducing a new data pipeline while also potentially being
faster.
Then there are much bigger datasets like criteo, outbrain where waiting for
20h vs 1h make much difference. That's where we want to be both fast AND
accurate.
On Fri, 26 Jun 2020, 12:55 am Robert DiPietro<EMAIL_ADDRESS>wrote:

@vinhngx https://github.com/vinhngx in my view, exposing multiple
options would be too messy. These are introductory notebooks, and they're
already complex enough (we're training/evaluating with 2 frameworks, soon
to be 3: TensorFlow, FastAI, PyTorch).
IMO small batch size is generally bad practice, because NVTabular is
designed more for real use cases than tiny datasets, but I should not be
the final say here since I am relatively new to NVTabular and the
intentions behind these notebooks. Any thoughts on this @alecgunny
https://github.com/alecgunny @benfred https://github.com/benfred
@jperez999 https://github.com/jperez999 ?
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I have to agree with @rdipietro, no one should be using small batches and using GPUs, it simply makes no sense from a cost perspective. And I think framing the argument as “small batch and good accuracy” vs. “large batch and worse accuracy” is the exact wrong argument we want to make. This creates the impression that there is no cost effective and high-performing way to use GPUs for tabular DL, which forces users into a false dichotomy. You absolutely CAN use larger batches and reach convergence as quickly smaller batches do, and there’s a large swath of literature that shows how to do this without increasing hyperparameter sensitivity (e.g. using ramping and then decaying learning rate schedules).
These are practices we should research,  document, and encourage just as much as the use of large batches itself. But the fact remains that for production, GPU-based DL applications, batch size should not be viewed as “just another hyperparameter.” Its value should be picked based on cost optimization purposes, with the remaining hyperparameters tuned to this value. To me, any example that doesn’t emphasize this incredibly important point is a DL example that happens to be running on a GPU, but tells you nothing about how DL on GPU ought to be done (which is the role I envision any of the examples our team produces playing).

I agree and also believe that we can do with both large batches and high accuracy, @rdipietro  already did a good job in this direction.
We care a lot about performance, but we have never treated accuracy as a 2nd class citizen. I doubt anyone does. The point here is if you don't make serious effort to reach a reasonable accuracy, you might well overlook problems/bugs in your stack, other than the batchsize itself. Hence a keyword here, sanity.

I guess I just disagree with the idea that optimizing performance requires treating accuracy as a 2nd class citizen, or that that's even an argument we want to be (or have been) making at all. I'm simply suggesting that this example currently doesn't reach comparable validation RMSE because we haven't been able to as exhaustively tune hyperparameters (or learning rate schedules) to the 65536 batch size as that done for the hyperparameters for the 512 batch size (which were given to us with no context for how long they took to settle on). This is not an indictment of our library or of large batch sizes broadly, and I think noting this discrepancy to the reader should more than suffice.
I do agree with your point about using training to validate NVTabular beyond unit tests, but I don't think that's our users/readers' problem. They should be operating under the assumption that we've done this legwork and that they're using a properly functioning library. What matters for them is learning how to effectively use a new library, and presumably a new hardware platform, for tabular DL training. Large batch sizes are an imperative part of that.
I can appreciate the concern that particularly astute readers will notice that our RMSE is higher than those at the top of the Kaggle leaderboard, but that's why I think it's very important to be transparent about this batch size issue and continue to update this example over time with  best practices for large batch training (and continue to hp search as well).

@rdipietro when we convert the rossmann notebook to pure PyT, wondering if we can test TF32  mode on A100 to see how much speed up we get compared to FP32 on V100?

Summary of where we are:

The team agrees that best practices such as large batch size are key in these notebooks, and that we will not release a version with small batch size.
It's possible to achieve 12% RMSPE by using Novograd with large batch size (65536), which is slightly worse than the 11% RMSPE achieved in the current version of the notebook with small batch size (512).

As an aside, note that the top 10 entries on the Kaggle public leaderboard are between 8.9% and 9.5%
As an aside, for the Novograd solution, train for 40 epochs with LR 0.01 and 10 epochs with LR 0.001

However, we were unable to find any TensorFlow compatible Novograd implementations that work here (note that sparse gradient support is required, unlike prior use cases)

What we'll do with this PR is

retain much of @vinhngx 's work that does not have to do with batch size (examples include fixing a PyTorch RMSPE bug, specifying a specific output range for the model, etc.)
maintain a batch size of 65536 and accept the RMSPE that comes along with it
add a TODO for achieving low RMSPE while retaining large batch size (and implementing the solution with all of the frameworks in the notebook)

@rnyak yes (at least I don't see why not)

Thanks @rdipietro for the summary. Sounds all good to me. Will you go ahead and make the modification? Unfortunately I won't have the bandwidth to do further work.

@vinhngx no worries – thank you for your help. I took care of it.
I had to create a new PR since I don't have write access to the branch that this PR was formed from. It's here: https://github.com/NVIDIA/NVTabular/pull/123
Therefore closing this PR


display: table-caption?

Can you please include table-caption?

I was looking for this display property as well.


Shared home emptyDir prevents k8s maintenance, autoscaling, etc.

Suggestion
I want to run a single node of Bitbucket. I don't need shared home, I'm not gonna use it anyway.
The chart only seems to have 2 options for shared-home: emptyDir or persistentVolumeClaim. Even if the volume is not even going to be mounted, it will still be created.
This is causing some issues later, as k8s autoscaler won't evict a pod that has local storage.
It looks like a better solution could be:

Support persistentVolumeClaim for multi-node deployments.
Do not create the shared-home volume at all for single-node deployments. What's the point of an unused emptyDir?

If I'm missing something and there's still some value in that emptyDir, perhaps it would be possible to add a switch that lets us avoid creating this volume?
Product
Bitbucket
Code of Conduct

[X] I agree to follow this project's Code of Conduct

Hey @konrad-garus. Thanks for raising the issue.
For the bitbucket, mounting persistentVolume to shared home is mandatory (regardless of number of bitbucket nodes) as it will store key contents.
emptyDir will mount VM storage to pod however this is ephemeral volume therefore not recommended for production clusters.
For this case, you can use custom persistentVolume for shared home.

If you are already using it for local home, you can re-use this for share home by provide it as customVolume to shared home in values.yaml file.
If you are not using persistentVolume for local home, manually create a PVC first, and provide it as customVolume to both local home and shared home in values.yaml file.

I find this a little strange.
When I just generate the template with no variables (helm template atlassian-data-center/bitbucket), I end up with emptyDir for shared-home in my StatefulSet volumes section, but it's not actually mounted anywhere. So it looks like this:
volumeMounts:
  - name: local-home
    mountPath: "/var/atlassian/application-data/bitbucket"

# ...

volumes:
  - name: local-home
    emptyDir: {}
  - name: shared-home
    emptyDir: {}

Looking at statefulset.yaml, it does seem to all be conditional:
{{- if or .Values.volumes.sharedHome.persistentVolumeClaim.create .Values.volumes.sharedHome.customVolume }}
- name: BITBUCKET_SHARED_HOME
  value: {{ .Values.volumes.sharedHome.mountPath | quote }}
{{- end }}

volumeMounts:
  - name: local-home
    mountPath: {{ .Values.volumes.localHome.mountPath | quote }}
  {{- if or .Values.volumes.sharedHome.persistentVolumeClaim.create .Values.volumes.sharedHome.customVolume }}
  - name: shared-home
    mountPath: {{ .Values.volumes.sharedHome.mountPath | quote }}
    {{- if .Values.volumes.sharedHome.subPath }}
    subPath: {{ .Values.volumes.sharedHome.subPath | quote }}
    {{- end }}
  {{- end }}

I went ahead and deleted shared-home from volumes. My Bitbucket seems to be perfectly happy. The "Storage" admin page is showing shared home at /var/atlassian/application-data/bitbucket/shared - that is a subdirectory of my local home (which is persistent). That's exactly what I wanted.

@konrad-garus right, this works for a single node deployment, but I guess  most things in Atlassian DC Helm charts assume scaling to 2+ replicas. Since shared home needs to be RWX, it needs its own dedicated PVC (or a direct NFS volume).
emptyDir is the default - a runtime volume which is gone when the pod is recreated.

Sure, I understand what it's for in multi-node DC. No questions there. That said, there are valid use cases for running it on a single node. Maybe you just don't need more, maybe it's a staging/test environment, etc.
That emptyDir is the worst of both worlds. It's useless for multi-node (and it's not even mounted!), and it's kind of breaking single-node. I had to patch it so that I could do k8s cluster maintenance, otherwise it couldn't be evicted.

Thanks for detailed explanation. I guess emptyDir here is rather a placeholder. Not sure what the best default is.

How about not generating the shared-home at all?

Hey @konrad-garus thanks for your suggestion.
What @bianchi2 mentioned is correct. The helm chart sets emptyDir as a default volume in case the PVC is not provided (At least to have something to mount).
But for bitbucket, shared home can be located under local home subpath and assuming that PVC was provisioned for local home, what you suggested might be a better option.
I created the PR.

LGTM, thank you!

@jjeongatl  was faster :) I was about to issue a similar PR. @konrad-garus thanks again for detailed explanations.

Hey @konrad-garus PR is merged! I will close the ticket


[DEV-6488] Robustifies osg.image.isReady

plz explain what this PR fix, it's easier when browsing history to understand why and how


Uncaught TypeError: Cannot read property 'default' of undefined in production mode

Versions

nuxt: v2.14.0

This only happen after i build the production using nuxt generate then nuxt start
It works completely fine in development mode, no error, warning what so ever
Now i don't know how to debug this because there's not enough information for me to know what to do :((
I tried to switch targer: '' in nuxt.config.js into static and server but both give the same result
The console give me an infinity loading screen of Nuxt and a error in console:
app.f2d5141.js:2 Uncaught TypeError: Cannot read property 'default' of undefined
at Object.b (app.f2d5141.js:2)
at Module. (app.f2d5141.js:2)
at l (runtime.8ff8709.js:1)
at Object. (app.f2d5141.js:2)
at l (runtime.8ff8709.js:1)
at Object. (app.f2d5141.js:2)
at l (runtime.8ff8709.js:1)
at Module. (app.f2d5141.js:2)
at Module. (app.f2d5141.js:2)
at l (runtime.8ff8709.js:1)
The terminal is clean also
My nuxt.config.js: (There's other configuration like css, axios and stuff, i think those are nothing to do with this problem)
export default {
  mode: 'spa',
  target: 'static',
  server: {
    port: process.env.NODE_ENV == 'development' ? 3010 : process.env.PORT, // default: 3010
    host: process.env.NODE_ENV == 'development' ? 'localhost' : process.env.HOST // default: localhost
  },
  components: true,
  generate: {},
}

Thanks for any of your help <3

Any recommend how i can debug this? everything is clean and that's the only error in the console and i don't know what to do

i solved the problem. the problem is you can't import files like so:
in ~/someDir/index.js
export { default as component1 } from './component1'
export { default as component2 } from './component2'

in component1:
import { component2  } from '~/someDir'
instead, you must use:
import componetn2 from ./component2
meaning you can't import components which their aliases are export at a same place


can only use seata-spring-boot-starter, not use spring-cloud-starter-alibaba-seata?

our project use 2.0.x springboot, but spring-cloud-starter-alibaba-seata 2.2.x RELEASE depend on 2.2.x+ version springboot, we can't to improve springboot version. I see spring-cloud-starter-alibaba-seata code , feign module depend on high version. If  not use this module, my project can run ok?

If you want to use Spring Cloud components like Feigin, Hystrix, etc., you need to depend on spring-cloud-starter-alibaba-seata. spring-cloud-starter-alibaba-seata is compatible with multiple Spring Cloud versions.  https://github.com/alibaba/spring-cloud-alibaba/wiki/版本说明

If you want to use Spring Cloud components like Feigin, Hystrix, etc., you need to depend on spring-cloud-starter-alibaba-seata. spring-cloud-starter-alibaba-seata is compatible with multiple Spring Cloud versions.  https://github.com/alibaba/spring-cloud-alibaba/wiki/版本说明

thanks. I want to use Spring Cloud components, but out project depend on spring2.0.x and cloud Finchley. If we use spring-cloud-starter-alibaba-seata 2.2.x, our project can't to run. I find spring-cloud-loadbalancer jar must depend on heigh version cloud , try to
compatible with heigh Spring Cloud versions, but our springboot2.0.x project can't to compatible with height spring cloud version. only when I improve to springboot version to 2.2.5.RELEASE+, spring-cloud-starter-alibaba-seata 2.2.1.RELEASE can worker well. Do you have some good way to compatible with springboot2.0.x and spring-cloud-starter-alibaba-seata 2.2.1.RELEASE?

thanks. I want to use Spring Cloud components, but out project depend on spring2.0.x and cloud Finchley. If we use spring-cloud-starter-alibaba-seata 2.2.x, our project can't to run. I find spring-cloud-loadbalancer jar must depend on heigh version cloud , try to
compatible with heigh Spring Cloud versions, but our springboot2.0.x project can't to compatible with height spring cloud version. only when I improve to springboot version to 2.2.5.RELEASE+, spring-cloud-starter-alibaba-seata 2.2.1.RELEASE can worker well. Do you have some good way to compatible with springboot2.0.x and spring-cloud-starter-alibaba-seata 2.2.1.RELEASE?

@zhangzl0119 how about spring-cloud-starter-alibaba-seata:2.0.3.RELEASE, but you may need to upgrade to the Seata version.

@zhangzl0119 how about spring-cloud-starter-alibaba-seata:2.0.3.RELEASE, but you may need to upgrade to the Seata version.

@slievrly we  want to use spring-cloud-starter-alibaba-seata 2.2.1.RELEASE, but not worker well with out springboot2.0.x version. So I want to find some way to compatible.

@slievrly we  want to use spring-cloud-starter-alibaba-seata 2.2.1.RELEASE, but not worker well with out springboot2.0.x version. So I want to find some way to compatible.

@zhangzl0119 so the core of the problem is that the Spring Cloud depends on the lowest version of Spring Boot.

@zhangzl0119 so the core of the problem is that the Spring Cloud depends on the lowest version of Spring Boot.

@slievrly I try to remove spring-cloud-loadbalancer code, the lowest version of Spring Boot can run well.

@slievrly I try to remove spring-cloud-loadbalancer code, the lowest version of Spring Boot can run well.


Very bad performance on all platforms except for Redox OS

Describe the bug
After compiling the calculator example in release mode and running it on my Linux machine with wayland, I get very bad performance, horrific input latency.
I don't know what exactly causes it, because the same calculator app on my Redox OS VM works perfectly, without any lag whatsoever.
OS: Arch Linux (up to date)
WM: Sway (Wayland)
To Reproduce
Steps to reproduce the behavior:

Compile and run the calculator example
Try using it

Expected behavior
Should perform better I think.
Screenshots

Note that I am not holding the keys pressed, only short clicks. It only reacts after 1 sec minimum.

For what it's worth, I have the same issue with the widgets demo on x11, using Mesa 20.0.4, and the Intel integrated graphics on a Thinkpad running Ubuntu 20.04.

Duplicate of #179.
The next release will ship with a new rendering backend.

On macOS it looks like this is caused by window.limit_update_rate() which causes minifb to limit the frame rate to no more than 15fps.

I have the same issue on windows 10 home
Intel core i5
Nividia Geforce 940m

Check: https://github.com/redox-os/orbtk/issues/179#issuecomment-640382888

Check: https://github.com/redox-os/orbtk/issues/179#issuecomment-641712743

should be fixed now.


corrected some metadata mismatches

Some updates:

Renamed "rolef" to "role"
Renamed "category" to "classification"
Removed "image_rights" as it is not present in the csv files.

Hi there—thank you for this!
I think that the changes on your branch got propagated into the pull request. However, most of them are fine by me, too
The only one that's odd to me is the creation_date_earliest, creation_date_latest, and acquisition_date are not dates.  I just checked, and they're all either dates or null.  I realize that they're listed as required, and they're null, and that's a problem, but that's an actual problem with the data, not with the datapackage.json.  (We shouldn't have things in our collection where we don't know when we acquired them!)
creation_date is indeed a string, and artist birth/death dates are tricky, since they can be pipe-separated dates, which don't parse as strings.  (If you've got a clever idea for many-to-many in CSV, please, please let me know!)
Would you mind making a couple changes to your pull request?

change those three fields back to 'date'
pull out the mira specific bits for provenance_text and image_url

If you'd rather, I can make your changes directly, rather than via this pull request.
Also—could you add your name to the CONTRIBUTORS file?
Thanks!

@workergnome - yes, I thought when I made the initial pull request it would only relate to the first commit. In any case, I've updated the datapackage.json file as you suggested.

Fantastic!  Thank you so much.

On 8 December 2015 at 12:36, David Newbury<EMAIL_ADDRESS>wrote:

Fantastic! Thank you so much.
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Reply to this email directly or view it on GitHub
https://github.com/cmoa/collection/pull/11#issuecomment-162867926.