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[BUG] Analysis of pytest execution difference between running tests locally vs CI #3228

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dantegd opened this issue Dec 2, 2020 · 1 comment
Closed

[BUG] Analysis of pytest execution difference between running tests locally vs CI #3228

dantegd opened this issue Dec 2, 2020 · 1 comment
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bug Something isn't working inactive-30d tests Unit testing for project

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@dantegd
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dantegd commented Dec 2, 2020

Describe the bug
This issue is not really a bug, but more of a description of the results of a quick analysis of why sometimes some tests that locally work super fast, end up in the list of the slowest pytests by orders of magnitude. It probably does not explain entirely why does this happen since it was a naive fast test. But is a good place to start the analysis, and can serve as a good tool for developers to analyze tests locally and reproduce CI conditions.

The spoiler (TL;DR) of the issue is: pytests that have CPU processing (particularly if it is multi-threaded) get slowed down immensely , up to 2 orders of magnitude, more than pytests that are pure GPU (or close to) bound when a system is loaded by other tasks. CI probably is exhibiting and magnifying this behavior.

This started because locally I was seeing this:

1.00s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-10-50-float32]

while CI showed this:

58.32s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-10-50-float32]

which ended up delaying the merge of #3126

Steps/Code to reproduce bug and full results
I built cuML from source, but using nightly conda packages should work just as well. First I ran the test suite on my workstation (details at the end of the issue, but quick specs: 3950x 16 core CPU, 3080 10GB GPU, 64 GB RAM), and got the usual fast results. Then I created 31 processes that load the CPU (naive simple yes > /dev/null &) and reniced them (with different priorities, but for the worst result it was a negative value) and then ran the test suite. This was to emulate the fact that CI can be very loaded (beyond CPU, the hardware probably is heavily loaded in RAM, bandwidth and disk usage beyond my naive test).

  1. test_kernel_shap_standalone: in this tests kernel shap does l1_regularization using Scikit-learn's lars_path, that even if its only one part of the algorithm, it is not only is CPU based, but is heavily multi threaded.

Results for system without additional load:

1.05s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-100-50-float32]
1.00s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-10-50-float32]
0.97s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-100-50-float32]
0.94s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-10-50-float64]
0.94s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-100-50-float64]
0.92s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-10-50-float32]
0.91s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-100-50-float64]
0.88s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-10-50-float64]
0.47s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-100-20-float64]
0.47s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-100-20-float64]
0.46s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-10-20-float64]
0.45s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-100-20-float32]
0.44s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-100-20-float32]
0.44s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-10-20-float32]
0.43s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-10-20-float32]
0.43s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-10-20-float64]

Results for system with the yes load:

20.17s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-10-50-float64]
19.04s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-100-50-float64]
18.99s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-10-50-float64]
18.31s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-10-50-float32]
18.27s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-100-50-float32]
18.22s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-10-50-float32]
17.99s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-100-50-float32]
17.17s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-100-50-float64]
12.57s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-10-20-float32]
12.00s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-100-20-float32]
11.73s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-100-20-float32]
11.38s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-10-20-float64]
11.04s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[PCA-100-20-float64]
10.54s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-100-20-float64]
9.47s call     cuml/test/experimental/test_explainer_kernel_shap.py::test_kernel_shap_standalone[TruncatedSVD-10-20-float64]
  1. test_explainer_permutation_shap: permutation SHAP is pretty much pure GPU code when explaining cuML models, so this contrasts siginificantly with the above.

Results with no load:

0.57s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-50-50-float64]
0.35s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-10-50-float64]
0.25s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-50-11-float64]
0.24s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-50-50-float32]
0.23s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-10-11-float64]
0.21s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-50-50-float64]
0.20s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-10-50-float32]
0.19s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-10-11-float32]
0.18s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-50-11-float32]
0.17s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-10-50-float64]
0.17s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-50-50-float32]
0.17s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-50-11-float64]
0.17s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-10-11-float32]
0.17s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-10-50-float32]
0.16s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-50-11-float32]
0.16s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-10-11-float64]

Results with yes load:

0.54s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-10-50-float64]
0.50s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-50-50-float64]
0.43s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-10-50-float64]
0.39s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-50-11-float64]
0.38s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-10-11-float32]
0.36s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-10-11-float64]
0.35s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-50-50-float32]
0.35s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-50-11-float32]
0.32s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-50-50-float32]
0.31s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-SVR-10-50-float32]
0.27s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-10-11-float32]
0.27s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-10-11-float64]
0.27s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-10-50-float32]
0.26s call     cuml/test/experimental/test_explainer_permutation_shap.py::test_different_parameters[50-LinearRegression-50-11-float64]

As can be seen, there is some impact on the permutation SHAP (pure GPU based) pytests, but the impact on Kernel SHAP was way higher.

Environment details (please complete the following information):

  • Environment location: Bare metal
  • Linux Distro/Architecture: Ubuntu 20.04
  • GPU Model/Driver: 3080 (laptop with 2070S showed similar behavior, but numbers are from 3080)
  • CUDA: 11.0 (and 10.2 on laptop)
  • Method of cuDF & cuML install: cuDF 0.17 nightly, cuML from source

Additional context
Full environment details:

Click here to see environment details
 **git***
 commit 2e0374f3d4db6d1cf51e0e203239a946a1e6a1c3 (HEAD -> 017-fea-kshap)
 Author: Dante Gama Dessavre <[email protected]>
 Date:   Tue Dec 1 13:55:16 2020 -0600
 
 FIX clang format fixes
 **git submodules***
 
 ***OS Information***
 DISTRIB_ID=Ubuntu
 DISTRIB_RELEASE=20.04
 DISTRIB_CODENAME=focal
 DISTRIB_DESCRIPTION="Ubuntu 20.04.1 LTS"
 NAME="Ubuntu"
 VERSION="20.04.1 LTS (Focal Fossa)"
 ID=ubuntu
 ID_LIKE=debian
 PRETTY_NAME="Ubuntu 20.04.1 LTS"
 VERSION_ID="20.04"
 HOME_URL="https://www.ubuntu.com/"
 SUPPORT_URL="https://help.ubuntu.com/"
 BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
 PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
 VERSION_CODENAME=focal
 UBUNTU_CODENAME=focal
 Linux schwifty1 5.4.0-53-generic #59-Ubuntu SMP Wed Oct 21 09:38:44 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux
 
 ***GPU Information***
 Tue Dec  1 18:50:50 2020
 +-----------------------------------------------------------------------------+
 | NVIDIA-SMI 455.23.04    Driver Version: 455.23.04    CUDA Version: 11.1     |
 |-------------------------------+----------------------+----------------------+
 | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
 | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
 |                               |                      |               MIG M. |
 |===============================+======================+======================|
 |   0  GeForce RTX 3080    Off  | 00000000:0B:00.0  On |                  N/A |
 |  0%   56C    P5    31W / 320W |    984MiB /  9984MiB |     16%      Default |
 |                               |                      |                  N/A |
 +-------------------------------+----------------------+----------------------+
 
 +-----------------------------------------------------------------------------+
 | Processes:                                                                  |
 |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
 |        ID   ID                                                   Usage      |
 |=============================================================================|
 |    0   N/A  N/A      1427      G   /usr/lib/xorg/Xorg                192MiB |
 |    0   N/A  N/A      2181      G   /usr/lib/xorg/Xorg                569MiB |
 |    0   N/A  N/A      2309      G   /usr/bin/gnome-shell              128MiB |
 |    0   N/A  N/A     32808      G   .../debug.log --shared-files       15MiB |
 |    0   N/A  N/A     41931      G   ...AAAAAAAA== --shared-files       28MiB |
 +-----------------------------------------------------------------------------+
 
 ***CPU***
 Architecture:                    x86_64
 CPU op-mode(s):                  32-bit, 64-bit
 Byte Order:                      Little Endian
 Address sizes:                   43 bits physical, 48 bits virtual
 CPU(s):                          32
 On-line CPU(s) list:             0-31
 Thread(s) per core:              2
 Core(s) per socket:              16
 Socket(s):                       1
 NUMA node(s):                    1
 Vendor ID:                       AuthenticAMD
 CPU family:                      23
 Model:                           113
 Model name:                      AMD Ryzen 9 3950X 16-Core Processor
 Stepping:                        0
 Frequency boost:                 disabled
 CPU MHz:                         3999.380
 CPU max MHz:                     4700.0000
 CPU min MHz:                     2200.0000
 BogoMIPS:                        7999.42
 Virtualization:                  AMD-V
 L1d cache:                       512 KiB
 L1i cache:                       512 KiB
 L2 cache:                        8 MiB
 L3 cache:                        64 MiB
 NUMA node0 CPU(s):               0-31
 Vulnerability Itlb multihit:     Not affected
 Vulnerability L1tf:              Not affected
 Vulnerability Mds:               Not affected
 Vulnerability Meltdown:          Not affected
 Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
 Vulnerability Spectre v1:        Mitigation; usercopy/swapgs barriers and __user pointer sanitization
 Vulnerability Spectre v2:        Mitigation; Full AMD retpoline, IBPB conditional, STIBP conditional, RSB filling
 Vulnerability Srbds:             Not affected
 Vulnerability Tsx async abort:   Not affected
 Flags:                           fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate sme ssbd mba sev ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr wbnoinvd arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif umip rdpid overflow_recov succor smca
 
 ***CMake***
 /home/galahad/miniconda3/envs/ns1116/bin/cmake
 cmake version 3.18.4
 
 CMake suite maintained and supported by Kitware (kitware.com/cmake).
 
 ***g++***
 /usr/bin/g++
 g++ (Ubuntu 8.4.0-3ubuntu2) 8.4.0
 Copyright (C) 2018 Free Software Foundation, Inc.
 This is free software; see the source for copying conditions.  There is NO
 warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
 
 
 ***nvcc***
 /usr/local/cuda-11.1/bin/nvcc
 nvcc: NVIDIA (R) Cuda compiler driver
 Copyright (c) 2005-2020 NVIDIA Corporation
 Built on Tue_Sep_15_19:10:02_PDT_2020
 Cuda compilation tools, release 11.1, V11.1.74
 Build cuda_11.1.TC455_06.29069683_0
 
 ***Python***
 /home/galahad/miniconda3/envs/ns1116/bin/python
 Python 3.8.6
 
 ***Environment Variables***
 PATH                            : /usr/local/cuda-11.1/bin:/usr/local/cuda-11.1/NsightCompute-2020.3.2:/home/galahad/miniconda3/envs/ns1116/bin:/home/galahad/miniconda3/condabin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin
 LD_LIBRARY_PATH                 : /usr/local/cuda-11.1/lib64
 NUMBAPRO_NVVM                   :
 NUMBAPRO_LIBDEVICE              :
 CONDA_PREFIX                    : /home/galahad/miniconda3/envs/ns1116
 PYTHON_PATH                     :
 
 ***conda packages***
 /home/galahad/miniconda3/envs/ns1116/bin/conda
 # packages in environment at /home/galahad/miniconda3/envs/ns1116:
 #
 # Name                    Version                   Build  Channel
 _libgcc_mutex             0.1                 conda_forge    conda-forge
 _openmp_mutex             4.5                      1_llvm    conda-forge
 abseil-cpp                20200225.2           he1b5a44_2    conda-forge
 aiohttp                   3.7.2            py38h1e0a361_0    conda-forge
 alabaster                 0.7.12                     py_0    conda-forge
 appdirs                   1.4.4              pyh9f0ad1d_0    conda-forge
 argon2-cffi               20.1.0           py38h25fe258_2    conda-forge
 arrow-cpp                 1.0.1           py38h9444e92_15_cuda    conda-forge
 arrow-cpp-proc            2.0.0                      cuda    conda-forge
 asn1crypto                1.4.0              pyh9f0ad1d_0    conda-forge
 async-timeout             3.0.1                   py_1000    conda-forge
 async_generator           1.10                       py_0    conda-forge
 atk                       2.36.0               ha770c72_4    conda-forge
 atk-1.0                   2.36.0               h0d5b62e_4    conda-forge
 attrs                     20.3.0             pyhd3deb0d_0    conda-forge
 autoconf                  2.69            pl5320h36c2ea0_10    conda-forge
 automake                  1.16.2          pl5320ha770c72_3    conda-forge
 autopep8                  1.5.4              pyh9f0ad1d_0    conda-forge
 aws-c-common              0.4.59               h36c2ea0_1    conda-forge
 aws-c-event-stream        0.1.6                had2084c_6    conda-forge
 aws-checksums             0.1.10               h4e93380_0    conda-forge
 aws-sam-translator        1.27.0             pyh9f0ad1d_0    conda-forge
 aws-sdk-cpp               1.8.70               h57dc084_1    conda-forge
 aws-xray-sdk              0.95                       py_0    conda-forge
 babel                     2.9.0              pyhd3deb0d_0    conda-forge
 backcall                  0.2.0              pyh9f0ad1d_0    conda-forge
 backports                 1.0                        py_2    conda-forge
 backports.functools_lru_cache 1.6.1                      py_0    conda-forge
 backports.tempfile        1.0                        py_0    conda-forge
 backports.weakref         1.0.post1       py38h32f6830_1002    conda-forge
 beautifulsoup4            4.9.3              pyhb0f4dca_0    conda-forge
 benchmark                 1.5.1                he1b5a44_2    conda-forge
 black                     19.10b0                    py_4    conda-forge
 blas                      2.17                   openblas    conda-forge
 bleach                    3.2.1              pyh9f0ad1d_0    conda-forge
 blinker                   1.4                        py_1    conda-forge
 bokeh                     2.2.3            py38h32f6830_0    conda-forge
 boost                     1.72.0           py38h1e42940_1    conda-forge
 boost-cpp                 1.72.0               h8e57a91_0    conda-forge
 boto                      2.49.0                     py_0    conda-forge
 boto3                     1.16.18            pyhd8ed1ab_0    conda-forge
 botocore                  1.19.18            pyhd8ed1ab_0    conda-forge
 brotli                    1.0.9                he1b5a44_3    conda-forge
 brotlipy                  0.7.0           py38h8df0ef7_1001    conda-forge
 bzip2                     1.0.8                h516909a_3    conda-forge
 c-ares                    1.16.1               h516909a_3    conda-forge
 ca-certificates           2020.11.8            ha878542_0    conda-forge
 cachetools                4.1.1                      py_0    conda-forge
 cairo                     1.16.0            hcf35c78_1003    conda-forge
 certifi                   2020.11.8        py38h578d9bd_0    conda-forge
 cffi                      1.14.3           py38h1bdcb99_1    conda-forge
 cfitsio                   3.470                h2e3daa1_7    conda-forge
 cfn-lint                  0.40.0           py38h578d9bd_0    conda-forge
 chardet                   3.0.4           py38h924ce5b_1008    conda-forge
 clang                     8.0.1                hc9558a2_2    conda-forge
 clang-tools               8.0.1                hc9558a2_2    conda-forge
 clangxx                   8.0.1                         2    conda-forge
 click                     7.1.2              pyh9f0ad1d_0    conda-forge
 click-plugins             1.1.1                      py_0    conda-forge
 cligj                     0.7.0                      py_0    conda-forge
 cloudpickle               1.6.0                      py_0    conda-forge
 cmake                     3.18.4               h1f3970d_0    conda-forge
 cmake-format              0.6.11             pyh9f0ad1d_0    conda-forge
 cmake_setuptools          0.1.3                      py_0    rapidsai
 cmarkgfm                  0.4.2            py38h1e0a361_3    conda-forge
 colorama                  0.4.4              pyh9f0ad1d_0    conda-forge
 colorcet                  2.0.1                      py_0    conda-forge
 commonmark                0.9.1                      py_0    conda-forge
 conda                     4.8.3            py38h32f6830_2    conda-forge
 conda-build               3.20.3           py38h32f6830_0    conda-forge
 conda-package-handling    1.7.2            py38h8df0ef7_0    conda-forge
 conda-verify              3.1.1           py38h32f6830_1002    conda-forge
 cookies                   2.2.1                      py_0    conda-forge
 coverage                  5.3              py38h1e0a361_1    conda-forge
 cryptography              3.2.1            py38h7699a38_0    conda-forge
 cudatoolkit               11.0.221             h6bb024c_0    nvidia
 cudf                      0.17.0a201116   cuda_11.0_py38_g21b28ba7bb_262    rapidsai-nightly
 cudnn                     8.0.0                cuda11.0_0    nvidia
 cuml                      0.17.0a0+182.g2170217ba          pypi_0    pypi
 cupy                      7.8.0            py38hb7c6141_0    rapidsai
 curl                      7.71.1               he644dc0_8    conda-forge
 cycler                    0.10.0                     py_2    conda-forge
 cyrus-sasl                2.1.27               h063b49f_1    conda-forge
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 sphinxcontrib-applehelp   1.0.2                      py_0    conda-forge
 sphinxcontrib-devhelp     1.0.2                      py_0    conda-forge
 sphinxcontrib-htmlhelp    1.0.3                      py_0    conda-forge
 sphinxcontrib-jsmath      1.0.1                      py_0    conda-forge
 sphinxcontrib-qthelp      1.0.3                      py_0    conda-forge
 sphinxcontrib-serializinghtml 1.1.4                      py_0    conda-forge
 sphinxcontrib-websupport  1.2.4              pyh9f0ad1d_0    conda-forge
 sqlite                    3.33.0               h4cf870e_1    conda-forge
 sshpubkeys                3.1.0                      py_0    conda-forge
 statsmodels               0.12.1           py38h0b5ebd8_1    conda-forge
 streamz                   0.6.1              pyhd3deb0d_1    conda-forge
 tbb                       2020.2               hc9558a2_0    conda-forge
 tblib                     1.6.0                      py_0    conda-forge
 terminado                 0.9.1            py38h32f6830_1    conda-forge
 testpath                  0.4.4                      py_0    conda-forge
 threadpoolctl             2.1.0              pyh5ca1d4c_0    conda-forge
 tiledb                    1.7.7                h8efa9f0_3    conda-forge
 tk                        8.6.10               hed695b0_1    conda-forge
 toml                      0.10.2             pyhd8ed1ab_0    conda-forge
 toolz                     0.11.1                     py_0    conda-forge
 tornado                   6.1              py38h25fe258_0    conda-forge
 tqdm                      4.52.0             pyhd3deb0d_0    conda-forge
 traitlets                 5.0.5                      py_0    conda-forge
 treelite                  0.93             py38hadf7658_3    conda-forge
 treelite-runtime          0.93                     pypi_0    pypi
 twine                     3.2.0            py38h32f6830_1    conda-forge
 typed-ast                 1.4.1            py38h25fe258_1    conda-forge
 typing-extensions         3.7.4.3                       0    conda-forge
 typing_extensions         3.7.4.3                    py_0    conda-forge
 tzcode                    2020a                h516909a_0    conda-forge
 ucx                       1.8.1+g6b29558       cuda11.0_0    rapidsai
 ucx-proc                  1.0.0                       gpu    rapidsai
 ucx-py                    0.17.0a201116   py38_g6b29558_17    rapidsai-nightly
 umap-learn                0.4.6            py38h32f6830_0    conda-forge
 urllib3                   1.25.11                    py_0    conda-forge
 wcwidth                   0.2.5              pyh9f0ad1d_2    conda-forge
 webencodings              0.5.1                      py_1    conda-forge
 websocket-client          0.57.0           py38h32f6830_3    conda-forge
 websockets                8.1              py38h1e0a361_2    conda-forge
 werkzeug                  1.0.1              pyh9f0ad1d_0    conda-forge
 wheel                     0.35.1             pyh9f0ad1d_0    conda-forge
 widgetsnbextension        3.5.1            py38h578d9bd_4    conda-forge
 wmctrl                    0.3             py38h32f6830_1002    conda-forge
 wrapt                     1.12.1           py38h1e0a361_1    conda-forge
 xarray                    0.16.1                     py_0    conda-forge
 xerces-c                  3.2.2             h8412b87_1004    conda-forge
 xmltodict                 0.12.0                     py_0    conda-forge
 xorg-kbproto              1.0.7             h14c3975_1002    conda-forge
 xorg-libice               1.0.10               h516909a_0    conda-forge
 xorg-libsm                1.2.3             h84519dc_1000    conda-forge
 xorg-libx11               1.6.12               h516909a_0    conda-forge
 xorg-libxau               1.0.9                h14c3975_0    conda-forge
 xorg-libxdmcp             1.1.3                h516909a_0    conda-forge
 xorg-libxext              1.3.4                h516909a_0    conda-forge
 xorg-libxpm               3.5.13               h516909a_0    conda-forge
 xorg-libxrender           0.9.10            h516909a_1002    conda-forge
 xorg-libxt                1.1.5             h516909a_1003    conda-forge
 xorg-renderproto          0.11.1            h14c3975_1002    conda-forge
 xorg-xextproto            7.3.0             h14c3975_1002    conda-forge
 xorg-xproto               7.0.31            h14c3975_1007    conda-forge
 xz                        5.2.5                h516909a_1    conda-forge
 yaml                      0.2.5                h516909a_0    conda-forge
 yarl                      1.6.3            py38h25fe258_0    conda-forge
 zeromq                    4.3.3                h58526e2_2    conda-forge
 zict                      2.0.0                      py_0    conda-forge
 zipp                      3.4.0                      py_0    conda-forge
 zlib                      1.2.11            h516909a_1010    conda-forge
 zstd                      1.4.5                h6597ccf_2    conda-forge

@dantegd dantegd added bug Something isn't working tests Unit testing for project labels Dec 2, 2020
@dantegd dantegd mentioned this issue Dec 2, 2020
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This issue has been marked stale due to no recent activity in the past 30d. Please close this issue if no further response or action is needed. Otherwise, please respond with a comment indicating any updates or changes to the original issue and/or confirm this issue still needs to be addressed. This issue will be marked rotten if there is no activity in the next 60d.

@dantegd dantegd closed this as completed Feb 26, 2021
@lowener lowener mentioned this issue May 25, 2021
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@dantegd dantegd mentioned this issue Apr 2, 2024
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bug Something isn't working inactive-30d tests Unit testing for project
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