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rapidsai / cuml

cuML - RAPIDS Machine Learning Library
https://docs.rapids.ai/api/cuml/stable/
Apache License 2.0
4.27k stars 536 forks source link

[BUG] Could not install cuML via conda on CentOS7 #4342

Open higgteil opened 3 years ago

higgteil commented 3 years ago

Describe the bug Hi, tried to install cuML on a computing cluster via conda in existing environment and then in a new environment. I also tried the advice found here https://github.com/rapidsai/cuml/issues/3108 and used more channels, but everything I tried had no success: conda cannot install the package.

Steps/Code to reproduce bug Minimal example: conda install -c rapidsai cuml Collecting package metadata (current_repodata.json): done Solving environment: failed with initial frozen solve. Retrying with flexible solve. Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source. Collecting package metadata (repodata.json): / I ran the debug script referenced here from one of the developers https://github.com/rapidsai/cuml/issues/3108 (file attached) env.txt

wphicks commented 3 years ago

Could you try the following and let us know if the install fails?

conda create -n rapids-21.10 -c rapidsai -c nvidia -c conda-forge cuml=21.10 python=3.7 cudatoolkit=11.0

For reference, this was taken from the RAPIDS release selector tool which helps generate the exact install command required for your system. If that doesn't work, please do let us know and we can look into it further.

higgteil commented 3 years ago

Could you try the following and let us know if the install fails?

conda create -n rapids-21.10 -c rapidsai -c nvidia -c conda-forge cuml=21.10 python=3.7 cudatoolkit=11.0

For reference, this was taken from the RAPIDS release selector tool which helps generate the exact install command required for your system. If that doesn't work, please do let us know and we can look into it further.

Dear wphicks,

thanks for your answer, I ran the command, but unfortunately it didn't work:

 $ conda create -n rapids-21.10 -c rapidsai -c nvidia -c conda-forge cuml=21.10 python=3.7 cudatoolkit=11.0
Collecting package metadata (current_repodata.json): done
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): | (base) $
dantegd commented 3 years ago

@higgteil that message does not imply that the install has failed, it's just the conda solver working which can take quite a while sometimes. I would recommend using mamba to speed up things, essentially doing this: 

$ conda install -c conda-forge mamba
$ mamba create -n rapids-21.10 -c rapidsai -c nvidia -c conda-forge cuml=21.10 python=3.7 cudatoolkit=11.0

If that doesn't work, then at least it should be way faster at finding the conflict/issue and printing something to help us triage the issue. Thanks!

higgteil commented 3 years ago

@higgteil that message does not imply that the install has failed, it's just the conda solver working which can take quite a while sometimes. I would recommend using mamba to speed up things, essentially doing this:

$ conda install -c conda-forge mamba
$ mamba create -n rapids-21.10 -c rapidsai -c nvidia -c conda-forge cuml=21.10 python=3.7 cudatoolkit=11.0

If that doesn't work, then at least it should be way faster at finding the conflict/issue and printing something to help us triage the issue. Thanks!

You're right! Now, it seems to download and install all the packages, but the verification at the end is terminated with a kill -

Here is the printout from your code:


(base)$ mamba create -n rapids-21.10 -c rapidsai -c nvidia -c conda-forge cuml=21.10 python=3.7 cudatoolkit=11.0

                  __    __    __    __
                 /  \  /  \  /  \  /  \
                /    \/    \/    \/    \
███████████████/  /██/  /██/  /██/  /████████████████████████
              /  / \   / \   / \   / \  \____
             /  /   \_/   \_/   \_/   \    o \__,
            / _/                       \_____/  `
            |/
        ███╗   ███╗ █████╗ ███╗   ███╗██████╗  █████╗
        ████╗ ████║██╔══██╗████╗ ████║██╔══██╗██╔══██╗
        ██╔████╔██║███████║██╔████╔██║██████╔╝███████║
        ██║╚██╔╝██║██╔══██║██║╚██╔╝██║██╔══██╗██╔══██║
        ██║ ╚═╝ ██║██║  ██║██║ ╚═╝ ██║██████╔╝██║  ██║
        ╚═╝     ╚═╝╚═╝  ╚═╝╚═╝     ╚═╝╚═════╝ ╚═╝  ╚═╝

        mamba (0.15.3) supported by @QuantStack

        GitHub:  https://github.com/mamba-org/mamba
        Twitter: https://twitter.com/QuantStack

█████████████████████████████████████████████████████████████

Looking for: ['cuml=21.10', 'python=3.7', 'cudatoolkit=11.0']

nvidia/linux-64          [====================] (00m:00s) Done
rapidsai/noarch          [====================] (00m:00s) Done
nvidia/noarch            [====================] (00m:00s) Done
rapidsai/linux-64        [====================] (00m:00s) Done
default/linux-64         [====================] (00m:00s) Done
pkgs/main/linux-64       [====================] (00m:00s) Done
pkgs/r/linux-64          [====================] (00m:00s) Done
default/noarch           [====================] (00m:00s) Done
pkgs/r/noarch            [====================] (00m:00s) Done
pkgs/main/noarch         [====================] (00m:00s) Done
conda-forge/noarch       [====================] (00m:01s) Done
bioconda/linux-64        [====================] (00m:00s) Done
bioconda/noarch          [====================] (00m:01s) Done
conda-forge/linux-64     [====================] (00m:05s) Done
Transaction

  Prefix: /fast/users/harp/work/miniconda/envs/rapids-21.10

  Updating specs:

   - cuml=21.10
   - python=3.7
   - cudatoolkit=11.0

  Package                       Version  Build                         Channel                     Size
─────────────────────────────────────────────────────────────────────────────────────────────────────────
  Install:
─────────────────────────────────────────────────────────────────────────────────────────────────────────

  + _libgcc_mutex                   0.1  conda_forge                   conda-forge/linux-64      Cached
  + _openmp_mutex                   4.5  1_gnu                         conda-forge/linux-64      Cached
  + abseil-cpp               20210324.2  h9c3ff4c_0                    conda-forge/linux-64     1010 KB
  + arrow-cpp                     5.0.0  py37h38eb46f_11_cuda          conda-forge/linux-64       23 MB
  + arrow-cpp-proc                3.0.0  cuda                          conda-forge/linux-64       24 KB
  + aws-c-auth                    0.6.4  h66ccdbb_3                    conda-forge/linux-64       99 KB
  + aws-c-cal                    0.5.12  hf5774b0_2                    conda-forge/linux-64       36 KB
  + aws-c-common                 0.6.11  h7f98852_0                    conda-forge/linux-64      174 KB
  + aws-c-compression            0.2.14  hcbdb60a_2                    conda-forge/linux-64       16 KB
  + aws-c-event-stream            0.2.7  hb3c4c74_24                   conda-forge/linux-64       47 KB
  + aws-c-http                    0.6.6  h0021954_1                    conda-forge/linux-64      170 KB
  + aws-c-io                     0.10.9  h14fba84_3                    conda-forge/linux-64      121 KB
  + aws-c-mqtt                    0.7.8  h8df633b_2                    conda-forge/linux-64       67 KB
  + aws-c-s3                     0.1.27  h8e2754f_1                    conda-forge/linux-64       48 KB
  + aws-checksums                0.1.12  hcbdb60a_1                    conda-forge/linux-64       50 KB
  + aws-crt-cpp                  0.17.1  hf793bd7_3                    conda-forge/linux-64      204 KB
  + aws-sdk-cpp                 1.9.120  hab07a0e_0                    conda-forge/linux-64        5 MB
  + bokeh                         2.4.1  py37h89c1867_1                conda-forge/linux-64       14 MB
  + bzip2                         1.0.8  h7f98852_4                    conda-forge/linux-64      Cached
  + c-ares                       1.18.1  h7f98852_0                    conda-forge/linux-64      Cached
  + ca-certificates           2021.10.8  ha878542_0                    conda-forge/linux-64      Cached
  + cachetools                    4.2.4  pyhd8ed1ab_0                  conda-forge/noarch         12 KB
  + click                         8.0.3  py37h89c1867_1                conda-forge/linux-64      145 KB
  + cloudpickle                   2.0.0  pyhd8ed1ab_0                  conda-forge/noarch        Cached
  + cudatoolkit                11.0.221  h6bb024c_0                    nvidia/linux-64           953 MB
  + cudf                       21.10.01  cuda_11.0_py37_ga1d2d13a14_0  rapidsai/linux-64          13 MB
  + cuml                       21.10.00  cuda11.0_py37_g0fd3503ba_0    rapidsai/linux-64           9 MB
  + cupy                          9.5.0  py37h6bfc3c5_1                conda-forge/linux-64       50 MB
  + cytoolz                      0.11.2  py37h5e8e339_1                conda-forge/linux-64      407 KB
  + dask                       2021.9.1  pyhd8ed1ab_0                  conda-forge/noarch          4 KB
  + dask-core                  2021.9.1  pyhd8ed1ab_0                  conda-forge/noarch        768 KB
  + dask-cudf                  21.10.01  py37_ga1d2d13a14_0            rapidsai/linux-64         110 KB
  + distributed                2021.9.1  py37h89c1867_0                conda-forge/linux-64        1 MB
  + dlpack                          0.5  h9c3ff4c_0                    conda-forge/linux-64       12 KB
  + faiss-proc                    1.0.0  cuda                          rapidsai/linux-64          24 KB
  + fastavro                      1.4.7  py37h5e8e339_1                conda-forge/linux-64      503 KB
  + fastrlock                       0.8  py37hcd2ae1e_1                conda-forge/linux-64       31 KB
  + freetype                     2.10.4  h0708190_1                    conda-forge/linux-64      Cached
  + fsspec                    2021.11.0  pyhd8ed1ab_0                  conda-forge/noarch        Cached
  + gflags                        2.2.2  he1b5a44_1004                 conda-forge/linux-64      114 KB
  + glog                          0.5.0  h48cff8f_0                    conda-forge/linux-64      104 KB
  + grpc-cpp                     1.40.0  h05f19cf_2                    conda-forge/linux-64        4 MB
  + heapdict                      1.0.1  py_0                          conda-forge/noarch        Cached
  + icu                            69.1  h9c3ff4c_0                    conda-forge/linux-64       13 MB
  + importlib-metadata            4.8.2  py37h89c1867_0                conda-forge/linux-64       32 KB
  + jbig                            2.1  h7f98852_2003                 conda-forge/linux-64      Cached
  + jinja2                        3.0.3  pyhd8ed1ab_0                  conda-forge/noarch         99 KB
  + joblib                        1.1.0  pyhd8ed1ab_0                  conda-forge/noarch        Cached
  + jpeg                             9d  h36c2ea0_0                    conda-forge/linux-64      Cached
  + krb5                         1.19.2  hcc1bbae_3                    conda-forge/linux-64      Cached
  + lcms2                          2.12  hddcbb42_0                    conda-forge/linux-64      Cached
  + ld_impl_linux-64             2.36.1  hea4e1c9_2                    conda-forge/linux-64      Cached
  + lerc                            3.0  h9c3ff4c_0                    conda-forge/linux-64      Cached
  + libblas                       3.9.0  12_linux64_openblas           conda-forge/linux-64      Cached
  + libbrotlicommon               1.0.9  h7f98852_6                    conda-forge/linux-64       65 KB
  + libbrotlidec                  1.0.9  h7f98852_6                    conda-forge/linux-64       33 KB
  + libbrotlienc                  1.0.9  h7f98852_6                    conda-forge/linux-64      286 KB
  + libcblas                      3.9.0  12_linux64_openblas           conda-forge/linux-64      Cached
  + libcudf                    21.10.01  cuda11.0_ga1d2d13a14_0        rapidsai/linux-64         220 MB
  + libcuml                    21.10.00  cuda11.0_g0fd3503ba_0         rapidsai/linux-64         181 MB
  + libcumlprims               21.10.00  cuda11.0_g167dc59_0           nvidia/linux-64             2 MB
  + libcurl                      7.80.0  h2574ce0_0                    conda-forge/linux-64      337 KB
  + libdeflate                      1.8  h7f98852_0                    conda-forge/linux-64      Cached
  + libedit                3.1.20191231  he28a2e2_2                    conda-forge/linux-64      Cached
  + libev                          4.33  h516909a_1                    conda-forge/linux-64      Cached
  + libevent                     2.1.10  h9b69904_4                    conda-forge/linux-64        1 MB
  + libfaiss                      1.7.0  cuda110h8045045_8_cuda        conda-forge/linux-64       67 MB
  + libffi                        3.4.2  h7f98852_5                    conda-forge/linux-64       57 KB
  + libgcc-ng                    11.2.0  h1d223b6_11                   conda-forge/linux-64      Cached
  + libgfortran-ng               11.2.0  h69a702a_11                   conda-forge/linux-64      Cached
  + libgfortran5                 11.2.0  h5c6108e_11                   conda-forge/linux-64      Cached
  + libgomp                      11.2.0  h1d223b6_11                   conda-forge/linux-64      Cached
  + libhwloc                      2.3.0  h5e5b7d1_1                    conda-forge/linux-64        3 MB
  + libiconv                       1.16  h516909a_0                    conda-forge/linux-64      Cached
  + liblapack                     3.9.0  12_linux64_openblas           conda-forge/linux-64      Cached
  + libllvm10                    10.0.1  he513fc3_3                    conda-forge/linux-64      Cached
  + libnghttp2                   1.43.0  h812cca2_1                    conda-forge/linux-64      Cached
  + libnsl                        2.0.0  h7f98852_0                    conda-forge/linux-64       31 KB
  + libopenblas                  0.3.18  pthreads_h8fe5266_0           conda-forge/linux-64      Cached
  + libpng                       1.6.37  h21135ba_2                    conda-forge/linux-64      Cached
  + libprotobuf                  3.18.1  h780b84a_0                    conda-forge/linux-64        3 MB
  + librmm                     21.10.01  cuda11.0_gc54767f_0           rapidsai/linux-64         688 KB
  + libssh2                      1.10.0  ha56f1ee_2                    conda-forge/linux-64      Cached
  + libstdcxx-ng                 11.2.0  he4da1e4_11                   conda-forge/linux-64      Cached
  + libthrift                    0.15.0  he6d91bd_1                    conda-forge/linux-64        5 MB
  + libtiff                       4.3.0  h6f004c6_2                    conda-forge/linux-64      Cached
  + libutf8proc                   2.6.1  h7f98852_0                    conda-forge/linux-64       95 KB
  + libwebp-base                  1.2.1  h7f98852_0                    conda-forge/linux-64      Cached
  + libxml2                      2.9.12  h885dcf4_1                    conda-forge/linux-64      760 KB
  + libzlib                      1.2.11  h36c2ea0_1013                 conda-forge/linux-64      Cached
  + llvmlite                     0.36.0  py37h9d7f4d0_0                conda-forge/linux-64        3 MB
  + locket                        0.2.0  py_2                          conda-forge/noarch        Cached
  + lz4-c                         1.9.3  h9c3ff4c_1                    conda-forge/linux-64      Cached
  + markupsafe                    2.0.1  py37h5e8e339_1                conda-forge/linux-64       22 KB
  + msgpack-python                1.0.2  py37h2527ec5_2                conda-forge/linux-64       91 KB
  + nccl                       2.11.4.1  h96e36e3_0                    conda-forge/linux-64      150 MB
  + ncurses                         6.2  h58526e2_4                    conda-forge/linux-64      Cached
  + numba                        0.53.1  py37hb11d6e1_1                conda-forge/linux-64        4 MB
  + numpy                        1.21.4  py37h31617e3_0                conda-forge/linux-64      Cached
  + nvtx                          0.2.3  py37h5e8e339_0                conda-forge/linux-64       55 KB
  + olefile                        0.46  pyh9f0ad1d_1                  conda-forge/noarch        Cached
  + openjpeg                      2.4.0  hb52868f_1                    conda-forge/linux-64      Cached
  + openssl                      1.1.1l  h7f98852_0                    conda-forge/linux-64      Cached
  + orc                           1.7.1  h68e2c4e_0                    conda-forge/linux-64        1 MB
  + packaging                      21.2  pyhd8ed1ab_1                  conda-forge/noarch         35 KB
  + pandas                        1.3.4  py37he8f5f7f_1                conda-forge/linux-64       13 MB
  + parquet-cpp                   1.5.1  1                             conda-forge/linux-64        3 KB
  + partd                         1.2.0  pyhd8ed1ab_0                  conda-forge/noarch        Cached
  + pillow                        8.4.0  py37h0f21c89_0                conda-forge/linux-64      706 KB
  + pip                          21.3.1  pyhd8ed1ab_0                  conda-forge/noarch        Cached
  + protobuf                     3.18.1  py37hcd2ae1e_0                conda-forge/linux-64      344 KB
  + psutil                        5.8.0  py37h5e8e339_2                conda-forge/linux-64      340 KB
  + pyarrow                       5.0.0  py37h08c6592_11_cuda          conda-forge/linux-64        3 MB
  + pyparsing                     2.4.7  pyhd8ed1ab_1                  conda-forge/noarch         60 KB
  + python                       3.7.12  hb7a2778_100_cpython          conda-forge/linux-64       57 MB
  + python-dateutil               2.8.2  pyhd8ed1ab_0                  conda-forge/noarch        Cached
  + python_abi                      3.7  2_cp37m                       conda-forge/linux-64      Cached
  + pytz                         2021.3  pyhd8ed1ab_0                  conda-forge/noarch        Cached
  + pyyaml                          6.0  py37h5e8e339_3                conda-forge/linux-64      187 KB
  + re2                      2021.09.01  h9c3ff4c_0                    conda-forge/linux-64      221 KB
  + readline                        8.1  h46c0cb4_0                    conda-forge/linux-64      Cached
  + rmm                        21.10.01  cuda_11.0_py37_gc54767f_0     rapidsai/linux-64         940 KB
  + s2n                           1.1.1  h9b69904_0                    conda-forge/linux-64      485 KB
  + scipy                         1.7.2  py37hf2a6cf1_0                conda-forge/linux-64       22 MB
  + setuptools                   58.5.3  py37h89c1867_0                conda-forge/linux-64        1 MB
  + six                          1.16.0  pyh6c4a22f_0                  conda-forge/noarch        Cached
  + snappy                        1.1.8  he1b5a44_3                    conda-forge/linux-64       32 KB
  + sortedcontainers              2.4.0  pyhd8ed1ab_0                  conda-forge/noarch        Cached
  + spdlog                        1.8.5  h4bd325d_0                    conda-forge/linux-64      353 KB
  + sqlite                       3.36.0  h9cd32fc_2                    conda-forge/linux-64      Cached
  + tblib                         1.7.0  pyhd8ed1ab_0                  conda-forge/noarch        Cached
  + tk                           8.6.11  h27826a3_1                    conda-forge/linux-64      Cached
  + toolz                        0.11.2  pyhd8ed1ab_0                  conda-forge/noarch        Cached
  + tornado                         6.1  py37h5e8e339_2                conda-forge/linux-64      642 KB
  + treelite                      2.1.0  py37h4b3d254_0                conda-forge/linux-64        1 MB
  + typing_extensions          3.10.0.2  pyha770c72_0                  conda-forge/noarch        Cached
  + ucx                 1.11.1+gc58db6b  cuda11.0_0                    rapidsai/linux-64          12 MB
  + ucx-proc                      1.0.0  gpu                           rapidsai/linux-64           9 KB
  + ucx-py                       0.22.0  py37_gc58db6b_0               rapidsai/linux-64         349 KB
  + wheel                        0.37.0  pyhd8ed1ab_1                  conda-forge/noarch        Cached
  + xz                            5.2.5  h516909a_1                    conda-forge/linux-64      Cached
  + yaml                          0.2.5  h516909a_0                    conda-forge/linux-64      Cached
  + zict                          2.0.0  py_0                          conda-forge/noarch        Cached
  + zipp                          3.6.0  pyhd8ed1ab_0                  conda-forge/noarch         12 KB
  + zlib                         1.2.11  h36c2ea0_1013                 conda-forge/linux-64      Cached
  + zstd                          1.5.0  ha95c52a_0                    conda-forge/linux-64      Cached

  Summary:

  Install: 146 packages

  Total download: 2 GB

─────────────────────────────────────────────────────────────────────────────────────────────────────────

Confirm changes: [Y/n] Y
Finished arrow-cpp-proc                       (00m:00s)              24 KB     69 KB/s
Finished libbrotlicommon                      (00m:00s)              65 KB    185 KB/s
Finished libutf8proc                          (00m:00s)              95 KB    269 KB/s
Finished dlpack                               (00m:00s)              12 KB     32 KB/s
Finished libbrotlidec                         (00m:00s)              33 KB     83 KB/s
Finished aws-c-compression                    (00m:00s)              16 KB     41 KB/s
Finished gflags                               (00m:00s)             114 KB    266 KB/s
Finished abseil-cpp                           (00m:00s)            1010 KB      2 MB/s
Finished aws-c-http                           (00m:00s)             170 KB    378 KB/s
Finished aws-c-io                             (00m:00s)             121 KB    260 KB/s
Finished s2n                                  (00m:00s)             485 KB      1 MB/s
Finished aws-c-s3                             (00m:00s)              48 KB     98 KB/s
Finished aws-c-mqtt                           (00m:00s)              67 KB    130 KB/s
Finished grpc-cpp                             (00m:00s)               4 MB      7 MB/s
Finished cachetools                           (00m:00s)              12 KB     22 KB/s
Finished markupsafe                           (00m:00s)              22 KB     37 KB/s
Finished pyyaml                               (00m:00s)             187 KB    305 KB/s
Finished nvtx                                 (00m:00s)              55 KB     86 KB/s
Finished aws-sdk-cpp                          (00m:00s)               5 MB      7 MB/s
Finished cytoolz                              (00m:00s)             407 KB    607 KB/s
Finished importlib-metadata                   (00m:00s)              32 KB     47 KB/s
Finished click                                (00m:00s)             145 KB    197 KB/s
Finished dask-core                            (00m:00s)             768 KB    965 KB/s
Finished pyarrow                              (00m:00s)               3 MB      4 MB/s
Finished numba                                (00m:00s)               4 MB      4 MB/s
Finished re2                                  (00m:00s)             221 KB    172 KB/s
Finished bokeh                                (00m:00s)              14 MB     11 MB/s
Finished glog                                 (00m:00s)             104 KB     79 KB/s
Finished libxml2                              (00m:00s)             760 KB    554 KB/s
Finished libhwloc                             (00m:00s)               3 MB      2 MB/s
Finished libcurl                              (00m:00s)             337 KB    196 KB/s
Finished zipp                                 (00m:00s)              12 KB      7 KB/s
Finished dask-cudf                            (00m:00s)             110 KB     51 KB/s
Finished fastrlock                            (00m:00s)              31 KB     14 KB/s
Finished fastavro                             (00m:00s)             503 KB    211 KB/s
Finished parquet-cpp                          (00m:00s)               3 KB      1 KB/s
Finished pandas                               (00m:00s)              13 MB      5 MB/s
Finished ucx                                  (00m:01s)              12 MB      4 MB/s
Finished librmm                               (00m:00s)             688 KB    207 KB/s
Finished libffi                               (00m:00s)              57 KB     16 KB/s
Finished aws-c-cal                            (00m:00s)              36 KB     10 KB/s
Finished aws-c-event-stream                   (00m:00s)              47 KB     13 KB/s
Finished aws-c-auth                           (00m:00s)              99 KB     27 KB/s
Finished ucx-py                               (00m:00s)             349 KB     81 KB/s
Finished tornado                              (00m:00s)             642 KB    144 KB/s
Finished protobuf                             (00m:00s)             344 KB     76 KB/s
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Finished dask                                 (00m:00s)               4 KB    915  B/s
Finished snappy                               (00m:00s)              32 KB      7 KB/s
Finished libnsl                               (00m:00s)              31 KB      6 KB/s
Finished libevent                             (00m:00s)               1 MB    226 KB/s
Finished orc                                  (00m:00s)               1 MB    217 KB/s
Finished aws-crt-cpp                          (00m:00s)             204 KB     39 KB/s
Finished packaging                            (00m:00s)              35 KB      7 KB/s
Finished msgpack-python                       (00m:00s)              91 KB     17 KB/s
Finished pillow                               (00m:00s)             706 KB    131 KB/s
Finished treelite                             (00m:00s)               1 MB    273 KB/s
Finished cupy                                 (00m:01s)              50 MB      9 MB/s
Finished icu                                  (00m:00s)              13 MB      2 MB/s
Finished libthrift                            (00m:00s)               5 MB    781 KB/s
Finished ucx-proc                             (00m:00s)               9 KB      1 KB/s
Finished cudf                                 (00m:01s)              13 MB      2 MB/s
Finished libbrotlienc                         (00m:00s)             286 KB     38 KB/s
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Finished setuptools                           (00m:00s)               1 MB    101 KB/s
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Finished llvmlite                             (00m:00s)               3 MB    257 KB/s
Finished aws-checksums                        (00m:00s)              50 KB      5 KB/s
Finished nccl                                 (00m:03s)             150 MB     14 MB/s
Finished libfaiss                             (00m:01s)              67 MB      6 MB/s
Finished libcumlprims                         (00m:00s)               2 MB    154 KB/s
Finished pyparsing                            (00m:00s)              60 KB      5 KB/s
Finished cuml                                 (00m:00s)               9 MB    728 KB/s
Finished libcudf                              (00m:15s)             220 MB     13 MB/s
Finished cudatoolkit                          (00m:17s)             953 MB     56 MB/s
Finished libcuml                              (00m:24s)             181 MB      6 MB/s
Downloading  [=================================================================] (03m:34s)   66.00 MB/s
Extracting   [=================================================================] (03m:34s)      84 / 84
Preparing transaction: done
Verifying transaction: \ Killed
github-actions[bot] commented 2 years ago

This issue has been labeled inactive-30d due to no recent activity in the past 30 days. 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 labeled inactive-90d if there is no activity in the next 60 days.

RichieHakim commented 2 years ago

@higgteil I'm having this issue as well. Did you find a solution?

dantegd commented 2 years ago

This issue seems to be stemming from the mamba/conda installation step more than from the rapids side, but we'll try to see if it repro's on the centos docker containers and try triage as well

github-actions[bot] commented 2 years ago

This issue has been labeled inactive-30d due to no recent activity in the past 30 days. 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 labeled inactive-90d if there is no activity in the next 60 days.

tkmamidi commented 2 years ago

Hello, I can't seem to install as well.

This is what I see with mamba

rapidsai/osx-64          [====================] (00m:00s) Done
rapidsai/noarch          [====================] (00m:00s) Done
nvidia/osx-64            [====================] (00m:00s) Done
nvidia/noarch            [====================] (00m:00s) Done
pkgs/r/noarch            [====================] (00m:00s) Done
pkgs/main/noarch         [====================] (00m:00s) Done
pkgs/r/osx-64            [====================] (00m:00s) Done
pkgs/main/osx-64         [====================] (00m:00s) Done
conda-forge/noarch       [====================] (00m:01s) Done
conda-forge/osx-64       [====================] (00m:04s) Done

Looking for: ['rapids=22.02', 'python=3.9', 'cudatoolkit=11.4', 'dask-sql']

Encountered problems while solving.
Problem: nothing provides requested rapids 22.02**
Problem: nothing provides requested cudatoolkit 11.4**

This is what I see with conda:

 % conda create -n rapids-22.02 -c rapidsai -c nvidia -c conda-forge \
    rapids=22.02 python=3.8 cudatoolkit=11.4 dask-sql
Collecting package metadata (current_repodata.json): done
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed

PackagesNotFoundError: The following packages are not available from current channels:

  - cudatoolkit=11.4
  - rapids=22.02

Current channels:

  - https://conda.anaconda.org/rapidsai/osx-64
  - https://conda.anaconda.org/rapidsai/noarch
  - https://conda.anaconda.org/nvidia/osx-64
  - https://conda.anaconda.org/nvidia/noarch
  - https://conda.anaconda.org/conda-forge/osx-64
  - https://conda.anaconda.org/conda-forge/noarch
  - https://repo.anaconda.com/pkgs/main/osx-64
  - https://repo.anaconda.com/pkgs/main/noarch
  - https://repo.anaconda.com/pkgs/r/osx-64
  - https://repo.anaconda.com/pkgs/r/noarch

Please help! Thanks in advance!

github-actions[bot] commented 2 years ago

This issue has been labeled inactive-90d due to no recent activity in the past 90 days. 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.

tkmamidi commented 2 years ago

Is there any update on this? Please help!

DeepTitan commented 2 years ago

Make sure that your channel priority is flexible. This works for me:

conda config --set channel_priority flexible conda create -n rapids -c rapidsai -c nvidia -c conda-forge cuml=22.06 python=3.8 cudatoolkit=11.5