通过 conda 安装 cuda rapids + xgboost 堆栈

Question

我正在尝试通过 conda 在 AWS Sagemaker Studio 实例内的 jupyter 笔记本中安装带有 CUDA 的RAPIDS堆栈：

conda install -y -c conda-forge -c rapidsai-nightly -c nvidia libgcc cudf cuml xgboost rapids-blazing

它试图解决依赖项中的尽可能多的冲突（大约 20 分钟后），然后它说：

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): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: \ 
Found conflicts! Looking for incompatible packages.
This can take several minutes.  Press CTRL-C to abort.
                                                                                /failed

UnsatisfiableError: The following specifications were found to be incompatible with each other:

Output in format: Requested package -> Available versions

Package _openmp_mutex conflicts for:
cudf -> libgcc-ng[version='>=12'] -> _openmp_mutex[version='>=4.5']
libgcc -> libgcc-ng[version='>=7.2.0'] -> _openmp_mutex[version='>=4.5']
python=3.8.10 -> libgcc-ng[version='>=9.4.0'] -> _openmp_mutex[version='>=4.5']
xgboost -> libgcc-ng[version='>=9.3.0'] -> _openmp_mutex[version='>=4.5']
cuml -> libgcc-ng[version='>=12'] -> _openmp_mutex[version='>=4.5']

Package libstdcxx-ng conflicts for:
cuml -> libstdcxx-ng[version='>=12']
python=3.8.10 -> libffi[version='>=3.4.2,<3.5.0a0'] -> libstdcxx-ng[version='>=7.3.0|>=7.5.0']
cudf -> libstdcxx-ng[version='>=12']
python=3.8.10 -> libstdcxx-ng[version='>=9.3.0|>=9.4.0']
rapids-blazing -> cudatoolkit=11.4 -> libstdcxx-ng[version='>=10.3.0|>=9.4.0|>=9.3.0|>=7.3.0']
xgboost -> nccl[version='>=2.14.3.1,<3.0a0'] -> libstdcxx-ng[version='>=10.3.0|>=11.2.0|>=12|>=9.4.0|>=7.2.0']
xgboost -> libstdcxx-ng[version='>=4.9|>=7.3.0|>=7.5.0|>=9.3.0']
cuml -> cuda-python[version='>=11.5,<11.7.1'] -> libstdcxx-ng[version='>=10.3.0|>=9.4.0|>=11.2.0|>=9.3.0|>=7.3.0|>=7.5.0']
libgcc -> libstdcxx-ng[version='>=7.2.0']
libgcc -> gmp[version='>=4.2'] -> libstdcxx-ng[version='>=12|>=4.9|>=7.3.0|>=7.5.0|>=9.4.0']
cudf -> cuda-python[version='>=11.5,<11.7.1'] -> libstdcxx-ng[version='>=10.3.0|>=9.4.0|>=11.2.0|>=9.3.0|>=7.3.0|>=7.5.0|>=4.9']

Package rmm conflicts for:
cuml -> cudf=22.10 -> rmm[version='22.08.*|22.10.*|>=22.10.0a.220827,<22.11.0a0|>=22.10.0a.220828,<22.11.0a0|>=22.10.0a.220829,<22.11.0a0|>=22.10.0a.220830,<22.11.0a0|>=22.10.0a.220831,<22.11.0a0|>=22.10.0a.220901,<22.11.0a0|>=22.10.0a.220902,<22.11.0a0|>=22.10.0a.220903,<22.11.0a0|>=22.10.0a.220905,<22.11.0a0|>=22.10.0a.220906,<22.11.0a0|>=22.8.0a.220905,<22.9.0a0|>=22.8.0a.220903,<22.9.0a0|>=22.8.0a.220902,<22.9.0a0|>=22.8.0a.220901,<22.9.0a0|>=22.8.0a.220831,<22.9.0a0|>=22.8.0a.220830,<22.9.0a0|>=22.8.0a.220829,<22.9.0a0|>=22.8.0a.220828,<22.9.0a0|>=22.8.0a.220827,<22.9.0a0']
cudf -> rmm[version='>=22.10.0a.220827,<22.11.0a0|>=22.10.0a.220828,<22.11.0a0|>=22.10.0a.220829,<22.11.0a0|>=22.10.0a.220830,<22.11.0a0|>=22.10.0a.220831,<22.11.0a0|>=22.10.0a.220901,<22.11.0a0|>=22.10.0a.220902,<22.11.0a0|>=22.10.0a.220903,<22.11.0a0|>=22.10.0a.220905,<22.11.0a0|>=22.10.0a.220906,<22.11.0a0|>=22.8.0a.220905,<22.9.0a0|>=22.8.0a.220903,<22.9.0a0|>=22.8.0a.220902,<22.9.0a0|>=22.8.0a.220901,<22.9.0a0|>=22.8.0a.220831,<22.9.0a0|>=22.8.0a.220830,<22.9.0a0|>=22.8.0a.220829,<22.9.0a0|>=22.8.0a.220828,<22.9.0a0|>=22.8.0a.220827,<22.9.0a0']
xgboost -> py-xgboost==1.6.2dev.rapidsai22.10=cuda_11_py39_0 -> rmm[version='22.02.*|22.04.*|22.06.*|22.08.*|22.10.*']

Package nccl conflicts for:
xgboost -> nccl[version='>=2.10.3.1,<3.0a0|>=2.11.4.1,<3.0a0|>=2.13.4.1,<3.0a0|>=2.14.3.1,<3.0a0|>=2.12.12.1,<3.0a0|>=2.12.7.1,<3.0a0|>=2.7.8.1,<3.0a0']
cuml -> nccl[version='>=2.9.9']
cuml -> cupy[version='>=7.8.0,<11.0.0a0'] -> nccl[version='2.7.8.1.*|>=2.4.6.1,<3.0a0|>=2.7.8.1,<3.0a0|>=2.8.4.1,<3.0a0|>=2.8.3.1,<3.0a0|>=2.12.12.1,<3.0a0|>=2.13.4.1,<3.0a0']

Package libgcc conflicts for:
xgboost -> scipy -> libgcc
libgcc

Package python_abi conflicts for:
xgboost -> python[version='>=3.8,<3.9.0a0'] -> python_abi[version='3.8|3.9',build='*_pypy38_pp73|*_pypy39_pp73']
cuml -> cuda-python[version='>=11.5,<11.7.1'] -> python_abi[version='3.10.*|3.7.*|3.7|3.6.*|3.6|3.9|3.8',build='*_pypy38_pp73|*_pypy39_pp73|*_pypy36_pp73|*_cp36m|*_cp310|*_cp37m|*_pypy37_pp73']
cudf -> cuda-python[version='>=11.5,<11.7.1'] -> python_abi[version='2.7.*|3.10.*|3.7.*|3.7|3.9|3.8|3.6.*|3.6',build='*_cp27mu|*_pypy36_pp73|*_cp36m|*_pypy39_pp73|*_cp310|*_cp37m|*_pypy37_pp73|*_pypy38_pp73']
xgboost -> python_abi[version='3.10.*|3.7.*|3.8.*|3.9.*|3.7|3.6.*|3.6',build='*_pypy36_pp73|*_cp310|*_cp38|*_cp37m|*_cp39|*_pypy37_pp73|*_cp36m']
cuml -> python_abi[version='3.8.*|3.9.*',build='*_cp38|*_cp39']
rapids-blazing -> python_abi[version='3.7.*|3.8.*',build='*_cp38|*_cp37m']
cudf -> python_abi[version='3.8.*|3.9.*',build='*_cp38|*_cp39']

Package ncurses conflicts for:
python=3.8.10 -> readline[version='>=8.1,<9.0a0'] -> ncurses[version='>=6.1,<7.0.0a0|>=6.3,<7.0a0|>=6.1,<7.0a0']
cudf -> python[version='>=3.8,<3.9.0a0'] -> ncurses[version='>=6.1,<7.0.0a0|>=6.2,<7.0.0a0|>=6.3,<7.0a0|>=6.2,<7.0a0|>=6.1,<7.0a0']
xgboost -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='5.9.*|5.9|>=6.1,<7.0.0a0|>=6.2,<7.0.0a0|>=6.3,<7.0a0|>=6.2,<7.0a0|>=6.1,<7.0a0|>=6.2,<6.3.0a0|>=6.0,<7.0a0|6.0.*']
python=3.8.10 -> ncurses[version='>=6.2,<7.0.0a0|>=6.2,<7.0a0']
cuml -> python[version='>=3.9,<3.10.0a0'] -> ncurses[version='>=6.1,<7.0.0a0|>=6.2,<7.0.0a0|>=6.3,<7.0a0|>=6.2,<7.0a0|>=6.1,<7.0a0']

Package libsqlite conflicts for:
xgboost -> python[version='>=3.10,<3.11.0a0'] -> libsqlite[version='>=3.39.2,<4.0a0']
python=3.8.10 -> sqlite[version='>=3.36.0,<4.0a0'] -> libsqlite[version='3.39.2|3.39.3',build='h753d276_1|h753d276_0']

Package numpy conflicts for:
cudf -> numpy
cudf -> cupy[version='>=9.5.0,<11.0.0a0'] -> numpy[version='>=1.14.6,<2.0a0|>=1.15.4,<2.0a0|>=1.16.5,<2.0a0|>=1.16.6,<2.0a0|>=1.17|>=1.18|>=1.21.6,<2.0a0|>=1.19.5,<2.0a0|>=1.21.5,<2.0a0|>=1.18.5,<2.0a0|>=1.21.2,<2.0a0|>=1.21.4,<2.0a0|>=1.17.5,<2.0a0|>=1.19.4,<2.0a0|>=1.19.2,<2.0a0|>=1.18.4,<2.0a0|>=1.18.1,<2.0a0|>=1.20.3,<2.0a0|>=1.20.2,<2.0a0|>=1.16,<2.0a0|>=1.19']

Package cudf conflicts for:
cudf
cuml -> dask-cudf=22.10 -> cudf[version='22.08.00a220827.*|22.08.00a220828.*|22.08.00a220829.*|22.08.00a220830.*|22.08.00a220831.*|22.08.00a220901.*|22.08.00a220902.*|22.08.00a220903.*|22.08.00a220905.*|22.08.00a220906.*|22.10.00a.*|22.10.00a220827.*|22.10.00a220828.*|22.10.00a220829.*|22.10.00a220830.*|22.10.00a220831.*|22.10.00a220901.*|22.10.00a220902.*|22.10.00a220903.*|22.10.00a220905.*|22.10.00a220906.*']
cuml -> cudf[version='22.08.*|22.10.*']

Package dask-cudf conflicts for:
cuml -> dask-cudf[version='22.08.*|22.10.*']
rapids-blazing -> blazingsql=21.10 -> dask-cudf=21.10

Package libgcc-ng conflicts for:
cudf -> cuda-python[version='>=11.5,<11.7.1'] -> libgcc-ng[version='>=10.3.0|>=9.4.0|>=11.2.0|>=9.3.0|>=7.3.0|>=7.5.0|>=4.9|>=7.2.0']
cudf -> libgcc-ng[version='>=12']

Package cudatoolkit conflicts for:
cudf -> cudatoolkit[version='>=11,<12.0a0']
cudf -> cupy[version='>=9.5.0,<11.0.0a0'] -> cudatoolkit[version='10.0|10.0.*|10.1|10.1.*|10.2|10.2.*|11.0|11.0.*|11.1|11.1.*|>=11.2,<12|9.2|9.2.*|>=11.0,<=11.7|>=11.0,<=11.6|>=11.0,<=11.5']

Package numpy-base conflicts for:
cudf -> numpy -> 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xgboost -> numpy -> 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following specifications were found to be incompatible with your system:

  - feature:/linux-64::__cuda==11.4=0
  - feature:/linux-64::__glibc==2.31=0
  - feature:|@/linux-64::__cuda==11.4=0
  - feature:|@/linux-64::__glibc==2.31=0
  - cudf -> __glibc[version='>=2.17,<3.0.a0']
  - cudf -> cupy[version='>=9.5.0,<11.0.0a0'] -> __glibc[version='>=2.17']
  - cuml -> __glibc[version='>=2.17,<3.0.a0']
  - cuml -> cupy[version='>=7.8.0,<11.0.0a0'] -> __glibc[version='>=2.17']
  - libgcc -> libgcc-ng[version='>=7.2.0'] -> __glibc[version='>=2.17']
  - rapids-blazing -> cudatoolkit=11.4 -> __glibc[version='>=2.17,<3.0.a0']
  - xgboost -> __cuda
  - xgboost -> __glibc[version='>=2.17']
  - xgboost -> cudatoolkit[version='>=11,<12.0a0'] -> __glibc[version='>=2.17,<3.0.a0']

Your installed version is: 11.4

但是当我尝试运行import xgboost时，我得到了一个ModuleNotFound 。

有关于要安装的特定版本号的这篇文章，但它已经过时了

如何在 AWS Sagemaker 中通过 conda 安装 cuda rapids + xgboost 堆栈？

---

注意：不知何故在 Kaggle 笔记本上，它开箱即用，例如https://www.kaggle.com/code/alvations/numerai-baseline-2015-gpu

Answer 1

经过一番尝试，来自https://rapids.ai/start.html#get-rapids的这种组合有效：

conda create -n rapids-22.08 -c rapidsai -c nvidia -c conda-forge  \
    cudf=22.08 cuml=22.08 cugraph=22.08 cuspatial=22.08 cuxfilter=22.08 cusignal=22.08 cucim=22.08 python=3.8 cudatoolkit=11.5 \
    jupyterlab dask-sql graphistry dash pycaret xarray-spatial

虽然，我的实例上有 11.6 CUDA。