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dependencies.yaml
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dependencies.yaml
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# Dependency list for https://github.com/rapidsai/dependency-file-generator
files:
all:
output: conda
matrix:
cuda: ["11.8", "12.5"]
arch: [x86_64]
includes:
- common_build
- cuda
- cuda_version
- docs
- py_build
- py_run
- py_version
- rapids_build_backend
- test_python
cpp_all:
output: conda
matrix:
cuda: ["11.8", "12.5"]
arch: [x86_64]
includes:
- common_build
- cuda
- cuda_version
checks:
output: none
includes:
- checks
- py_version
clang_tidy:
output: conda
matrix:
cuda: ["11.8"]
arch: [x86_64]
includes:
- clang_tidy
- common_build
- cuda
- cuda_version
docs:
output: none
includes:
- cuda_version
- docs
- py_version
test_cpp:
output: none
includes:
- cuda_version
- test_libcuml
- test_cpp
test_python:
output: none
includes:
- cuda_version
- py_version
- test_cuml
- test_python
test_notebooks:
output: none
includes:
- cuda_version
- py_run
- py_version
- test_cuml
- test_notebooks
py_build:
output: pyproject
pyproject_dir: python/cuml
extras:
table: build-system
includes:
- rapids_build_backend
py_rapids_build:
output: pyproject
pyproject_dir: python/cuml
extras:
table: tool.rapids-build-backend
key: requires
includes:
- common_build
- py_build
py_run:
output: pyproject
pyproject_dir: python/cuml
extras:
table: project
includes:
- cuda_wheels
- py_run
py_test:
output: pyproject
pyproject_dir: python/cuml
extras:
table: project.optional-dependencies
key: test
includes:
- test_python
channels:
- rapidsai
- rapidsai-nightly
- dask/label/dev
- conda-forge
- nvidia
dependencies:
rapids_build_backend:
common:
- output_types: [conda, requirements, pyproject]
packages:
- rapids-build-backend>=0.3.0,<0.4.0.dev0
- output_types: [conda]
packages:
- scikit-build-core>=0.10.0
- output_types: [requirements, pyproject]
packages:
- scikit-build-core[pyproject]>=0.10.0
checks:
common:
- output_types: [conda, requirements]
packages:
- pre-commit
clang_tidy:
common:
- output_types: [conda, requirements]
packages:
# clang 15 required by libcudacxx.
- clang==15.0.7
- clang-tools==15.0.7
- ninja
- tomli
common_build:
common:
- output_types: [conda, requirements, pyproject]
packages:
- &cmake_ver cmake>=3.26.4,!=3.30.0
- ninja
- output_types: conda
packages:
- c-compiler
- cxx-compiler
- libcumlprims==24.10.*,>=0.0.0a0
- libraft==24.10.*,>=0.0.0a0
- libraft-headers==24.10.*,>=0.0.0a0
- librmm==24.10.*,>=0.0.0a0
specific:
- output_types: conda
matrices:
- matrix:
arch: x86_64
packages:
- gcc_linux-64=11.*
- sysroot_linux-64==2.17
- matrix:
arch: aarch64
packages:
- gcc_linux-aarch64=11.*
- sysroot_linux-aarch64==2.17
- output_types: conda
matrices:
- matrix:
arch: x86_64
cuda: "11.8"
packages:
- nvcc_linux-64=11.8
- matrix:
arch: aarch64
cuda: "11.8"
packages:
- nvcc_linux-aarch64=11.8
- matrix:
cuda: "12.*"
packages:
- cuda-nvcc
py_build:
common:
- output_types: [conda, requirements, pyproject]
packages:
- &cython cython>=3.0.0
- &treelite treelite==4.3.0
- output_types: conda
packages:
- &pylibraft_unsuffixed pylibraft==24.10.*,>=0.0.0a0
- &rmm_unsuffixed rmm==24.10.*,>=0.0.0a0
- output_types: requirements
packages:
# pip recognizes the index as a global option for the requirements.txt file
# This index is needed for cudf and rmm.
- --extra-index-url=https://pypi.nvidia.com
- --extra-index-url=https://pypi.anaconda.org/rapidsai-wheels-nightly/simple
specific:
- output_types: [conda, requirements, pyproject]
matrices:
- matrix:
cuda: "12.*"
packages:
- cuda-python>=12.0,<13.0a0
- matrix:
cuda: "11.*"
packages:
- cuda-python>=11.7.1,<12.0a0
- matrix:
packages:
- cuda-python
- output_types: [requirements, pyproject]
matrices:
- matrix:
cuda: "12.*"
cuda_suffixed: "true"
packages:
- pylibraft-cu12==24.10.*,>=0.0.0a0
- rmm-cu12==24.10.*,>=0.0.0a0
- matrix:
cuda: "11.*"
cuda_suffixed: "true"
packages:
- pylibraft-cu11==24.10.*,>=0.0.0a0
- rmm-cu11==24.10.*,>=0.0.0a0
- matrix:
packages:
- *pylibraft_unsuffixed
- *rmm_unsuffixed
py_run:
common:
- output_types: [conda, requirements, pyproject]
packages:
- dask-cuda==24.10.*,>=0.0.0a0
- joblib>=0.11
- numba>=0.57
- numpy>=1.23,<3.0a0
# TODO: Is scipy really a hard dependency, or should
# we make it optional (i.e. an extra for pip
# installation/run_constrained for conda)?
- scipy>=1.8.0
- packaging
- rapids-dask-dependency==24.10.*,>=0.0.0a0
- *treelite
- output_types: conda
packages:
- &cudf_unsuffixed cudf==24.10.*,>=0.0.0a0
- &cupy_unsuffixed cupy>=12.0.0
- &dask_cudf_unsuffixed dask-cudf==24.10.*,>=0.0.0a0
- &raft_dask_unsuffixed raft-dask==24.10.*,>=0.0.0a0
- output_types: requirements
packages:
# pip recognizes the index as a global option for the requirements.txt file
# This index is needed for cudf and rmm.
- --extra-index-url=https://pypi.nvidia.com
- --extra-index-url=https://pypi.anaconda.org/rapidsai-wheels-nightly/simple
specific:
- output_types: [requirements, pyproject]
matrices:
- matrix:
cuda: "12.*"
cuda_suffixed: "true"
packages:
- cudf-cu12==24.10.*,>=0.0.0a0
- &cupy_pyproject_cu12 cupy-cuda12x>=12.0.0
- dask-cudf-cu12==24.10.*,>=0.0.0a0
- pylibraft-cu12==24.10.*,>=0.0.0a0
- raft-dask-cu12==24.10.*,>=0.0.0a0
- rmm-cu12==24.10.*,>=0.0.0a0
- matrix:
cuda: "12.*"
cuda_suffixed: "false"
packages:
- *cudf_unsuffixed
# NOTE: cupy still has a "-cuda12x" suffix here, because it's suffixed
# in DLFW builds
- *cupy_pyproject_cu12
- *dask_cudf_unsuffixed
- *pylibraft_unsuffixed
- *raft_dask_unsuffixed
- *rmm_unsuffixed
- matrix:
cuda: "11.*"
cuda_suffixed: "true"
packages: &py_run_packages_cu11
- cudf-cu11==24.10.*,>=0.0.0a0
- &cupy_pyproject_cu11 cupy-cuda11x>=12.0.0
- dask-cudf-cu11==24.10.*,>=0.0.0a0
- pylibraft-cu11==24.10.*,>=0.0.0a0
- raft-dask-cu11==24.10.*,>=0.0.0a0
- rmm-cu11==24.10.*,>=0.0.0a0
- matrix:
cuda: "11.*"
cuda_suffixed: "false"
packages:
- *cudf_unsuffixed
# NOTE: cupy still has a "-cuda11x" suffix here, because it's suffixed
# in DLFW builds
- *cupy_pyproject_cu11
- *dask_cudf_unsuffixed
- *pylibraft_unsuffixed
- *raft_dask_unsuffixed
- *rmm_unsuffixed
- matrix:
packages:
- *cudf_unsuffixed
- *cupy_pyproject_cu11
- *dask_cudf_unsuffixed
- *pylibraft_unsuffixed
- *raft_dask_unsuffixed
- *rmm_unsuffixed
cuda_version:
specific:
- output_types: conda
matrices:
- matrix:
cuda: "11.2"
packages:
- cuda-version=11.2
- matrix:
cuda: "11.4"
packages:
- cuda-version=11.4
- matrix:
cuda: "11.5"
packages:
- cuda-version=11.5
- matrix:
cuda: "11.8"
packages:
- cuda-version=11.8
- matrix:
cuda: "12.0"
packages:
- cuda-version=12.0
- matrix:
cuda: "12.2"
packages:
- cuda-version=12.2
- matrix:
cuda: "12.5"
packages:
- cuda-version=12.5
cuda:
specific:
- output_types: conda
matrices:
- matrix:
cuda: "12.*"
packages:
- cuda-cudart-dev
- cuda-profiler-api
- libcublas-dev
- libcufft-dev
- libcurand-dev
- libcusolver-dev
- libcusparse-dev
- matrix:
cuda: "11.8"
packages:
- cudatoolkit
- libcublas-dev=11.11.3.6
- libcublas=11.11.3.6
- libcufft-dev=10.9.0.58
- libcufft=10.9.0.58
- libcurand-dev=10.3.0.86
- libcurand=10.3.0.86
- libcusolver-dev=11.4.1.48
- libcusolver=11.4.1.48
- libcusparse-dev=11.7.5.86
- libcusparse=11.7.5.86
- matrix:
cuda: "11.5"
packages:
- cudatoolkit
- libcublas-dev>=11.7.3.1,<=11.7.4.6
- libcublas>=11.7.3.1,<=11.7.4.6
- libcufft-dev>=10.6.0.54,<=10.6.0.107
- libcufft>=10.6.0.54,<=10.6.0.107
- libcurand-dev>=10.2.6.48,<=10.2.7.107
- libcurand>=10.2.6.48,<=10.2.7.107
- libcusolver-dev>=11.2.1.48,<=11.3.2.107
- libcusolver>=11.2.1.48,<=11.3.2.107
- libcusparse-dev>=11.7.0.31,<=11.7.0.107
- libcusparse>=11.7.0.31,<=11.7.0.107
- matrix:
cuda: "11.4"
packages:
- cudatoolkit
- &libcublas_dev114 libcublas-dev>=11.5.2.43,<=11.6.5.2
- &libcublas114 libcublas>=11.5.2.43,<=11.6.5.2
- &libcufft_dev114 libcufft-dev>=10.5.0.43,<=10.5.2.100
- &libcufft114 libcufft>=10.5.0.43,<=10.5.2.100
- &libcurand_dev114 libcurand-dev>=10.2.5.43,<=10.2.5.120
- &libcurand114 libcurand>=10.2.5.43,<=10.2.5.120
- &libcusolver_dev114 libcusolver-dev>=11.2.0.43,<=11.2.0.120
- &libcusolver114 libcusolver>=11.2.0.43,<=11.2.0.120
- &libcusparse_dev114 libcusparse-dev>=11.6.0.43,<=11.6.0.120
- &libcusparse114 libcusparse>=11.6.0.43,<=11.6.0.120
- matrix:
cuda: "11.2"
packages:
- cudatoolkit
# The NVIDIA channel doesn't publish pkgs older than 11.4 for these libs,
# so 11.2 uses 11.4 packages (the oldest available).
- *libcublas_dev114
- *libcublas114
- *libcufft_dev114
- *libcufft114
- *libcurand_dev114
- *libcurand114
- *libcusolver_dev114
- *libcusolver114
- *libcusparse_dev114
- *libcusparse114
cuda_wheels:
specific:
- output_types: pyproject
matrices:
- matrix:
cuda: "12.*"
use_cuda_wheels: "true"
packages:
- nvidia-cublas-cu12
- nvidia-cufft-cu12
- nvidia-curand-cu12
- nvidia-cusparse-cu12
- nvidia-cusolver-cu12
# CUDA 11 does not provide wheels, so use the system libraries instead
- matrix:
cuda: "11.*"
use_cuda_wheels: "true"
packages:
# if use_cuda_wheels=false is provided, do not add dependencies on any CUDA wheels
# (e.g. for DLFW and pip devcontainers)
- matrix:
use_cuda_wheels: "false"
packages:
# if no matching matrix selectors passed, list the unsuffixed packages
# (just as a source of documentation, as this populates pyproject.toml in source control)
- matrix:
packages:
- nvidia-cublas
- nvidia-cufft
- nvidia-curand
- nvidia-cusparse
- nvidia-cusolver
docs:
common:
- output_types: [conda, requirements]
packages:
- graphviz
- ipython
- ipykernel
- nbsphinx
- numpydoc
# https://github.com/pydata/pydata-sphinx-theme/issues/1539
- pydata-sphinx-theme!=0.14.2
- recommonmark
- &scikit_learn scikit-learn==1.5
- sphinx<6
- sphinx-copybutton
- sphinx-markdown-tables
- output_types: conda
packages:
- doxygen=1.9.1
py_version:
specific:
- output_types: conda
matrices:
- matrix:
py: "3.10"
packages:
- python=3.10
- matrix:
py: "3.11"
packages:
- python=3.11
- matrix:
packages:
- python>=3.10,<3.12
test_libcuml:
common:
- output_types: conda
packages:
- libcuml==24.10.*,>=0.0.0a0
- libcuml-tests==24.10.*,>=0.0.0a0
test_cuml:
common:
- output_types: conda
packages:
- libcuml==24.10.*,>=0.0.0a0
- cuml==24.10.*,>=0.0.0a0
test_cpp:
common:
- output_types: conda
packages:
- *cmake_ver
test_python:
common:
- output_types: [conda, requirements, pyproject]
packages:
- *cython
- dask-ml
- hdbscan>=0.8.38,<0.8.39
- hypothesis>=6.0,<7
- nltk
- numpydoc
- pytest==7.*
- pytest-benchmark
- pytest-cases
- pytest-cov
- pytest-xdist
- seaborn
- *scikit_learn
- statsmodels
- umap-learn==0.5.3
- pynndescent
- output_types: conda
packages:
- pip
- pip:
- dask-glm==0.3.0
- output_types: pyproject
packages:
- dask-glm==0.3.0
test_notebooks:
common:
- output_types: [conda, requirements]
packages:
- dask-ml==2023.3.24
- jupyter
- matplotlib
- numpy
- pandas
- *scikit_learn
- seaborn
- xgboost