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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", "12.0"]
arch: [x86_64]
includes:
- common_build
- cuda
- cuda_version
- docs
- py_build
- py_run
- py_version
- test_python
cpp_all:
output: conda
matrix:
cuda: ["11.8", "12.0"]
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_cpp
test_python:
output: none
includes:
- cuda_version
- py_version
- test_python
test_notebooks:
output: none
includes:
- cuda_version
- py_run
- py_version
- test_notebooks
py_build:
output: pyproject
extras:
table: build-system
includes:
- common_build
- py_build
py_run:
output: pyproject
extras:
table: project
includes:
- py_run
py_test:
output: pyproject
extras:
table: project.optional-dependencies
key: test
includes:
- test_python
channels:
- rapidsai
- rapidsai-nightly
- dask/label/dev
- conda-forge
- nvidia
dependencies:
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
- ninja
- output_types: conda
packages:
- c-compiler
- cxx-compiler
- gmock>=1.13.0
- gtest>=1.13.0
- libcumlprims==24.2.*
- libraft==24.2.*
- libraft-headers==24.2.*
- librmm==24.2.*
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:
arch: x86_64
cuda: "12.0"
packages:
- cuda-nvcc
py_build:
common:
- output_types: [conda, requirements, pyproject]
packages:
- cython>=3.0.0
- &treelite treelite==3.9.1
- output_types: conda
packages:
- &pylibraft_conda pylibraft==24.2.*
- &rmm_conda rmm==24.2.*
- scikit-build-core>=0.7.0
- 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
- output_types: [pyproject, requirements]
packages:
- scikit-build-core[pyproject]>=0.7.0
- &treelite_runtime treelite_runtime==3.9.1
specific:
- output_types: [conda, requirements, pyproject]
matrices:
- matrix:
cuda: "12.0"
packages:
- &cuda_python12 cuda-python>=12.0,<13.0a0
- matrix: # All CUDA 11 versions
packages:
- &cuda_python11 cuda-python>=11.7.1,<12.0a0
- output_types: [requirements, pyproject]
matrices:
- matrix: {cuda: "12.0"}
packages:
- pylibraft-cu12==24.2.*
- rmm-cu12==24.2.*
- matrix: {cuda: "11.8"}
packages: &py_build_packages_cu11
- &pylibraft_cu11 pylibraft-cu11==24.2.*
- &rmm_cu11 rmm-cu11==24.2.*
- {matrix: {cuda: "11.5"}, packages: *py_build_packages_cu11}
- {matrix: {cuda: "11.4"}, packages: *py_build_packages_cu11}
- {matrix: {cuda: "11.2"}, packages: *py_build_packages_cu11}
- {matrix: null, packages: [*pylibraft_conda, *rmm_conda] }
py_run:
common:
- output_types: [conda, requirements, pyproject]
packages:
- dask-cuda==24.2.*
- joblib>=0.11
- numba>=0.57
# 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
- rapids-dask-dependency==24.2.*
- *treelite
- output_types: conda
packages:
- &cudf_conda cudf==24.2.*
- &cupy_conda cupy>=12.0.0
- &dask_cudf_conda dask-cudf==24.2.*
- &raft_dask_conda raft-dask==24.2.*
- 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
- output_types: [pyproject, requirements]
packages:
- *treelite_runtime
specific:
- output_types: [requirements, pyproject]
matrices:
- matrix: {cuda: "12.0"}
packages:
- cudf-cu12==24.2.*
- cupy-cuda12x>=12.0.0
- dask-cudf-cu12==24.2.*
- pylibraft-cu12==24.2.*
- raft-dask-cu12==24.2.*
- rmm-cu12==24.2.*
# All CUDA 11 versions
- matrix: {cuda: "11.8"}
packages: &py_run_packages_cu11
- cudf-cu11==24.2.*
- &cupy_pyproject_cu11 cupy-cuda11x>=12.0.0
- dask-cudf-cu11==24.2.*
- *pylibraft_cu11
- raft-dask-cu11==24.2.*
- *rmm_cu11
- {matrix: {cuda: "11.5"}, packages: *py_run_packages_cu11}
- {matrix: {cuda: "11.4"}, packages: *py_run_packages_cu11}
- {matrix: {cuda: "11.2"}, packages: *py_run_packages_cu11}
- matrix: null
packages:
- *cudf_conda
- *cupy_pyproject_cu11
- *dask_cudf_conda
- *pylibraft_conda
- *raft_dask_conda
- *rmm_conda
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
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
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==1.2
- sphinx<6
- sphinx-copybutton
- sphinx-markdown-tables
- output_types: conda
packages:
- doxygen=1.9.1
py_version:
specific:
- output_types: conda
matrices:
- matrix:
py: "3.9"
packages:
- python=3.9
- matrix:
py: "3.10"
packages:
- python=3.10
- matrix:
packages:
- python>=3.9,<3.11
test_cpp:
common:
- output_types: conda
packages:
- *cmake_ver
test_python:
common:
- output_types: [conda, requirements, pyproject]
packages:
- dask-ml
- hypothesis>=6.0,<7
- nltk
- numpydoc
- pytest
- pytest-benchmark
- pytest-cases
- pytest-cov
- pytest-xdist
- seaborn
- *scikit_learn
- statsmodels
- umap-learn==0.5.3
- pynndescent==0.5.8
- output_types: conda
packages:
- pip
- pip:
- dask-glm==0.3.0
# TODO: remove pin once a release that includes fixes for the error
# is released: https://github.com/rapidsai/cuml/issues/5514
- hdbscan<=0.8.30
- output_types: pyproject
packages:
- dask-glm==0.3.0
# TODO: Can we stop pulling from the master branch now that there was a release in October?
- hdbscan @ git+https://github.com/scikit-learn-contrib/hdbscan.git@master
test_notebooks:
common:
- output_types: [conda, requirements]
packages:
- dask-ml==2023.3.24
- jupyter
- matplotlib
- numpy
- pandas
- *scikit_learn
- seaborn