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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:
- checks
- build
- cuda
- cuda_version
- py_version
- rapids_build_skbuild
- run
- test_python
- docs
- clang_tools
test_cpp:
output: none
includes:
- cuda_version
test_python:
output: none
includes:
- cuda_version
- py_version
- test_python
checks:
output: none
includes:
- checks
- py_version
docs:
output: none
includes:
- cuda_version
- docs
- py_version
- pytorch_cpu
clang_tidy:
output: none
includes:
- build
- cuda
- cuda_version
- py_version
- rapids_build_skbuild
- run
- pytorch_cpu
- clang_tools
py_build_pylibwholegraph:
output: pyproject
pyproject_dir: python/pylibwholegraph
extras:
table: build-system
includes:
- rapids_build_skbuild
py_rapids_build_pylibwholegraph:
output: pyproject
pyproject_dir: python/pylibwholegraph
extras:
table: tool.rapids-build-backend
key: requires
includes:
- python_build_wheel
channels:
- rapidsai
- rapidsai-nightly
- pytorch
- conda-forge
- nvidia
dependencies:
build:
common:
- output_types: [conda, requirements]
packages:
- ninja
- output_types: conda
packages:
- c-compiler
- cmake>=3.26.4,!=3.30.0
- cudnn=8.8
- cxx-compiler
- cython>=3.0.0
- &doxygen doxygen==1.9.1
- libraft-headers==24.10.*,>=0.0.0a0
- librmm==24.10.*,>=0.0.0a0
- nanobind>=0.2.0
- &nccl nccl>=2.19
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: x86_64
cuda: "11.5"
packages:
- nvcc_linux-64=11.5
- matrix:
arch: aarch64
cuda: "11.8"
packages:
- nvcc_linux-aarch64=11.8
- matrix:
cuda: "12.*"
packages:
- cuda-nvcc
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: "11.2"
packages:
- cudatoolkit
- cuda-nvtx=11.4 # oldest available
- matrix:
cuda: "11.4"
packages:
- cudatoolkit
- cuda-nvtx=11.4 # oldest available
- matrix:
cuda: "11.5"
packages:
- cudatoolkit
- cuda-nvtx=11.5
- matrix:
cuda: "11.8"
packages:
- cudatoolkit
- cuda-nvtx=11.8
- matrix:
cuda: "12.*"
packages:
- cuda-cudart-dev
- cuda-nvml-dev
- cuda-nvtx
checks:
common:
- output_types: [conda, requirements]
packages:
- pre-commit
py_version:
specific:
- output_types: conda
matrices:
- matrix:
py: "3.10"
packages:
- python=3.10
- matrix:
py: "3.11"
packages:
- python=3.11
- matrix:
py: "3.12"
packages:
- python=3.12
- matrix:
packages:
- python>=3.10,<3.13
run:
common:
- output_types: [conda, requirements]
packages: []
test_cpp:
common:
- output_types: [conda]
packages:
- *nccl
test_python:
common:
- output_types: [conda]
packages:
- c-compiler
- cxx-compiler
- *nccl
- output_types: [conda, requirements]
packages:
- ninja
- numpy>=1.23,<3.0a0
- pytest
- pytest-forked
- pytest-xdist
specific:
- output_types: [conda]
matrices:
- matrix:
arch: x86_64
cuda: "11.2"
packages:
# It's impossible to create this environment with pyg because
# the pyg package has an explicit dependency on cudatoolkit=11.*
# and there simply isn't any build for cudatoolkit=11.2.
# Note that the packages for CUDA 11.2/11.4 environments are the
# ones from conda-forge (built only against CUDA 11.2) and
# *not* the pytorch channel. For CUDA 11.5/11.8 environments,
# we're using packages from the pytorch channel.
- pytorch=1.11.0=*cuda112*
- matrix:
arch: x86_64
cuda: "11.4"
packages:
# It's impossible to create this environment with pyg because
# the pyg package has an explicit dependency on cudatoolkit=11.*
# and there simply isn't any build for cudatoolkit=11.4.
# There is also no build of pytorch for CUDA 11.4 but the 11.2
# build should work in practice and doesn't require any
# cudatoolkit version explicitly.
- pytorch=1.11.0=*cuda112*
- matrix:
arch: x86_64
cuda: "11.5"
packages:
# This environment "just works" for both pytorch and pyg, but only
# with older pytorch versions since the newest ones aren't built
# against 11.5 anymore.
- pytorch=1.11.0=*cuda11.5*
- matrix:
arch: x86_64
cuda: "11.8"
packages:
# Since CUDA 11.6, pytorch switched to using the `cuda-*` packages
# as dependencies for its official conda package. These are only
# available from the nvidia channel at the moment, and this will
# probably continue once conda-forge has added these new packages
# since conda-forge will only add this from CUDA 12.0 onwards,
# at least in the near-term.
# Our own RAPIDS packages are dependent on the `cudatoolkit`
# package from conda-forge though, which means that we have to
# install both `cudatoolkit` version 11.8 and the `cuda-*` packages
# version 11.8 here.
# Starting with Pytorch 2.0, this works well though, since Pytorch
# has largely reduced its dependencies, so only part of the CUDA
# toolkit needs to be duplicated this way.
# If conda-forge supports the new cuda-* packages for CUDA 11.8
# at some point, then we can fully support/properly specify
# this environment.
- &pytorch pytorch>=2.0,<2.4.0a0
- pytorch-cuda=11.8
- matrix:
arch: aarch64
cuda: "11.8"
packages:
- *pytorch
- pytorch-cuda=11.8
- matrix:
packages:
docs:
common:
- output_types: [conda]
packages:
- *doxygen
- output_types: [conda, requirements]
packages:
- breathe
- graphviz
- ipython
- ipykernel
- nbsphinx
- numpydoc
- pydata-sphinx-theme
- recommonmark
- sphinx<6
- sphinx-copybutton
- sphinx-markdown-tables
- sphinxcontrib-websupport
pytorch_cpu:
common:
- output_types: [conda]
packages:
- *pytorch
- cpuonly
clang_tools:
common:
- output_types: [conda, requirements]
packages:
- gitpython
- output_types: conda
packages:
- clangxx==16.0.6
- clang-tools==16.0.6
rapids_build_skbuild:
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
python_build_wheel:
common:
- output_types: [pyproject]
packages:
- cmake>=3.26.4,!=3.30.0
- cython>=3.0.0
- ninja