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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:
- build
- cuda
- cuda_version
- checks
- docs
- py_version
- run
- test_python
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
py_build:
output: pyproject
pyproject_dir: python/cucim
extras:
table: build-system
includes:
- build
py_run:
output: pyproject
pyproject_dir: python/cucim
extras:
table: project
includes:
- run
py_optional_test:
output: pyproject
pyproject_dir: python/cucim
extras:
table: project.optional-dependencies
key: test
includes:
- test_python
py_develop:
output: pyproject
pyproject_dir: python/cucim
extras:
table: project.optional-dependencies
key: developer
includes:
- develop
py_develop:
output: pyproject
pyproject_dir: python/cucim
extras:
table: project.optional-dependencies
key: docs
includes:
- docs
channels:
- rapidsai
- rapidsai-nightly
- conda-forge
- nvidia
dependencies:
build:
common:
# Note:
# Currently omit pyproject output_type from cmake, ninja. The python
# build doesn't use these, but assumes that the C++ libcucim shared
# library had already previously been built and the .so file copied to
# python/cucim/src/cucim/clara/ before calling `pip install .`.
- output_types: [conda, requirements]
packages:
- cmake>=3.23.1,!=3.25.0
- ninja
- output_types: conda
packages:
- c-compiler
- cxx-compiler
- output_types: [requirements, pyproject]
packages:
- setuptools>=24.2.0
- wheel
specific:
- output_types: conda
matrices:
- matrix:
arch: x86_64
packages:
- gcc_linux-64=11.*
- sysroot_linux-64==2.17
- yasm
- 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:
- cuda-version=11.8
- nvcc_linux-64=11.8
- libcufile=1.4.0.31
- libcufile-dev=1.4.0.31
- libnvjpeg=11.6.0.55
- libnvjpeg-dev=11.6.0.55
- matrix:
arch: aarch64
cuda: "11.8"
packages:
- cuda-version=11.8
- nvcc_linux-aarch64=11.8
- libnvjpeg=11.6.0.55
- libnvjpeg-dev=11.6.0.55
- matrix:
cuda: "12.0"
packages:
- cuda-version=12.0
- cuda-nvcc
- libcufile-dev
- libnvjpeg-dev
- libnvjpeg-static
checks:
common:
- output_types: [conda, requirements]
packages:
- pre-commit
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: "11.*"
packages:
- cudatoolkit
- matrix:
cuda: "12.*"
packages:
- cuda-cudart-dev
- libnvjpeg-dev
- libcufile-dev
develop:
common:
- output_types: [conda, requirements, pyproject]
packages:
- pre-commit
- black
- ruff
- isort
docs:
common:
- output_types: [conda, requirements, pyproject]
packages:
- ipython
- nbsphinx
- numpydoc
- pydata-sphinx-theme
- recommonmark
# TODO: sphinx upper version limit can likely be removed after pydata 0.13
# is released. See https://github.com/pydata/pydata-sphinx-theme/issues/1094
- sphinx<6
py_version:
specific:
- output_types: conda
matrices:
- matrix:
py: "3.8"
packages:
- python=3.8
- matrix:
py: "3.9"
packages:
- python=3.9
- matrix:
py: "3.10"
packages:
- python=3.10
- matrix:
packages:
- python>=3.8,<3.11
run:
common:
- output_types: [conda, requirements, pyproject]
packages:
- lazy_loader>=0.1
- scikit-image>=0.19.0,<0.22.0a0
- scipy
- output_types: conda
packages:
- cupy>=12.0.0
- numpy>=1.21.3
# All dependencies below this point are specific to `cucim.clara` and
# are not needed for either `cucim.core` or `cucim.skimage`. I did
# not include these under a "pyproject" output so that it is still
# possible to run `pip install .` from the python/cucim folder
# without having build the C++ library at all. This allows, usage of
# usage of `cucim.skimage` on Windows, for example.
- click
- jbig
- libwebp-base
- xz
- zlib
- zstd
# Not sure where these go, if anywhere:
# - openslide
# - xorg-libxcb
- output_types: [requirements, pyproject]
packages:
- cupy-cuda11x>=12.0.0
- numpy
test_python:
common:
- output_types: [conda, requirements, pyproject]
packages:
- GPUtil>=1.4.0
- psutil>=5.8.0
- pytest-cov>=2.12.1
- pytest-lazy-fixture>=0.6.3
- pytest-xdist
- pytest>=6.2.4
- tifffile>=2022.7.28
- pooch>=1.6.0 # needed to download scikit-image sample data
- output_types: [conda]
packages:
- imagecodecs>=2021.6.8
- matplotlib-base
- openslide-python>=1.3.0
- pip
- pip:
- opencv-python-headless>=4.6
- output_types: [requirements, pyproject]
packages:
# skip packages on arm64 that don't provide a wheel
- imagecodecs>=2021.6.8; platform_machine=='x86_64'
- openslide-python>=1.3.0; platform_machine=='x86_64'
- matplotlib
- opencv-python-headless>=4.6
- click