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Add support for the installation via pip.
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‎README.md‎

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### Installing
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#### Install via CMake
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The library supports the `install` target:
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```bash
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export CPLUS_INCLUDE_PATH=${CMAKE_INSTALL_PREFIX}/include:${CPLUS_INCLUDE_PATH}
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```
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If our library was built with the Python bindings enabled, the `PYTHONPATH` must additionally be set:
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```bash
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export PYTHONPATH=${CMAKE_INSTALL_PREFIX}/lib:${CMAKE_INSTALL_PREFIX}/lib64:${PYTHONPATH}
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```
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#### Install via pip
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We also support a pip packages that can be used to install our library:
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```bash
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pip install plssvm
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```
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This pip install behaves **as if** the CMake `all_python` preset is used.
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This means that the `PLSSVM_TARGET_PLATFORMS` are automatically determined and PLSSVM is build with all supported
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backends that available on the target machine at the point of the `pip install plssvm` invocation.
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To check the installation, including, e.g., the installed backends, we provide the `plssvm-install-check` command after
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PLSSVM has been installed via pip.
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An example output of this command can look like:
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```text
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PLSSVM - Parallel Least Squares Support Vector Machine (3.0.0)
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Copyright(C) 2018-today The PLSSVM project - All Rights Reserved
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This is free software distributed under the MIT license.
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Available target platforms: TargetPlatform.AUTOMATIC, TargetPlatform.GPU_NVIDIA, TargetPlatform.CPU
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Default target platform: TargetPlatform.GPU_NVIDIA
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Available backends: BackendType.AUTOMATIC, BackendType.OPENMP, BackendType.CUDA, BackendType.OPENCL, BackendType.SYCL
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Default backend for target platform TargetPlatform.GPU_NVIDIA: BackendType.CUDA
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Default backend for target platform TargetPlatform.CPU: BackendType.SYCL
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Available SYCL implementations: ImplementationType.AUTOMATIC, ImplementationType.ADAPTIVECPP
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Repository: https://github.com/SC-SGS/PLSSVM.git
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Documentation: https://sc-sgs.github.io/PLSSVM
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Issues: https://github.com/SC-SGS/PLSSVM/issues
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```
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## Usage
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PLSSVM provides three executables: `plssvm-train`, `plssvm-predict`, and `plssvm-scale`.
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<img alt="Example regression output using a sine curve." src="https://github.com/SC-SGS/PLSSVM/raw/regression/.figures/regression_example.png" width="80%">
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</p>
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**Note:** it may be necessary to set the environment variable `PYTHONPATH` to the `lib` folder in the PLSSVM install path.
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```bash
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export PYTHONPATH=${CMAKE_INSTALL_PREFIX}/lib:${CMAKE_INSTALL_PREFIX}/lib64:${PYTHONPATH}
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```
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Note that currently not all sklearn `SVC` and `SVR` functionality has been implemented in PLSSVM.
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The respective functions will throw a Python `AttributeError` if called.
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For a detailed overview of the functions that are currently implemented, see [our API documentation](bindings/Python/README.md).

‎bindings/Python/CMakeLists.txt‎

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# append pybind11 bindings library to installed targets
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append_local_and_parent(PLSSVM_TARGETS_TO_INSTALL ${PLSSVM_PYTHON_BINDINGS_LIBRARY_NAME})
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# install the __init__.py file so Python recognizes the package when installed via pip
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# install the __cli__.py file so the PLSSVM executables can be used when installed via pip
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# install the __install_check__.py file creating a new executable plssvm-install-check outputting some information when installed via pip
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include(GNUInstallDirs)
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install(FILES "${CMAKE_CURRENT_SOURCE_DIR}/__init__.py"
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"${CMAKE_CURRENT_SOURCE_DIR}/__cli__.py"
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"${CMAKE_CURRENT_SOURCE_DIR}/__install_check__.py"
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DESTINATION "${CMAKE_INSTALL_LIBDIR}"
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)

‎bindings/Python/__cli__.py‎

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import sys
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import subprocess
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from pathlib import Path
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# support for plssvm-train including command line arguments
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def train():
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exe_path = Path(__file__).parent / "plssvm-train"
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subprocess.run([str(exe_path)] + sys.argv[1:])
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# support for plssvm-predict including command line arguments
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def predict():
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exe_path = Path(__file__).parent / "plssvm-predict"
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subprocess.run([str(exe_path)] + sys.argv[1:])
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# support for plssvm-scale including command line arguments
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def scale():
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exe_path = Path(__file__).parent / "plssvm-scale"
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subprocess.run([str(exe_path)] + sys.argv[1:])

‎bindings/Python/__init__.py‎

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# import all bindings from the compiled PLSSVM module
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from .plssvm import *
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# explicitly set the module level attributes
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__doc__ = plssvm.__doc__
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__version__ = plssvm.__version__

‎bindings/Python/__install_check__.py‎

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import plssvm
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# print information regarding the current installation after an installation via pip
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def check():
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print("{} ({})".format(plssvm.__doc__, plssvm.__version__))
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print()
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print("Copyright(C) 2018-today The PLSSVM project - All Rights Reserved")
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print("This is free software distributed under the MIT license.")
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print()
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print("Available target platforms: {}".format(', '.join(str(target) for target in plssvm.list_available_target_platforms())))
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print("Default target platform: {}\n".format(str(plssvm.determine_default_target_platform())))
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print("Available backends: {}".format(', '.join(str(backend) for backend in plssvm.list_available_backends())))
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for target in plssvm.list_available_target_platforms():
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if target == plssvm.TargetPlatform.AUTOMATIC:
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continue
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try:
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backend = plssvm.determine_default_backend(available_target_platforms=[target])
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print("Default backend for target platform {}: {}".format(str(target), str(backend)))
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except:
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pass
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print()
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if plssvm.BackendType.SYCL in plssvm.list_available_backends():
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print("Available SYCL implementations: {}".format(', '.join(str(impl) for impl in plssvm.sycl.list_available_sycl_implementations())))
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print()
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print()
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print("Repository: https://github.com/SC-SGS/PLSSVM.git")
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print("Documentation: https://sc-sgs.github.io/PLSSVM/")
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print("Issues: https://github.com/SC-SGS/PLSSVM/issues")

‎pyproject.toml‎

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[build-system]
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requires = ["scikit-build-core"]
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build-backend = "scikit_build_core.build"
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# set the necessary CMake build options
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[tool.scikit-build]
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cmake.args = [
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"--preset all_python",
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"-DCMAKE_INSTALL_LIBDIR=plssvm",
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"-DCMAKE_INSTALL_BINDIR=plssvm",
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"-DCMAKE_INSTALL_INCLUDEDIR=plssvm",
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"-DCMAKE_INSTALL_MANDIR=plssvm",
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"-DCMAKE_INSTALL_DATAROOTDIR=plssvm/cmake",
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"-DCMAKE_INSTALL_RPATH=$ORIGIN"
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]
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sdist.exclude = ["build*/", "dist/", "docs/html/", ".github", ".jenkins", "examples", "install", "tests", ".clang*", ".clion*", ".gitignore"]
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# expose the PLSSVM executables after a pip install
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[project.scripts]
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plssvm-train = "plssvm.__cli__:train"
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plssvm-predict = "plssvm.__cli__:predict"
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plssvm-scale = "plssvm.__cli__:scale"
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plssvm-install-check = "plssvm.__install_check__:check"
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# project specific metadata
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[project]
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name = "plssvm"
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version = "3.0.3" # TODO: fix
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description = "PLSSVM - A high-performance Least Squares Support Vector Machine implementation for GPUs and CPUs"
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readme = "README.md"
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license = { file = "LICENSE.md" }
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authors = [
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{ name = "Alexander Van Craen, Marcel Breyer" }
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]
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maintainers = [
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{ name = "University of Stuttgart IPVS - SC", email = "[email protected]" }
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]
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dependencies = ["numpy"]
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requires-python = ">=3.8"
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classifiers = [
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"Development Status :: 5 - Production/Stable",
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"Environment :: GPU",
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"Intended Audience :: Science/Research",
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"License :: OSI Approved :: MIT License",
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"Natural Language :: English",
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"Operating System :: POSIX :: Linux",
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"Operating System :: Microsoft :: Windows",
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"Programming Language :: C++",
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"Programming Language :: Python :: 3",
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"Topic :: Scientific/Engineering :: Artificial Intelligence"
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]
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# project specific URLs
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[project.urls]
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homepage = "https://www.ipvs.uni-stuttgart.de/departments/sc/research/projects/recent/plssvm/"
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documentation = "https://sc-sgs.github.io/PLSSVM/"
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repository = "https://github.com/SC-SGS/PLSSVM.git"
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issues = "https://github.com/SC-SGS/PLSSVM/issues"

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