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adds scikit core to build arrayfire binaries (#12)
* adds scikit core to build arrayfire binaries * export set_backend * enable source builds without binaries * adds README with build instructions * move unified functions to Backend class * temporary revert hasattr * black formatting * _backend import order * unused import _backend.py
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‎CMakeLists.txt

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cmake_minimum_required(VERSION 3.20)
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project(
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${SKBUILD_PROJECT_NAME}
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LANGUAGES C CXX
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VERSION ${SKBUILD_PROJECT_VERSION})
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find_package(Python COMPONENTS Interpreter Development.Module)
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if(DEFINED ENV{AF_BUILD_LOCAL_LIBS})
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include(FetchContent)
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#set(NO_SONAME)
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FetchContent_Declare(
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arrayfire
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GIT_REPOSITORY https://github.com/arrayfire/arrayfire.git
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GIT_TAG v3.9
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)
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#TODO: change package name to match repository/project name?
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#set(AF_INSTALL_CMAKE_DIR "${SKBUILD_PROJECT_NAME}")
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set(AF_INSTALL_BIN_DIR "arrayfire_wrapper/binaries")
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set(AF_INSTALL_CMAKE_DIR "arrayfire_wrapper/binaries")
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set(AF_INSTALL_DOC_DIR "arrayfire_wrapper/binaries")
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set(AF_INSTALL_EXAMPLE_DIR "arrayfire_wrapper/binaries")
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set(AF_INSTALL_INC_DIR "arrayfire_wrapper/binaries")
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set(AF_INSTALL_LIB_DIR "arrayfire_wrapper/binaries")
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set(FG_INSTALL_LIB_DIR "arrayfire_wrapper/binaries")
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FetchContent_MakeAvailable(arrayfire)
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endif()
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# Testing artifacts
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file(WRITE ${CMAKE_CURRENT_BINARY_DIR}/generated.txt "Testing")
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install(
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FILES ${CMAKE_CURRENT_BINARY_DIR}/generated.txt
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DESTINATION arrayfire_wrapper
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COMPONENT Generated)
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file(WRITE ${CMAKE_CURRENT_BINARY_DIR}/generated_ignored.txt "Testing")
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install(FILES ${CMAKE_CURRENT_BINARY_DIR}/generated_ignored.txt
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DESTINATION arrayfire_wrapper)

‎LICENSE

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BSD 3-Clause License
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Copyright (c) 2023, Anton
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Copyright (c) 2023, ArrayFire
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are met:

‎README.md

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# arrayfire-binary-python-wrapper
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Arrayfire python C library wrapper
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## Coverage
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- [x] Computer Vision
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- [x] Events
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- [x] Functions to Create and Modify Arrays
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- [x] Functions to Work with Internal Array Layout
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- [x] Image Processing
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- [x] Features
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- [x] Input and Output Functions
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- [x] Interface Functions
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- [x] Linear Algebra
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- [x] Machine Learning
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- [x] Mathematical Functions
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- [x] Signal Processing
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- [x] Statistics
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- [x] Unified API Functions
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- [x] Vector Algorithms
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[ArrayFire](https://github.com/arrayfire/arrayfire) is a high performance library for parallel computing with an easy-to-use API. It enables users to write scientific computing code that is portable across CUDA, OpenCL and CPU devices.
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This project is meant to provide thin Python bindings for the ArrayFire C library. It also decouples releases of the main C/C++ library from the Python library by acting as a intermediate library and only wrapping the provided C calls.
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This allows the building of large binary wheels only when the underlying ArrayFire version is increased, and the fully-featured Python library can be developed atop independently. The package is not intended to be used directly and merely exposes the
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C functionality required by downstream implementations. This package can exist in two forms, with a bundled binary distribution, or merely as a loader that will load the ArrayFire library from a system or user level install.
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# Installing
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The arrayfire-binary-python-wrapper can be installed from a variety of sources. [Pre-built wheels](https://repo.arrayfire.com/python/wheels/3.9.0/) are available for a number of systems and toolkits. These will include a binary distribution of the ArrayFire libraries. Installing from PyPI directly will only include a wrapper-only, source distribution that will not contain binaries. In this case, wrapper-only installations will require a separate installation of the ArrayFire C/C++ libraries.
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You can get the ArrayFire C/C++ library from the following sources:
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- [Download and install binaries](https://arrayfire.com/download)
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- [Build and install from source](https://github.com/arrayfire/arrayfire)
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**Install the last stable version of python wrapper:**
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```
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pip install arrayfire-binary-python-wrapper
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```
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**Install a pre-built wheel:**
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```
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pip install arrayfire-binary-python-wrapper -f https://repo.arrayfire.com/python/wheels/3.9.0/
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```
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# Building
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The arrayfire-binary-python-wrapper can build wheels in packaged-binary or in system-wrapper modes.
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[scikit-build-core](https://github.com/scikit-build/scikit-build-core) is used to provide the python build backend.
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The minimal, wrapper-only mode that relies on a system install will be built by default though the regular python build process. For example:
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```
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pipx run build --wheel
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```
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Building a full pre-packaged local binary is an involved process that will require referencing the regular ArrayFire [build](https://github.com/arrayfire/arrayfire/wiki/Build-Instructions-for-Linux) [procedures](https://github.com/arrayfire/arrayfire/wiki/Build-Instructions-for-Windows).
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Besides the regular ArrayFire CMake configuration, building the binaries is an opt-in process that is set by an environment variable `AF_BUILD_LOCAL_LIBS=1`. Once that environment variable is set, scikit-build-core will take care of cloning ArrayFire, building, and including the necessary binaries.
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# Contributing
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The community of ArrayFire developers invites you to build with us if you are
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interested and able to write top-performing tensor functions. Together we can
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fulfill [The ArrayFire
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Mission](https://github.com/arrayfire/arrayfire/wiki/The-ArrayFire-Mission-Statement)
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for fast scientific computing for all.
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Contributions of any kind are welcome! Please refer to [the
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wiki](https://github.com/arrayfire/arrayfire/wiki) and our [Code of
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Conduct](33) to learn more about how you can get involved with the ArrayFire
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Community through
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[Sponsorship](https://github.com/arrayfire/arrayfire/wiki/Sponsorship),
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[Developer
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Commits](https://github.com/arrayfire/arrayfire/wiki/Contributing-Code-to-ArrayFire),
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or [Governance](https://github.com/arrayfire/arrayfire/wiki/Governance).
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# Citations and Acknowledgements
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If you redistribute ArrayFire, please follow the terms established in [the
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license](LICENSE).
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ArrayFire development is funded by AccelerEyes LLC and several third parties,
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please see the list of [acknowledgements](ACKNOWLEDGEMENTS.md) for an
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expression of our gratitude.
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# Support and Contact Info
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* [Slack Chat](https://join.slack.com/t/arrayfire-org/shared_invite/MjI4MjIzMDMzMTczLTE1MDI5ODg4NzYtN2QwNGE3ODA5OQ)
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* [Google Groups](https://groups.google.com/forum/#!forum/arrayfire-users)
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* ArrayFire Services: [Consulting](http://arrayfire.com/consulting) | [Support](http://arrayfire.com/download) | [Training](http://arrayfire.com/training)
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# Trademark Policy
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The literal mark "ArrayFire" and ArrayFire logos are trademarks of AccelerEyes
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LLC (dba ArrayFire). If you wish to use either of these marks in your own
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project, please consult [ArrayFire's Trademark
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Policy](http://arrayfire.com/trademark-policy/)

‎arrayfire_wrapper/__init__.py

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"Backend",
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"BackendType",
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"get_backend",
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"set_backend",
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]
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from ._backend import Backend, BackendType, get_backend
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from ._backend import Backend, BackendType, get_backend, set_backend
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__all__ += [
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"Dtype",

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