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diff --git a/python-pyrevolve.spec b/python-pyrevolve.spec new file mode 100644 index 0000000..3b584a3 --- /dev/null +++ b/python-pyrevolve.spec @@ -0,0 +1,300 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pyrevolve +Version: 2.2.2 +Release: 1 +Summary: Python wrapper for Revolve checkpointing +License: MIT +URL: https://github.com/opesci/pyrevolve/ +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/72/4e/d0926921a4fedd0fdf786e4ce5450e5a1eeebb5a2225110fc72bf17dd0a1/pyrevolve-2.2.2.tar.gz +BuildArch: noarch + + +%description +# Checkpointing + +The adjoint computation of an unsteady nonlinear primal function requires the +full primal trajectory in reverse temporal order. Storing this can exceed the +available memory. In that case, Checkpointing can be used to store the state +only at carefully selected points in time. From there, the forward computation +can be restarted to recompute lost sections of the trajectory when they are +needed during the adjoint computation. This is always a tradeoff between memory +and runtime. The classic and provably optimal way to do this for a known number +of time steps is [Revolve](https://doi.org/10.1145/347837.347846), and there are other algorithms for optimal online +checkpointing if the number of steps is unknown a priori, or for multistage +checkpointing if there are multiple layers of storage, e.g. memory and hard +drive. + + +# PyRevolve + +The pyrevolve library contains two parts: crevolve, which is a thin Python +wrapper around a previously published [C++ implementation](https://www.mathematik.hu-berlin.de/de/forschung/forschungsgebiete/mathematische-optimierung/andrea-walther/walther-software), and pyrevolve +itself, which sits on top of crevolve and manages data and computation +management for the user. + +The C++ files in this package are slightly modified to play more nicely with +Python, but the original is available from the link below. In addition, there +is a C wrapper around the C++ library, to simplify the interface with Python. +This C wrapper is taken from [libadjoint](https://bitbucket.org/dolfin-adjoint/libadjoint). + + + +# Installation +Since PyRevolve is distributed as source, you must have a functional C/C++ +compiler in your environment before trying to install PyRevolve. The +installation procedure respects the standard environment variables +like CC/CXX. + +The simplest installation is through pip by simply doing: + + pip install pyrevolve + +If you would like to have a local development copy that you can edit, +clone the repo and call the following command in the home directory: + + pip install -e . + +If you face any installation issues, first check that you really do +have a functional C++ compiler, either available as `g++` in the path +or pointed to by the environment variable `CXX`. If this is not the +reason, please raise a issue here or on +[this](https://opesci-slackin.now.sh) Slack channel. +# Usage + +There are two wrappers: a _classic_ wrapper that follows the behaviour of Revolve +as described in the papers, and leaves the data mangement, the actual copying +of data, and the calling of operators to the user. An example of how to use it +can be executed by calling + + python examples/use_classic.py + +The other, _modernised_ wrapper, takes care of all this. The user creates a +Revolver object, and passes a forward operator, reverse operator, and +checkpoint operator to it. The Revolver provides two important methods: +`apply_forward`, and `apply_reverse`. A call to `apply_forward` executes the +forward computation, while creating the necessary checkpoints for the reverse +computation. After this, a user may also call the `apply_reverse` method to +compute the adjoints. + +For this to work, the user is responsible that the operators have an `apply()` +method that takes arguments `t_start` and `t_end`, and that the checkpoint +object has a property `size` to report the size of one checkpoint, and methods +`load(ptr)` and `save(ptr)` that deep-copy all time-dependent live data into +a location given in `ptr`. + +An example of this can be found here: + + python examples/use_modernised.py + + + +%package -n python3-pyrevolve +Summary: Python wrapper for Revolve checkpointing +Provides: python-pyrevolve +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-pyrevolve +# Checkpointing + +The adjoint computation of an unsteady nonlinear primal function requires the +full primal trajectory in reverse temporal order. Storing this can exceed the +available memory. In that case, Checkpointing can be used to store the state +only at carefully selected points in time. From there, the forward computation +can be restarted to recompute lost sections of the trajectory when they are +needed during the adjoint computation. This is always a tradeoff between memory +and runtime. The classic and provably optimal way to do this for a known number +of time steps is [Revolve](https://doi.org/10.1145/347837.347846), and there are other algorithms for optimal online +checkpointing if the number of steps is unknown a priori, or for multistage +checkpointing if there are multiple layers of storage, e.g. memory and hard +drive. + + +# PyRevolve + +The pyrevolve library contains two parts: crevolve, which is a thin Python +wrapper around a previously published [C++ implementation](https://www.mathematik.hu-berlin.de/de/forschung/forschungsgebiete/mathematische-optimierung/andrea-walther/walther-software), and pyrevolve +itself, which sits on top of crevolve and manages data and computation +management for the user. + +The C++ files in this package are slightly modified to play more nicely with +Python, but the original is available from the link below. In addition, there +is a C wrapper around the C++ library, to simplify the interface with Python. +This C wrapper is taken from [libadjoint](https://bitbucket.org/dolfin-adjoint/libadjoint). + + + +# Installation +Since PyRevolve is distributed as source, you must have a functional C/C++ +compiler in your environment before trying to install PyRevolve. The +installation procedure respects the standard environment variables +like CC/CXX. + +The simplest installation is through pip by simply doing: + + pip install pyrevolve + +If you would like to have a local development copy that you can edit, +clone the repo and call the following command in the home directory: + + pip install -e . + +If you face any installation issues, first check that you really do +have a functional C++ compiler, either available as `g++` in the path +or pointed to by the environment variable `CXX`. If this is not the +reason, please raise a issue here or on +[this](https://opesci-slackin.now.sh) Slack channel. +# Usage + +There are two wrappers: a _classic_ wrapper that follows the behaviour of Revolve +as described in the papers, and leaves the data mangement, the actual copying +of data, and the calling of operators to the user. An example of how to use it +can be executed by calling + + python examples/use_classic.py + +The other, _modernised_ wrapper, takes care of all this. The user creates a +Revolver object, and passes a forward operator, reverse operator, and +checkpoint operator to it. The Revolver provides two important methods: +`apply_forward`, and `apply_reverse`. A call to `apply_forward` executes the +forward computation, while creating the necessary checkpoints for the reverse +computation. After this, a user may also call the `apply_reverse` method to +compute the adjoints. + +For this to work, the user is responsible that the operators have an `apply()` +method that takes arguments `t_start` and `t_end`, and that the checkpoint +object has a property `size` to report the size of one checkpoint, and methods +`load(ptr)` and `save(ptr)` that deep-copy all time-dependent live data into +a location given in `ptr`. + +An example of this can be found here: + + python examples/use_modernised.py + + + +%package help +Summary: Development documents and examples for pyrevolve +Provides: python3-pyrevolve-doc +%description help +# Checkpointing + +The adjoint computation of an unsteady nonlinear primal function requires the +full primal trajectory in reverse temporal order. Storing this can exceed the +available memory. In that case, Checkpointing can be used to store the state +only at carefully selected points in time. From there, the forward computation +can be restarted to recompute lost sections of the trajectory when they are +needed during the adjoint computation. This is always a tradeoff between memory +and runtime. The classic and provably optimal way to do this for a known number +of time steps is [Revolve](https://doi.org/10.1145/347837.347846), and there are other algorithms for optimal online +checkpointing if the number of steps is unknown a priori, or for multistage +checkpointing if there are multiple layers of storage, e.g. memory and hard +drive. + + +# PyRevolve + +The pyrevolve library contains two parts: crevolve, which is a thin Python +wrapper around a previously published [C++ implementation](https://www.mathematik.hu-berlin.de/de/forschung/forschungsgebiete/mathematische-optimierung/andrea-walther/walther-software), and pyrevolve +itself, which sits on top of crevolve and manages data and computation +management for the user. + +The C++ files in this package are slightly modified to play more nicely with +Python, but the original is available from the link below. In addition, there +is a C wrapper around the C++ library, to simplify the interface with Python. +This C wrapper is taken from [libadjoint](https://bitbucket.org/dolfin-adjoint/libadjoint). + + + +# Installation +Since PyRevolve is distributed as source, you must have a functional C/C++ +compiler in your environment before trying to install PyRevolve. The +installation procedure respects the standard environment variables +like CC/CXX. + +The simplest installation is through pip by simply doing: + + pip install pyrevolve + +If you would like to have a local development copy that you can edit, +clone the repo and call the following command in the home directory: + + pip install -e . + +If you face any installation issues, first check that you really do +have a functional C++ compiler, either available as `g++` in the path +or pointed to by the environment variable `CXX`. If this is not the +reason, please raise a issue here or on +[this](https://opesci-slackin.now.sh) Slack channel. +# Usage + +There are two wrappers: a _classic_ wrapper that follows the behaviour of Revolve +as described in the papers, and leaves the data mangement, the actual copying +of data, and the calling of operators to the user. An example of how to use it +can be executed by calling + + python examples/use_classic.py + +The other, _modernised_ wrapper, takes care of all this. The user creates a +Revolver object, and passes a forward operator, reverse operator, and +checkpoint operator to it. The Revolver provides two important methods: +`apply_forward`, and `apply_reverse`. A call to `apply_forward` executes the +forward computation, while creating the necessary checkpoints for the reverse +computation. After this, a user may also call the `apply_reverse` method to +compute the adjoints. + +For this to work, the user is responsible that the operators have an `apply()` +method that takes arguments `t_start` and `t_end`, and that the checkpoint +object has a property `size` to report the size of one checkpoint, and methods +`load(ptr)` and `save(ptr)` that deep-copy all time-dependent live data into +a location given in `ptr`. + +An example of this can be found here: + + python examples/use_modernised.py + + + +%prep +%autosetup -n pyrevolve-2.2.2 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-pyrevolve -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 2.2.2-1 +- Package Spec generated |