From d3e54673715ed8374002ec4164bd519ec2bd49a8 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Wed, 12 Apr 2023 03:57:08 +0000 Subject: automatic import of python-pytorch-memlab --- .gitignore | 1 + python-pytorch-memlab.spec | 135 +++++++++++++++++++++++++++++++++++++++++++++ sources | 1 + 3 files changed, 137 insertions(+) create mode 100644 python-pytorch-memlab.spec create mode 100644 sources diff --git a/.gitignore b/.gitignore index e69de29..9706151 100644 --- a/.gitignore +++ b/.gitignore @@ -0,0 +1 @@ +/pytorch_memlab-0.2.4.tar.gz diff --git a/python-pytorch-memlab.spec b/python-pytorch-memlab.spec new file mode 100644 index 0000000..976445f --- /dev/null +++ b/python-pytorch-memlab.spec @@ -0,0 +1,135 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pytorch-memlab +Version: 0.2.4 +Release: 1 +Summary: A lab to do simple and accurate memory experiments on pytorch +License: MIT +URL: https://github.com/Stonesjtu/pytorch_memlab +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/ca/a9/0554fae8883b2a646720e0e1d84d1bdef57e90ee3c244686f589052c3e0a/pytorch_memlab-0.2.4.tar.gz +BuildArch: noarch + + +%description +[![Build Status](https://travis-ci.com/Stonesjtu/pytorch_memlab.svg?token=vyTdxHbi1PCRzV6disHp&branch=master)](https://travis-ci.com/Stonesjtu/pytorch_memlab) +![PyPI](https://img.shields.io/pypi/v/pytorch_memlab.svg) +[![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/Stonesjtu/pytorch_memlab.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/Stonesjtu/pytorch_memlab/context:python) +![PyPI - Downloads](https://img.shields.io/pypi/dm/pytorch_memlab.svg) +A simple and accurate **CUDA** memory management laboratory for pytorch, +it consists of different parts about the memory: +- Features: + - Memory Profiler: A `line_profiler` style CUDA memory profiler with simple API. + - Memory Reporter: A reporter to inspect tensors occupying the CUDA memory. + - Courtesy: An interesting feature to temporarily move all the CUDA tensors into + CPU memory for courtesy, and of course the backward transferring. + - IPython support through `%mlrun`/`%%mlrun` line/cell magic + commands. +- Table of Contents + * [Installation](#installation) + * [User-Doc](#user-doc) + + [Memory Profiler](#memory-profiler) + + [IPython support](#ipython-support) + + [Memory Reporter](#memory-reporter) + + [Courtesy](#courtesy) + + [ACK](#ack) + * [CHANGES](#changes) + +%package -n python3-pytorch-memlab +Summary: A lab to do simple and accurate memory experiments on pytorch +Provides: python-pytorch-memlab +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-pytorch-memlab +[![Build Status](https://travis-ci.com/Stonesjtu/pytorch_memlab.svg?token=vyTdxHbi1PCRzV6disHp&branch=master)](https://travis-ci.com/Stonesjtu/pytorch_memlab) +![PyPI](https://img.shields.io/pypi/v/pytorch_memlab.svg) +[![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/Stonesjtu/pytorch_memlab.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/Stonesjtu/pytorch_memlab/context:python) +![PyPI - Downloads](https://img.shields.io/pypi/dm/pytorch_memlab.svg) +A simple and accurate **CUDA** memory management laboratory for pytorch, +it consists of different parts about the memory: +- Features: + - Memory Profiler: A `line_profiler` style CUDA memory profiler with simple API. + - Memory Reporter: A reporter to inspect tensors occupying the CUDA memory. + - Courtesy: An interesting feature to temporarily move all the CUDA tensors into + CPU memory for courtesy, and of course the backward transferring. + - IPython support through `%mlrun`/`%%mlrun` line/cell magic + commands. +- Table of Contents + * [Installation](#installation) + * [User-Doc](#user-doc) + + [Memory Profiler](#memory-profiler) + + [IPython support](#ipython-support) + + [Memory Reporter](#memory-reporter) + + [Courtesy](#courtesy) + + [ACK](#ack) + * [CHANGES](#changes) + +%package help +Summary: Development documents and examples for pytorch-memlab +Provides: python3-pytorch-memlab-doc +%description help +[![Build Status](https://travis-ci.com/Stonesjtu/pytorch_memlab.svg?token=vyTdxHbi1PCRzV6disHp&branch=master)](https://travis-ci.com/Stonesjtu/pytorch_memlab) +![PyPI](https://img.shields.io/pypi/v/pytorch_memlab.svg) +[![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/Stonesjtu/pytorch_memlab.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/Stonesjtu/pytorch_memlab/context:python) +![PyPI - Downloads](https://img.shields.io/pypi/dm/pytorch_memlab.svg) +A simple and accurate **CUDA** memory management laboratory for pytorch, +it consists of different parts about the memory: +- Features: + - Memory Profiler: A `line_profiler` style CUDA memory profiler with simple API. + - Memory Reporter: A reporter to inspect tensors occupying the CUDA memory. + - Courtesy: An interesting feature to temporarily move all the CUDA tensors into + CPU memory for courtesy, and of course the backward transferring. + - IPython support through `%mlrun`/`%%mlrun` line/cell magic + commands. +- Table of Contents + * [Installation](#installation) + * [User-Doc](#user-doc) + + [Memory Profiler](#memory-profiler) + + [IPython support](#ipython-support) + + [Memory Reporter](#memory-reporter) + + [Courtesy](#courtesy) + + [ACK](#ack) + * [CHANGES](#changes) + +%prep +%autosetup -n pytorch-memlab-0.2.4 + +%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-pytorch-memlab -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed Apr 12 2023 Python_Bot - 0.2.4-1 +- Package Spec generated diff --git a/sources b/sources new file mode 100644 index 0000000..ba9c330 --- /dev/null +++ b/sources @@ -0,0 +1 @@ +4112c26e120708e558e1d841a6623b92 pytorch_memlab-0.2.4.tar.gz -- cgit v1.2.3