automatic import of python-pytorch-memlabopeneuler20.03

3 files changed, 137 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..9706151 100644
--- a/.gitignore
+++ b/.gitignore
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+/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
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+%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 <Python_Bot@openeuler.org> - 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