automatic import of python-bxtorch

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diff --git a/.gitignore b/.gitignore
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+/BxTorch-0.7.3.tar.gz
diff --git a/python-bxtorch.spec b/python-bxtorch.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-BxTorch
+Version:	0.7.3
+Release:	1
+Summary:	Large-Scale Machine and Deep Learning in PyTorch.
+License:	License :: OSI Approved :: MIT License
+URL:		https://github.com/borchero/bxtorch
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/5b/92/2877000b7111453fc7b3af3aa7714e7cc98cfb5fe2f39ed008906d6f47e9/BxTorch-0.7.3.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-torch
+Requires:	python3-numpy
+Requires:	python3-scipy
+Requires:	python3-numba
+Requires:	python3-scikit-learn
+
+%description
+# BxTorch
+
+BxTorch is a high-level library for large-scale machine learning in [PyTorch](https://pytorch.org).
+It is engineered both to cut obsolete boilerplate code while preserving the flexibility of PyTorch to create just about any deep learning model.
+
+## Installation
+
+BxTorch is available on PyPi, so simply run the following command:
+
+```bash
+pip install bxtorch
+```
+
+## Features
+
+Generally, BxTorch provides an object-oriented approach to abstracting
+PyTorch's API. The core design objective is to provide an API both as simple
+and as extensible as possible. The goal of this library is to be able to iterate between different models easily instead of squeezing out milliseconds
+where it is not required.
+
+Still, being focused on large-scale machine learning, BxTorch aims to make it
+as easy as possible working with large datasets. This includes out-of-the-box
+multi-GPU support where the user *does not need to write a single line of
+code*. Currently, BxTorch only provides means for running training/inference
+on a single machine. In case this is insufficient, you might be better off
+using PyTorch's `distributed` package directly.
+
+It must be emphasized that BxTorch is not meant to be a wrapper for PyTorch as
+Keras is for TensorFlow - it only provides *extensions*.
+
+## Documentation
+
+Examples of the usage of BxTorch can be found in the [docs folder](docs).
+Method documentation is currently only available as [docstrings](bxtorch).
+
+## License
+
+BxTorch is licensed under the [MIT License](LICENSE).
+
+
+
+
+%package -n python3-BxTorch
+Summary:	Large-Scale Machine and Deep Learning in PyTorch.
+Provides:	python-BxTorch
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-BxTorch
+# BxTorch
+
+BxTorch is a high-level library for large-scale machine learning in [PyTorch](https://pytorch.org).
+It is engineered both to cut obsolete boilerplate code while preserving the flexibility of PyTorch to create just about any deep learning model.
+
+## Installation
+
+BxTorch is available on PyPi, so simply run the following command:
+
+```bash
+pip install bxtorch
+```
+
+## Features
+
+Generally, BxTorch provides an object-oriented approach to abstracting
+PyTorch's API. The core design objective is to provide an API both as simple
+and as extensible as possible. The goal of this library is to be able to iterate between different models easily instead of squeezing out milliseconds
+where it is not required.
+
+Still, being focused on large-scale machine learning, BxTorch aims to make it
+as easy as possible working with large datasets. This includes out-of-the-box
+multi-GPU support where the user *does not need to write a single line of
+code*. Currently, BxTorch only provides means for running training/inference
+on a single machine. In case this is insufficient, you might be better off
+using PyTorch's `distributed` package directly.
+
+It must be emphasized that BxTorch is not meant to be a wrapper for PyTorch as
+Keras is for TensorFlow - it only provides *extensions*.
+
+## Documentation
+
+Examples of the usage of BxTorch can be found in the [docs folder](docs).
+Method documentation is currently only available as [docstrings](bxtorch).
+
+## License
+
+BxTorch is licensed under the [MIT License](LICENSE).
+
+
+
+
+%package help
+Summary:	Development documents and examples for BxTorch
+Provides:	python3-BxTorch-doc
+%description help
+# BxTorch
+
+BxTorch is a high-level library for large-scale machine learning in [PyTorch](https://pytorch.org).
+It is engineered both to cut obsolete boilerplate code while preserving the flexibility of PyTorch to create just about any deep learning model.
+
+## Installation
+
+BxTorch is available on PyPi, so simply run the following command:
+
+```bash
+pip install bxtorch
+```
+
+## Features
+
+Generally, BxTorch provides an object-oriented approach to abstracting
+PyTorch's API. The core design objective is to provide an API both as simple
+and as extensible as possible. The goal of this library is to be able to iterate between different models easily instead of squeezing out milliseconds
+where it is not required.
+
+Still, being focused on large-scale machine learning, BxTorch aims to make it
+as easy as possible working with large datasets. This includes out-of-the-box
+multi-GPU support where the user *does not need to write a single line of
+code*. Currently, BxTorch only provides means for running training/inference
+on a single machine. In case this is insufficient, you might be better off
+using PyTorch's `distributed` package directly.
+
+It must be emphasized that BxTorch is not meant to be a wrapper for PyTorch as
+Keras is for TensorFlow - it only provides *extensions*.
+
+## Documentation
+
+Examples of the usage of BxTorch can be found in the [docs folder](docs).
+Method documentation is currently only available as [docstrings](bxtorch).
+
+## License
+
+BxTorch is licensed under the [MIT License](LICENSE).
+
+
+
+
+%prep
+%autosetup -n BxTorch-0.7.3
+
+%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-BxTorch -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed Apr 12 2023 Python_Bot <Python_Bot@openeuler.org> - 0.7.3-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..a3d8813
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+eef95c8dcab9a7c3c778f273cb92fdb0  BxTorch-0.7.3.tar.gz