automatic import of python-elasticdeform

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diff --git a/.gitignore b/.gitignore
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+/elasticdeform-0.5.0.tar.gz
diff --git a/python-elasticdeform.spec b/python-elasticdeform.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-elasticdeform
+Version:	0.5.0
+Release:	1
+Summary:	Elastic deformations for N-D images.
+License:	BSD
+URL:		https://github.com/gvtulder/elasticdeform
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/b6/ee/562d0bc43151411ffcfbac1cb1419748df9fbffb2a2685c9735f3e7e6352/elasticdeform-0.5.0.tar.gz
+
+Requires:	python3-numpy
+Requires:	python3-scipy
+
+%description
+[![Documentation Status](https://readthedocs.org/projects/elasticdeform/badge/?version=latest)](https://elasticdeform.readthedocs.io/en/latest/?badge=latest)
+[![Test](https://github.com/gvtulder/elasticdeform/actions/workflows/test.yml/badge.svg)](https://github.com/gvtulder/elasticdeform/actions/workflows/test.yml)
+[![Build](https://github.com/gvtulder/elasticdeform/actions/workflows/wheels.yml/badge.svg)](https://github.com/gvtulder/elasticdeform/actions/workflows/wheels.yml)
+[![DOI](https://zenodo.org/badge/145003699.svg)](https://zenodo.org/badge/latestdoi/145003699)
+This library implements elastic grid-based deformations for N-dimensional images.
+The elastic deformation approach is described in
+*   Ronneberger, Fischer, and Brox, "U-Net: Convolutional Networks for Biomedical
+    Image Segmentation" (<https://arxiv.org/abs/1505.04597>)
+*   Çiçek et al., "3D U-Net: Learning Dense Volumetric
+    Segmentation from Sparse Annotation" (<https://arxiv.org/abs/1606.06650>)
+The procedure generates a coarse displacement grid with a random displacement
+for each grid point. This grid is then interpolated to compute a displacement for
+each pixel in the input image. The input image is then deformed using the
+displacement vectors and a spline interpolation.
+In addition to the normal, forward deformation, this package also provides a
+function that can backpropagate the gradient through the deformation. This makes
+it possible to use the deformation as a layer in a convolutional neural network.
+For convenience, TensorFlow and PyTorch wrappers are provided in `elasticdeform.tf`
+and `elasticdeform.torch`.
+
+%package -n python3-elasticdeform
+Summary:	Elastic deformations for N-D images.
+Provides:	python-elasticdeform
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+BuildRequires:	python3-cffi
+BuildRequires:	gcc
+BuildRequires:	gdb
+%description -n python3-elasticdeform
+[![Documentation Status](https://readthedocs.org/projects/elasticdeform/badge/?version=latest)](https://elasticdeform.readthedocs.io/en/latest/?badge=latest)
+[![Test](https://github.com/gvtulder/elasticdeform/actions/workflows/test.yml/badge.svg)](https://github.com/gvtulder/elasticdeform/actions/workflows/test.yml)
+[![Build](https://github.com/gvtulder/elasticdeform/actions/workflows/wheels.yml/badge.svg)](https://github.com/gvtulder/elasticdeform/actions/workflows/wheels.yml)
+[![DOI](https://zenodo.org/badge/145003699.svg)](https://zenodo.org/badge/latestdoi/145003699)
+This library implements elastic grid-based deformations for N-dimensional images.
+The elastic deformation approach is described in
+*   Ronneberger, Fischer, and Brox, "U-Net: Convolutional Networks for Biomedical
+    Image Segmentation" (<https://arxiv.org/abs/1505.04597>)
+*   Çiçek et al., "3D U-Net: Learning Dense Volumetric
+    Segmentation from Sparse Annotation" (<https://arxiv.org/abs/1606.06650>)
+The procedure generates a coarse displacement grid with a random displacement
+for each grid point. This grid is then interpolated to compute a displacement for
+each pixel in the input image. The input image is then deformed using the
+displacement vectors and a spline interpolation.
+In addition to the normal, forward deformation, this package also provides a
+function that can backpropagate the gradient through the deformation. This makes
+it possible to use the deformation as a layer in a convolutional neural network.
+For convenience, TensorFlow and PyTorch wrappers are provided in `elasticdeform.tf`
+and `elasticdeform.torch`.
+
+%package help
+Summary:	Development documents and examples for elasticdeform
+Provides:	python3-elasticdeform-doc
+%description help
+[![Documentation Status](https://readthedocs.org/projects/elasticdeform/badge/?version=latest)](https://elasticdeform.readthedocs.io/en/latest/?badge=latest)
+[![Test](https://github.com/gvtulder/elasticdeform/actions/workflows/test.yml/badge.svg)](https://github.com/gvtulder/elasticdeform/actions/workflows/test.yml)
+[![Build](https://github.com/gvtulder/elasticdeform/actions/workflows/wheels.yml/badge.svg)](https://github.com/gvtulder/elasticdeform/actions/workflows/wheels.yml)
+[![DOI](https://zenodo.org/badge/145003699.svg)](https://zenodo.org/badge/latestdoi/145003699)
+This library implements elastic grid-based deformations for N-dimensional images.
+The elastic deformation approach is described in
+*   Ronneberger, Fischer, and Brox, "U-Net: Convolutional Networks for Biomedical
+    Image Segmentation" (<https://arxiv.org/abs/1505.04597>)
+*   Çiçek et al., "3D U-Net: Learning Dense Volumetric
+    Segmentation from Sparse Annotation" (<https://arxiv.org/abs/1606.06650>)
+The procedure generates a coarse displacement grid with a random displacement
+for each grid point. This grid is then interpolated to compute a displacement for
+each pixel in the input image. The input image is then deformed using the
+displacement vectors and a spline interpolation.
+In addition to the normal, forward deformation, this package also provides a
+function that can backpropagate the gradient through the deformation. This makes
+it possible to use the deformation as a layer in a convolutional neural network.
+For convenience, TensorFlow and PyTorch wrappers are provided in `elasticdeform.tf`
+and `elasticdeform.torch`.
+
+%prep
+%autosetup -n elasticdeform-0.5.0
+
+%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-elasticdeform -f filelist.lst
+%dir %{python3_sitearch}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.5.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..091862a
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+e3930acb3227fb1b13ebbf80d28901a4  elasticdeform-0.5.0.tar.gz