File python-opt-einsum.spec of Package python-opt-einsum

#
# spec file for package python-opt-einsum
#
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Name:           python-opt-einsum
Version:        3.3.0
Release:        0
Summary:        Optimizing numpys einsum function
License:        MIT
URL:            https://github.com/dgasmith/opt_einsum
Source:         https://files.pythonhosted.org/packages/source/o/opt_einsum/opt_einsum-%{version}.tar.gz
# PATCH-FIX-UPSTREAM opt_einsum-pr208-configparser.patch gh#dgasmith/opt_einsum#208
Patch0:         https://github.com/dgasmith/opt_einsum/pull/208.patch#/opt_einsum-pr208-configparser.patch
BuildRequires:  %{python_module numpy >= 1.7}
BuildRequires:  %{python_module pip}
BuildRequires:  %{python_module pytest}
BuildRequires:  %{python_module setuptools}
BuildRequires:  %{python_module wheel}
Requires:       python-numpy >= 1.7
BuildRequires:  fdupes
BuildRequires:  python-rpm-macros
BuildArch:      noarch
%python_subpackages

%description
Optimized einsum can significantly reduce the overall execution time of einsum-like expressions (e.g.,
`np.einsum`,`dask.array.einsum`,`pytorch.einsum`,`tensorflow.einsum`)
by optimizing the expression's contraction order and dispatching many
operations to canonical BLAS, cuBLAS, or other specialized routines. Optimized
einsum is agnostic to the backend and can handle NumPy, Dask, PyTorch,
Tensorflow, CuPy, Sparse, Theano, JAX, and Autograd arrays as well as potentially
any library which conforms to a standard API. See the
[**documentation**](http://optimized-einsum.readthedocs.io) for more
information.

%prep
%autosetup -p1 -n opt_einsum-%{version}
sed -i '1{/^#!/d}' opt_einsum/parser.py

%build
%pyproject_wheel

%install
%pyproject_install
%python_expand %fdupes %{buildroot}%{$python_sitelib}

%check
%pytest

%files %{python_files}
%doc README.md
%license LICENSE
%{python_sitelib}/opt_einsum
%{python_sitelib}/opt_einsum-%{version}.dist-info

%changelog