%global pypi_name torchdiffeq

Name:           python-%{pypi_name}
Version:        0.2.5
Release:        %autorelease
Summary:        Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation

License:        MIT
URL:            https://github.com/rtqichen/%{pypi_name}
Source:         %{pypi_source torchdiffeq}

# Only x86_64 tested
ExclusiveArch:  x86_64
BuildArch:      noarch

BuildRequires:  python3-devel

%description 
This library provides ordinary differential equation (ODE) solvers
implemented in PyTorch. Backpropagation through ODE solutions is
supported using the adjoint method for constant memory cost. For
usage of ODE solvers in deep learning applications.

As the solvers are implemented in PyTorch, algorithms in this
repository are fully supported to run on the GPU.

%package -n     python3-%{pypi_name}
Summary:        %{summary}

%description -n python3-%{pypi_name}
This library provides ordinary differential equation (ODE) solvers
implemented in PyTorch. Backpropagation through ODE solutions is
supported using the adjoint method for constant memory cost. For
usage of ODE solvers in deep learning applications.

As the solvers are implemented in PyTorch, algorithms in this
repository are fully supported to run on the GPU.

%prep
%autosetup -p1 -n %{pypi_name}-%{version}

%generate_buildrequires
%pyproject_buildrequires

%build
%pyproject_wheel

%install
%pyproject_install
%pyproject_save_files -l %{pypi_name}

%check
%pyproject_check_import

%files -n python3-%{pypi_name} -f %{pyproject_files}
%doc README.md

%changelog
%autochangelog