%global pypi_name tensordict
%global pypi_version 0.3.1

# torch toolchain
%global toolchain gcc

Name:           python-%{pypi_name}
Version:        %{pypi_version}
Release:        %autorelease
Summary:        TensorDict is a PyTorch dedicated tensor container

License:        MIT
URL:            https://github.com/pytorch/%{pypi_name}
Source0:        %{url}/archive/v%{version}.tar.gz#/%{pypi_name}-v%{version}.tar.gz

# Limit to these because that is what torch is on
ExclusiveArch:  x86_64 aarch64

BuildRequires:  clang
BuildRequires:  ninja-build
BuildRequires:  python3-devel
BuildRequires:  python3-torch

BuildRequires:  python3dist(setuptools)
BuildRequires:  python3dist(pybind11)

Requires:       python3dist(torch)

%description
TensorDict is a dictionary-like class that inherits properties from tensors,
such as indexing, shape operations, casting to device or point-to-point
communication in distributed settings.

The main purpose of TensorDict is to make code-bases more readable and
modular by abstracting away tailored operations.

%package -n     python3-%{pypi_name}
Summary:        TensorDict is a pytorch dedicated tensor container

%description -n python3-%{pypi_name}
TensorDict is a dictionary-like class that inherits properties from tensors,
such as indexing, shape operations, casting to device or point-to-point
communication in distributed settings.

The main purpose of TensorDict is to make code-bases more readable and
modular by abstracting away tailored operations.

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

%generate_buildrequires
%pyproject_buildrequires

%build
# Building uses python3_sitearch/torch/utils/cpp_extension.py
# cpp_extension.py does a general linking with all the pytorch libs which
# leads warnings being reported by rpmlint.
%pyproject_wheel

%check
%pyproject_check_import

%install
%pyproject_install
%pyproject_save_files %{pypi_name}

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

%changelog
%autochangelog