import os
import glob

import torch

from torch.utils.cpp_extension import CUDA_HOME
from torch.utils.cpp_extension import CppExtension
from torch.utils.cpp_extension import CUDAExtension

from setuptools import find_packages
from setuptools import setup

requirements = ["torch", "torchvision"]


def get_extensions():
    this_dir = os.path.dirname(os.path.abspath(__file__))
    extensions_dir = os.path.join(this_dir, "src")

    main_file = glob.glob(os.path.join(extensions_dir, "*.cpp"))
    # source_cpu = glob.glob(os.path.join(extensions_dir, "cpu", "*.cpp"))
    source_cuda = glob.glob(os.path.join(extensions_dir, "*.cu"))

    sources = main_file
    extension = CppExtension
    extra_compile_args = {"cxx": []}
    define_macros = []

    if torch.cuda.is_available() and CUDA_HOME is not None:
        extension = CUDAExtension
        sources += source_cuda
        define_macros += [("WITH_CUDA", None)]
        extra_compile_args["nvcc"] = [
            "-DCUDA_HAS_FP16=1",
            "-D__CUDA_NO_HALF_OPERATORS__",
            "-D__CUDA_NO_HALF_CONVERSIONS__",
            "-D__CUDA_NO_HALF2_OPERATORS__",
        ]
    else:
        raise NotImplementedError('Cuda is not availabel')

    sources = [os.path.join(extensions_dir, s) for s in sources]
    include_dirs = [extensions_dir]
    ext_modules = [
        extension(
            "GeometricKernelAttention",
            sources,
            include_dirs=include_dirs,
            define_macros=define_macros,
            extra_compile_args=extra_compile_args,
        )
    ]
    return ext_modules


setup(
    name="GeometricKernelAttention",
    version="1.0",
    description="PyTorch Wrapper for CUDA Functions of Multi-Scale Geometric Kernel Attention",
    packages=find_packages(exclude=("configs", "tests",)),
    ext_modules=get_extensions(),
    cmdclass={"build_ext": torch.utils.cpp_extension.BuildExtension},
)
