#!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.

import glob
import os
import shutil
from os import path
from typing import List

import torch
from setuptools import find_packages, setup
from torch.utils.cpp_extension import CUDA_HOME, CppExtension, CUDAExtension

torch_ver = [int(x) for x in torch.__version__.split(".")[:2]]
assert torch_ver >= [1, 8], "Requires PyTorch >= 1.8"


def get_version():
    init_py_path = path.join(path.abspath(path.dirname(__file__)), "ape", "__init__.py")
    init_py = open(init_py_path, "r").readlines()
    version_line = [l.strip() for l in init_py if l.startswith("__version__")][0]
    version = version_line.split("=")[-1].strip().strip("'\"")

    # The following is used to build release packages.
    # Users should never use it.
    suffix = os.getenv("D2_VERSION_SUFFIX", "")
    version = version + suffix
    if os.getenv("BUILD_NIGHTLY", "0") == "1":
        from datetime import datetime

        date_str = datetime.today().strftime("%y%m%d")
        version = version + ".dev" + date_str

        new_init_py = [l for l in init_py if not l.startswith("__version__")]
        new_init_py.append('__version__ = "{}"\n'.format(version))
        with open(init_py_path, "w") as f:
            f.write("".join(new_init_py))
    return version


def get_extensions():
    this_dir = path.dirname(path.abspath(__file__))
    extensions_dir = path.join(this_dir, "ape", "layers", "csrc")

    main_source = path.join(extensions_dir, "vision.cpp")
    sources = glob.glob(path.join(extensions_dir, "**", "*.cpp"))

    from torch.utils.cpp_extension import ROCM_HOME

    is_rocm_pytorch = (
        True if ((torch.version.hip is not None) and (ROCM_HOME is not None)) else False
    )
    if is_rocm_pytorch:
        assert torch_ver >= [1, 8], "ROCM support requires PyTorch >= 1.8!"

    # common code between cuda and rocm platforms, for hipify version [1,0,0] and later.
    source_cuda = glob.glob(path.join(extensions_dir, "**", "*.cu")) + glob.glob(
        path.join(extensions_dir, "*.cu")
    )
    sources = [main_source] + sources

    extension = CppExtension

    extra_compile_args = {"cxx": []}
    define_macros = []

    if (torch.cuda.is_available() and ((CUDA_HOME is not None) or is_rocm_pytorch)) or os.getenv(
        "FORCE_CUDA", "0"
    ) == "1":
        extension = CUDAExtension
        sources += source_cuda

        if not is_rocm_pytorch:
            define_macros += [("WITH_CUDA", None)]
            extra_compile_args["nvcc"] = [
                "-O3",
                "-DCUDA_HAS_FP16=1",
                "-D__CUDA_NO_HALF_OPERATORS__",
                "-D__CUDA_NO_HALF_CONVERSIONS__",
                "-D__CUDA_NO_HALF2_OPERATORS__",
            ]
        else:
            define_macros += [("WITH_HIP", None)]
            extra_compile_args["nvcc"] = []

        nvcc_flags_env = os.getenv("NVCC_FLAGS", "")
        if nvcc_flags_env != "":
            extra_compile_args["nvcc"].extend(nvcc_flags_env.split(" "))

        if torch_ver < [1, 7]:
            # supported by https://github.com/pytorch/pytorch/pull/43931
            CC = os.environ.get("CC", None)
            if CC is not None:
                extra_compile_args["nvcc"].append("-ccbin={}".format(CC))

    include_dirs = [extensions_dir]

    ext_modules = [
        extension(
            "ape._C",
            sources,
            include_dirs=include_dirs,
            define_macros=define_macros,
            extra_compile_args=extra_compile_args,
        )
    ]

    return ext_modules


def get_model_zoo_configs() -> List[str]:
    """
    Return a list of configs to include in package for model zoo. Copy over these configs inside
    detectron2/model_zoo.
    """

    # Use absolute paths while symlinking.
    source_configs_dir = path.join(path.dirname(path.realpath(__file__)), "configs")
    destination = path.join(path.dirname(path.realpath(__file__)), "ape", "model_zoo", "configs")
    # Symlink the config directory inside package to have a cleaner pip install.

    # Remove stale symlink/directory from a previous build.
    if path.exists(source_configs_dir):
        if path.islink(destination):
            os.unlink(destination)
        elif path.isdir(destination):
            shutil.rmtree(destination)

    if not path.exists(destination):
        try:
            os.symlink(source_configs_dir, destination)
        except OSError:
            # Fall back to copying if symlink fails: ex. on Windows.
            shutil.copytree(source_configs_dir, destination)

    config_paths = glob.glob("configs/**/*.yaml", recursive=True) + glob.glob(
        "configs/**/*.py", recursive=True
    )
    return config_paths


# For projects that are relative small and provide features that are very close
# to detectron2's core functionalities, we install them under detectron2.projects
PROJECTS = {
}

setup(
    name="ape",
    version=get_version(),
    author="Yunhang Shen",
    url="https://github.com/shenyunhang",
    description="APE is next-generation research "
    "framework for object detection and segmentation.",
    packages=find_packages(exclude=("configs", "tests*")) + list(PROJECTS.keys()),
    package_dir=PROJECTS,
    package_data={"ape.model_zoo": get_model_zoo_configs(), "ape.modeling.text.eva02_clip": ["*.gz", "**/*.json"], "ape.modeling.text.eva01_clip": ["*.gz", "**/*.json"]},
    python_requires=">=3.7",
    install_requires=[
    ],
    ext_modules=get_extensions(),
    cmdclass={"build_ext": torch.utils.cpp_extension.BuildExtension},
)