# Copyright (c) 2023, Tri Dao.
import logging
import sys
import os
import re
import ast
from collections import namedtuple
from pathlib import Path
from typing import Dict
from shutil import which
from packaging.version import Version, parse

import subprocess

import torch
from torch.utils.cpp_extension import (
    BuildExtension,
    CUDA_HOME,
)

from setuptools import Extension, find_packages, setup
from setuptools.command.build_ext import build_ext

logger = logging.getLogger(__name__)

# Enivronment variables
Envs = namedtuple("Envs", ["VERBOSE", "MAX_JOBS", "NVCC_THREADS", "VLLM_TARGET_DEVICE", "CMAKE_BUILD_TYPE"])
envs = Envs(
    VERBOSE=bool(int(os.getenv("VERBOSE", "0"))),
    MAX_JOBS=os.getenv("MAX_JOBS"),
    NVCC_THREADS=os.getenv("NVCC_THREADS"),
    VLLM_TARGET_DEVICE=os.getenv("VLLM_TARGET_DEVICE", "cuda"),
    CMAKE_BUILD_TYPE=os.getenv("CMAKE_BUILD_TYPE"),
)

with open("README.md", "r", encoding="utf-8") as fh:
    long_description = fh.read()

# ninja build does not work unless include_dirs are abs path
this_dir = os.path.dirname(os.path.abspath(__file__))

PACKAGE_NAME = "vllm_flash_attn"

cmdclass = {}
ext_modules = []

# TODO(luka): This should be replaced with a fetch_content call in CMakeLists.txt
subprocess.run(["git", "submodule", "update", "--init", "csrc/cutlass"])


def is_sccache_available() -> bool:
    return which("sccache") is not None


def is_ccache_available() -> bool:
    return which("ccache") is not None


def is_ninja_available() -> bool:
    return which("ninja") is not None


def remove_prefix(text, prefix):
    if text.startswith(prefix):
        return text[len(prefix):]
    return text


VLLM_TARGET_DEVICE = envs.VLLM_TARGET_DEVICE


def _is_cuda() -> bool:
    has_cuda = torch.version.cuda is not None
    return VLLM_TARGET_DEVICE == "cuda" and has_cuda


def _is_hip() -> bool:
    return (VLLM_TARGET_DEVICE == "cuda"
            or VLLM_TARGET_DEVICE == "rocm") and torch.version.hip is not None


class CMakeExtension(Extension):

    def __init__(self, name: str, cmake_lists_dir: str = '.', **kwa) -> None:
        super().__init__(name, sources=[], py_limited_api=True, **kwa)
        self.cmake_lists_dir = os.path.abspath(cmake_lists_dir)


class cmake_build_ext(build_ext):
    # A dict of extension directories that have been configured.
    did_config: Dict[str, bool] = {}

    #
    # Determine number of compilation jobs and optionally nvcc compile threads.
    #
    def compute_num_jobs(self):
        # `num_jobs` is either the value of the MAX_JOBS environment variable
        # (if defined) or the number of CPUs available.
        num_jobs = envs.MAX_JOBS
        if num_jobs is not None:
            num_jobs = int(num_jobs)
            logger.info("Using MAX_JOBS=%d as the number of jobs.", num_jobs)
        else:
            try:
                # os.sched_getaffinity() isn't universally available, so fall
                #  back to os.cpu_count() if we get an error here.
                num_jobs = len(os.sched_getaffinity(0))
            except AttributeError:
                num_jobs = os.cpu_count()

        nvcc_threads = None
        if _is_cuda() and get_nvcc_cuda_version() >= Version("11.2"):
            # `nvcc_threads` is either the value of the NVCC_THREADS
            # environment variable (if defined) or 1.
            # when it is set, we reduce `num_jobs` to avoid
            # overloading the system.
            nvcc_threads = envs.NVCC_THREADS
            if nvcc_threads is not None:
                nvcc_threads = int(nvcc_threads)
                logger.info(
                    "Using NVCC_THREADS=%d as the number of nvcc threads.",
                    nvcc_threads)
            else:
                nvcc_threads = 1
            num_jobs = max(1, num_jobs // nvcc_threads)

        return num_jobs, nvcc_threads

    #
    # Perform cmake configuration for a single extension.
    #
    def configure(self, ext: CMakeExtension) -> None:
        # If we've already configured using the CMakeLists.txt for
        # this extension, exit early.
        if ext.cmake_lists_dir in cmake_build_ext.did_config:
            return

        cmake_build_ext.did_config[ext.cmake_lists_dir] = True

        # Select the build type.
        # Note: optimization level + debug info are set by the build type
        default_cfg = "Debug" if self.debug else "RelWithDebInfo"
        cfg = envs.CMAKE_BUILD_TYPE or default_cfg

        cmake_args = [
            '-DCMAKE_BUILD_TYPE={}'.format(cfg),
            '-DVLLM_TARGET_DEVICE={}'.format(VLLM_TARGET_DEVICE),
        ]

        verbose = envs.VERBOSE
        if verbose:
            cmake_args += ['-DCMAKE_VERBOSE_MAKEFILE=ON']

        if is_sccache_available():
            cmake_args += [
                '-DCMAKE_CXX_COMPILER_LAUNCHER=sccache',
                '-DCMAKE_CUDA_COMPILER_LAUNCHER=sccache',
                '-DCMAKE_C_COMPILER_LAUNCHER=sccache',
            ]
        elif is_ccache_available():
            cmake_args += [
                '-DCMAKE_CXX_COMPILER_LAUNCHER=ccache',
                '-DCMAKE_CUDA_COMPILER_LAUNCHER=ccache',
            ]

        # Pass the python executable to cmake so it can find an exact
        # match.
        cmake_args += ['-DPython_EXECUTABLE={}'.format(sys.executable)]

        # Pass the python path to cmake so it can reuse the build dependencies
        # on subsequent calls to python.
        cmake_args += ['-DVLLM_PYTHON_PATH={}'.format(":".join(sys.path))]

        #
        # Setup parallelism and build tool
        #
        num_jobs, nvcc_threads = self.compute_num_jobs()

        if nvcc_threads:
            cmake_args += ['-DNVCC_THREADS={}'.format(nvcc_threads)]

        if is_ninja_available():
            build_tool = ['-G', 'Ninja']
            cmake_args += [
                '-DCMAKE_JOB_POOL_COMPILE:STRING=compile',
                '-DCMAKE_JOB_POOLS:STRING=compile={}'.format(num_jobs),
            ]
        else:
            # Default build tool to whatever cmake picks.
            build_tool = []
        subprocess.check_call(
            ['cmake', ext.cmake_lists_dir, *build_tool, *cmake_args],
            cwd=self.build_temp)

    def build_extensions(self) -> None:
        # Ensure that CMake is present and working
        try:
            subprocess.check_output(['cmake', '--version'])
        except OSError as e:
            raise RuntimeError('Cannot find CMake executable') from e

        # Create build directory if it does not exist.
        if not os.path.exists(self.build_temp):
            os.makedirs(self.build_temp)

        targets = []
        target_name = lambda s: remove_prefix(s, "vllm_flash_attn.")
        # Build all the extensions
        for ext in self.extensions:
            self.configure(ext)
            targets.append(target_name(ext.name))

        num_jobs, _ = self.compute_num_jobs()

        build_args = [
            "--build",
            ".",
            f"-j={num_jobs}",
            *[f"--target={name}" for name in targets],
        ]

        subprocess.check_call(["cmake", *build_args], cwd=self.build_temp)

        # Install the libraries
        for ext in self.extensions:
            # Install the extension into the proper location
            outdir = Path(self.get_ext_fullpath(ext.name)).parent.absolute()

            # Skip if the install directory is the same as the build directory
            if outdir == self.build_temp:
                continue

            # CMake appends the extension prefix to the install path,
            # and outdir already contains that prefix, so we need to remove it.
            prefix = outdir
            for i in range(ext.name.count('.')):
                prefix = prefix.parent

            # prefix here should actually be the same for all components
            install_args = [
                "cmake", "--install", ".", "--prefix", prefix, "--component",
                target_name(ext.name)
            ]
            subprocess.check_call(install_args, cwd=self.build_temp)


def get_package_version():
    with open(Path(this_dir) / PACKAGE_NAME / "__init__.py", "r") as f:
        version_match = re.search(r"^__version__\s*=\s*(.*)$", f.read(), re.MULTILINE)
    public_version = ast.literal_eval(version_match.group(1))
    local_version = os.environ.get("FLASH_ATTN_LOCAL_VERSION")
    if local_version:
        return f"{public_version}+{local_version}"
    else:
        return str(public_version)


PYTORCH_VERSION = "2.4.0"
MAIN_CUDA_VERSION = "12.1"


def get_nvcc_cuda_version() -> Version:
    """Get the CUDA version from nvcc.

    Adapted from https://github.com/NVIDIA/apex/blob/8b7a1ff183741dd8f9b87e7bafd04cfde99cea28/setup.py
    """
    assert CUDA_HOME is not None, "CUDA_HOME is not set"
    nvcc_output = subprocess.check_output([CUDA_HOME + "/bin/nvcc", "-V"],
                                          universal_newlines=True)
    output = nvcc_output.split()
    release_idx = output.index("release") + 1
    nvcc_cuda_version = parse(output[release_idx].split(",")[0])
    return nvcc_cuda_version


def get_version() -> str:
    version = get_package_version()
    cuda_version = str(get_nvcc_cuda_version())
    if cuda_version != MAIN_CUDA_VERSION:
        cuda_version_str = cuda_version.replace(".", "")[:3]
        version += f"+cu{cuda_version_str}"
    return version


ext_modules.append(CMakeExtension(name="vllm_flash_attn._vllm_fa2_C"))
ext_modules.append(CMakeExtension(name="vllm_flash_attn._vllm_fa3_C"))

setup(
    name="vllm-flash-attn",
    version=get_version(),
    packages=find_packages(exclude=("build",
                                    "csrc",
                                    "include",
                                    "tests",
                                    "dist",
                                    "docs",
                                    "benchmarks",
                                    f"{PACKAGE_NAME}.egg-info",)),
    author="vLLM Team",
    description="Forward-only flash-attn",
    long_description=f"Forward-only flash-attn package built for PyTorch {PYTORCH_VERSION} and CUDA {MAIN_CUDA_VERSION}",
    url="https://github.com/vllm-project/flash-attention.git",
    classifiers=[
        "Programming Language :: Python :: 3",
        "License :: OSI Approved :: BSD License",
        "Operating System :: Unix",
    ],
    ext_modules=ext_modules,
    cmdclass={"build_ext": cmake_build_ext} if len(ext_modules) > 0 else {},
    python_requires=">=3.8",
    install_requires=[f"torch == {PYTORCH_VERSION}"],
    setup_requires=["psutil"],
)