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setup.py
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# Modified from https://github.com/vllm-project/vllm/blob/main/setup.py
import contextlib
import io
import os
import re
import subprocess
import warnings
from pathlib import Path
from typing import List, Set
import setuptools
import torch
import torch.utils.cpp_extension as torch_cpp_ext
from packaging.version import Version, parse
from torch.utils.cpp_extension import CUDA_HOME, BuildExtension, CUDAExtension
ROOT_DIR = os.path.abspath(os.path.dirname(__file__))
# Supported NVIDIA GPU architectures.
NVIDIA_SUPPORTED_ARCHS = {"7.0", "7.5", "8.0", "8.6", "8.9", "9.0"}
def _is_cuda() -> bool:
return os.getenv("REAL_CUDA", "0") == "1"
# Compiler flags.
CXX_FLAGS = ["-g", "-O3", "-std=c++17"]
NVCC_FLAGS = ["-O3", "-std=c++17"]
if _is_cuda() and CUDA_HOME is None:
raise RuntimeError(
"Cannot find CUDA_HOME. In GPU environment, CUDA must be available to build the package."
)
ABI = 1 if torch._C._GLIBCXX_USE_CXX11_ABI else 0
CXX_FLAGS += [f"-D_GLIBCXX_USE_CXX11_ABI={ABI}"]
NVCC_FLAGS += [f"-D_GLIBCXX_USE_CXX11_ABI={ABI}"]
def glob(pattern: str):
root = Path(__name__).parent
return [str(p) for p in root.glob(pattern)]
def get_pybind11_include_path() -> str:
pybind11_meta = subprocess.check_output(
"python3 -m pip show pybind11", shell=True
).decode("ascii")
for line in pybind11_meta.split("\n"):
line = line.strip()
if line.startswith("Location: "):
return os.path.join(line.split(": ")[1], "pybind11", "include")
def get_nvcc_cuda_version(cuda_dir: str) -> Version:
"""Get the CUDA version from nvcc.
Adapted from
https://github.com/NVIDIA/apex/blob/8b7a1ff183741dd8f9b87e7bafd04cfde99cea28/setup.py
"""
nvcc_output = subprocess.check_output(
[cuda_dir + "/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_torch_arch_list() -> Set[str]:
# TORCH_CUDA_ARCH_LIST can have one or more architectures,
# e.g."8.0" or "7.5,8.0,8.6+PTX".Here, the "8.6+PTX" option asks the
# compiler to additionally include PTX code that can be runtime - compiled
# and executed on the 8.6 or newer architectures.While the PTX code will
# not give the best performance on the newer architectures, it provides
# forward compatibility.
env_arch_list = os.environ.get("TORCH_CUDA_ARCH_LIST", None)
if env_arch_list is None:
return set()
# List are separated by; or space.
torch_arch_list = set(env_arch_list.replace(" ", ";").split(";"))
if not torch_arch_list:
return set()
# Filter out the invalid architectures and print a warning.
valid_archs = NVIDIA_SUPPORTED_ARCHS.union(
{s + "+PTX" for s in NVIDIA_SUPPORTED_ARCHS}
)
arch_list = torch_arch_list.intersection(valid_archs)
# If none of the specified architectures are valid, raise an error.
if not arch_list:
raise RuntimeError(
"None of the CUDA architectures in `TORCH_CUDA_ARCH_LIST` env "
f"variable ({env_arch_list}) is supported. "
f"Supported CUDA architectures are: {valid_archs}."
)
invalid_arch_list = torch_arch_list - valid_archs
if invalid_arch_list:
warnings.warn(
f"Unsupported CUDA architectures ({invalid_arch_list}) are "
"excluded from the `TORCH_CUDA_ARCH_LIST` env variable "
f"({env_arch_list}). Supported CUDA architectures are: "
f"{valid_archs}.",
stacklevel=2,
)
return arch_list
# First, check the TORCH_CUDA_ARCH_LIST environment variable.
compute_capabilities = get_torch_arch_list()
if _is_cuda() and not compute_capabilities:
# If TORCH_CUDA_ARCH_LIST is not defined or empty, target all available
# GPUs on the current machine.
device_count = torch.cuda.device_count()
for i in range(device_count):
major, minor = torch.cuda.get_device_capability(i)
if major < 7:
raise RuntimeError(
"GPUs with compute capability below 7.0 are not supported."
)
compute_capabilities.add(f"{major}.{minor}")
ext_modules = []
if _is_cuda():
nvcc_cuda_version = get_nvcc_cuda_version(CUDA_HOME)
if not compute_capabilities:
# If no GPU is specified nor available, add all supported architectures
# based on the NVCC CUDA version.
compute_capabilities = NVIDIA_SUPPORTED_ARCHS.copy()
if nvcc_cuda_version < Version("11.1"):
compute_capabilities.remove("8.6")
if nvcc_cuda_version < Version("11.8"):
compute_capabilities.remove("8.9")
compute_capabilities.remove("9.0")
# Validate the NVCC CUDA version.
if nvcc_cuda_version < Version("11.0"):
raise RuntimeError("CUDA 11.0 or higher is required to build the package.")
if nvcc_cuda_version < Version("11.1") and any(
cc.startswith("8.6") for cc in compute_capabilities
):
raise RuntimeError(
"CUDA 11.1 or higher is required for compute capability 8.6."
)
if nvcc_cuda_version < Version("11.8"):
if any(cc.startswith("8.9") for cc in compute_capabilities):
# CUDA 11.8 is required to generate the code targeting compute capability 8.9.
# However, GPUs with compute capability 8.9 can also run the code generated by
# the previous versions of CUDA 11 and targeting compute capability 8.0.
# Therefore, if CUDA 11.8 is not available, we target compute capability 8.0
# instead of 8.9.
warnings.warn(
"CUDA 11.8 or higher is required for compute capability 8.9. "
"Targeting compute capability 8.0 instead.",
stacklevel=2,
)
compute_capabilities = set(
cc for cc in compute_capabilities if not cc.startswith("8.9")
)
compute_capabilities.add("8.0+PTX")
if any(cc.startswith("9.0") for cc in compute_capabilities):
raise RuntimeError(
"CUDA 11.8 or higher is required for compute capability 9.0."
)
NVCC_FLAGS_PUNICA = NVCC_FLAGS.copy()
# Add target compute capabilities to NVCC flags.
for capability in compute_capabilities:
num = capability[0] + capability[2]
NVCC_FLAGS += ["-gencode", f"arch=compute_{num},code=sm_{num}"]
if capability.endswith("+PTX"):
NVCC_FLAGS += ["-gencode", f"arch=compute_{num},code=compute_{num}"]
if int(capability[0]) >= 8:
NVCC_FLAGS_PUNICA += [
"-gencode",
f"arch=compute_{num},code=sm_{num}",
]
if capability.endswith("+PTX"):
NVCC_FLAGS_PUNICA += [
"-gencode",
f"arch=compute_{num},code=compute_{num}",
]
# Use NVCC threads to parallelize the build.
if nvcc_cuda_version >= Version("11.2"):
nvcc_threads = int(os.getenv("NVCC_THREADS", 8))
num_threads = min(os.cpu_count(), nvcc_threads)
NVCC_FLAGS += ["--threads", str(num_threads)]
if nvcc_cuda_version >= Version("11.8"):
NVCC_FLAGS += ["-DENABLE_FP8_E5M2"]
# changes for punica kernels
NVCC_FLAGS += torch_cpp_ext.COMMON_NVCC_FLAGS
REMOVE_NVCC_FLAGS = [
"-D__CUDA_NO_HALF_OPERATORS__",
"-D__CUDA_NO_HALF_CONVERSIONS__",
"-D__CUDA_NO_BFLOAT16_CONVERSIONS__",
"-D__CUDA_NO_HALF2_OPERATORS__",
]
for flag in REMOVE_NVCC_FLAGS:
with contextlib.suppress(ValueError):
torch_cpp_ext.COMMON_NVCC_FLAGS.remove(flag)
os.makedirs(os.path.join(ROOT_DIR, "realhf", "_C"), exist_ok=True)
if _is_cuda():
cr_extension = CUDAExtension(
name="realhf._C.custom_all_reduce",
sources=[
"csrc/custom_all_reduce/custom_all_reduce.cu",
"csrc/custom_all_reduce/pybind.cpp",
],
extra_compile_args={
"cxx": CXX_FLAGS,
"nvcc": NVCC_FLAGS,
},
libraries=["cuda"],
)
ext_modules.append(cr_extension)
gae_extension = CUDAExtension(
name="realhf._C.cugae",
sources=[
"csrc/cugae/gae.cu",
],
extra_compile_args={
"cxx": CXX_FLAGS,
"nvcc": NVCC_FLAGS
+ [
"--expt-relaxed-constexpr",
"--expt-extended-lambda",
"--use_fast_math",
],
},
libraries=["cuda"],
)
ext_modules.append(gae_extension)
interval_op_cuda = CUDAExtension(
name="realhf._C.interval_op_cuda",
sources=[
"csrc/interval_op/interval_op.cu",
],
extra_compile_args={
"cxx": CXX_FLAGS,
"nvcc": NVCC_FLAGS,
},
libraries=["cuda"],
)
ext_modules.append(interval_op_cuda)
search_extension = setuptools.Extension(
name="realhf._C.mdm_search",
sources=[
"csrc/search/search.cpp",
"csrc/search/rpc.cpp",
"csrc/search/device_mesh.cpp",
"csrc/search/simulate.cpp",
],
language="c++",
extra_compile_args=[
"-O3",
"-Wall",
"-shared",
"-std=c++11",
"-fPIC",
"-std=c++17",
],
include_dirs=[
os.path.join(os.path.abspath(os.path.dirname(__file__)), "csrc", "search"),
get_pybind11_include_path(),
],
)
ext_modules.append(search_extension)
interval_extension = setuptools.Extension(
name="realhf._C.interval_op",
sources=[
"csrc/interval_op/interval_op.cpp",
],
language="c++",
extra_compile_args=[
"-O3",
"-Wall",
"-std=c++17",
],
include_dirs=[
get_pybind11_include_path(),
],
)
ext_modules.append(interval_extension)
if os.getenv("REAL_NO_EXT", "0") == "1":
ext_modules = []
setuptools.setup(
name="realhf",
ext_modules=ext_modules,
cmdclass={"build_ext": BuildExtension},
packages=setuptools.find_packages(),
include_package_data=True,
package_data={
"": [
"csrc/**/*.cu",
"csrc/**/*.cuh",
"csrc/**/*.hpp",
"csrc/**/*.cpp",
],
},
)