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#!/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},
)