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#!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
# Modified by Feng Wang
import glob
import os
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, 3], "Requires PyTorch >= 1.3"
def get_extensions():
this_dir = os.path.dirname(os.path.abspath(__file__))
extensions_dir = os.path.join(this_dir, "dl_lib", "layers")
main_source = os.path.join(extensions_dir, "vision.cpp")
sources = glob.glob(os.path.join(extensions_dir, "**", "*.cpp"))
source_cuda = glob.glob(os.path.join(extensions_dir, "**", "*.cu")) + glob.glob(
os.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 os.getenv("FORCE_CUDA", "0") == "1":
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__",
]
# It's better if pytorch can do this by default ..
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(
"dl_lib._C",
sources,
include_dirs=include_dirs,
define_macros=define_macros,
extra_compile_args=extra_compile_args,
)
]
return ext_modules
cur_dir = os.getcwd()
with open("tools/dl_train", "w") as dl_lib_train:
head = f"#!/bin/bash\n\nexport OMP_NUM_THREADS=1\n"
dl_lib_train.write(
head + f"python3 {os.path.join(cur_dir, 'tools', 'train_net.py')} $@")
with open("tools/dl_test", "w") as dl_lib_test:
dl_lib_test.write(
head + f"python3 {os.path.join(cur_dir, 'tools', 'test_net.py')} $@")
setup(
name="dl_lib",
version="0.1",
author="Feng Wang",
url="https://github.com/Fatescript/centernet",
description="Deep Learning lib(dl_lib) is Feng Wang's"
"platform for object detection based on Detectron2.",
packages=find_packages(exclude=("configs", "tests")),
python_requires=">=3.6",
install_requires=[
"termcolor>=1.1",
"Pillow>=6.0",
"tabulate",
"cloudpickle",
"matplotlib",
"tqdm>4.29.0",
"Shapely",
"tensorboard",
"portalocker",
"pycocotools",
"easydict",
"imagesize",
],
extras_require={"all": ["shapely", "psutil"]},
ext_modules=get_extensions(),
cmdclass={"build_ext": torch.utils.cpp_extension.BuildExtension},
scripts=["tools/dl_train", "tools/dl_test"],
)