Inference Endpoints
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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 setuptools import find_packages, setup
from typing import List
import torch
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__)), "detectron2", "__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, "detectron2", "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"] = []
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(
"detectron2._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__)), "detectron2", "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="detectron2",
version=get_version(),
author="FAIR",
url="https://github.com/facebookresearch/detectron2",
description="Detectron2 is FAIR's next-generation research "
"platform for object detection and segmentation.",
packages=find_packages(exclude=("configs", "tests*")) + list(PROJECTS.keys()),
package_dir=PROJECTS,
package_data={"detectron2.model_zoo": get_model_zoo_configs()},
python_requires=">=3.6",
install_requires=[
# These dependencies are not pure-python.
# In general, avoid adding more dependencies like them because they are not
# guaranteed to be installable by `pip install` on all platforms.
# To tell if a package is pure-python, go to https://pypi.org/project/{name}/#files
"Pillow>=7.1", # or use pillow-simd for better performance
"matplotlib", # TODO move it to optional after we add opencv visualization
"pycocotools>=2.0.2", # corresponds to https://github.com/ppwwyyxx/cocoapi
# Do not add opencv here. Just like pytorch, user should install
# opencv themselves, preferrably by OS's package manager, or by
# choosing the proper pypi package name at https://github.com/skvark/opencv-python
# The following are pure-python dependencies that should be easily installable
"termcolor>=1.1",
"yacs>=0.1.8",
"tabulate",
"cloudpickle",
"tqdm>4.29.0",
"tensorboard",
# Lock version of fvcore/iopath because they may have breaking changes
# NOTE: when updating fvcore/iopath version, make sure fvcore depends
# on compatible version of iopath.
"fvcore>=0.1.5,<0.1.6", # required like this to make it pip installable
"iopath>=0.1.7,<0.1.10",
"future", # used by caffe2
"pydot", # used to save caffe2 SVGs
"dataclasses; python_version<'3.7'",
"omegaconf>=2.1",
"hydra-core>=1.1",
"black==21.4b2",
# If a new dependency is required at import time (in addition to runtime), it
# probably needs to exist in docs/requirements.txt, or as a mock in docs/conf.py
],
extras_require={
# optional dependencies, required by some features
"all": [
"shapely",
"pygments>=2.2",
"psutil",
"panopticapi @ https://github.com/cocodataset/panopticapi/archive/master.zip",
],
# dev dependencies. Install them by `pip install 'detectron2[dev]'`
"dev": [
"flake8==3.8.1",
"isort==4.3.21",
"flake8-bugbear",
"flake8-comprehensions",
],
},
ext_modules=get_extensions(),
cmdclass={"build_ext": torch.utils.cpp_extension.BuildExtension},
)