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setup.py
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setup.py
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import distutils.command.clean
import distutils.spawn
import glob
import os
import shutil
import subprocess
import sys
import torch
from pkg_resources import parse_version, get_distribution, DistributionNotFound
from setuptools import setup, find_packages
from torch.utils.cpp_extension import BuildExtension, CppExtension, CUDAExtension, CUDA_HOME
def read(*names, **kwargs):
with open(os.path.join(os.path.dirname(__file__), *names), encoding=kwargs.get("encoding", "utf8")) as fp:
return fp.read()
def get_dist(pkgname):
try:
return get_distribution(pkgname)
except DistributionNotFound:
return None
cwd = os.path.dirname(os.path.abspath(__file__))
version_txt = os.path.join(cwd, "version.txt")
with open(version_txt) as f:
version = f.readline().strip()
sha = "Unknown"
package_name = "torchvision"
try:
sha = subprocess.check_output(["git", "rev-parse", "HEAD"], cwd=cwd).decode("ascii").strip()
except Exception:
pass
if os.getenv("BUILD_VERSION"):
version = os.getenv("BUILD_VERSION")
elif sha != "Unknown":
version += "+" + sha[:7]
def write_version_file():
version_path = os.path.join(cwd, "torchvision", "version.py")
with open(version_path, "w") as f:
f.write(f"__version__ = '{version}'\n")
f.write(f"git_version = {repr(sha)}\n")
f.write("from torchvision.extension import _check_cuda_version\n")
f.write("if _check_cuda_version() > 0:\n")
f.write(" cuda = _check_cuda_version()\n")
pytorch_dep = "torch"
if os.getenv("PYTORCH_VERSION"):
pytorch_dep += "==" + os.getenv("PYTORCH_VERSION")
requirements = [
"typing_extensions",
"numpy",
"requests",
pytorch_dep,
]
# Excluding 8.3.* because of https://github.com/pytorch/vision/issues/4934
pillow_ver = " >= 5.3.0, !=8.3.*"
pillow_req = "pillow-simd" if get_dist("pillow-simd") is not None else "pillow"
requirements.append(pillow_req + pillow_ver)
def find_library(name, vision_include):
this_dir = os.path.dirname(os.path.abspath(__file__))
build_prefix = os.environ.get("BUILD_PREFIX", None)
is_conda_build = build_prefix is not None
library_found = False
conda_installed = False
lib_folder = None
include_folder = None
library_header = f"{name}.h"
# Lookup in TORCHVISION_INCLUDE or in the package file
package_path = [os.path.join(this_dir, "torchvision")]
for folder in vision_include + package_path:
candidate_path = os.path.join(folder, library_header)
library_found = os.path.exists(candidate_path)
if library_found:
break
if not library_found:
print(f"Running build on conda-build: {is_conda_build}")
if is_conda_build:
# Add conda headers/libraries
if os.name == "nt":
build_prefix = os.path.join(build_prefix, "Library")
include_folder = os.path.join(build_prefix, "include")
lib_folder = os.path.join(build_prefix, "lib")
library_header_path = os.path.join(include_folder, library_header)
library_found = os.path.isfile(library_header_path)
conda_installed = library_found
else:
# Check if using Anaconda to produce wheels
conda = shutil.which("conda")
is_conda = conda is not None
print(f"Running build on conda: {is_conda}")
if is_conda:
python_executable = sys.executable
py_folder = os.path.dirname(python_executable)
if os.name == "nt":
env_path = os.path.join(py_folder, "Library")
else:
env_path = os.path.dirname(py_folder)
lib_folder = os.path.join(env_path, "lib")
include_folder = os.path.join(env_path, "include")
library_header_path = os.path.join(include_folder, library_header)
library_found = os.path.isfile(library_header_path)
conda_installed = library_found
if not library_found:
if sys.platform == "linux":
library_found = os.path.exists(f"/usr/include/{library_header}")
library_found = library_found or os.path.exists(f"/usr/local/include/{library_header}")
return library_found, conda_installed, include_folder, lib_folder
def get_extensions():
this_dir = os.path.dirname(os.path.abspath(__file__))
extensions_dir = os.path.join(this_dir, "torchvision", "csrc")
main_file = glob.glob(os.path.join(extensions_dir, "*.cpp")) + glob.glob(
os.path.join(extensions_dir, "ops", "*.cpp")
)
source_cpu = (
glob.glob(os.path.join(extensions_dir, "ops", "autograd", "*.cpp"))
+ glob.glob(os.path.join(extensions_dir, "ops", "cpu", "*.cpp"))
+ glob.glob(os.path.join(extensions_dir, "ops", "quantized", "cpu", "*.cpp"))
)
is_rocm_pytorch = False
if torch.__version__ >= "1.5":
from torch.utils.cpp_extension import ROCM_HOME
is_rocm_pytorch = (torch.version.hip is not None) and (ROCM_HOME is not None)
if is_rocm_pytorch:
from torch.utils.hipify import hipify_python
hipify_python.hipify(
project_directory=this_dir,
output_directory=this_dir,
includes="torchvision/csrc/ops/cuda/*",
show_detailed=True,
is_pytorch_extension=True,
)
source_cuda = glob.glob(os.path.join(extensions_dir, "ops", "hip", "*.hip"))
# Copy over additional files
for file in glob.glob(r"torchvision/csrc/ops/cuda/*.h"):
shutil.copy(file, "torchvision/csrc/ops/hip")
else:
source_cuda = glob.glob(os.path.join(extensions_dir, "ops", "cuda", "*.cu"))
source_cuda += glob.glob(os.path.join(extensions_dir, "ops", "autocast", "*.cpp"))
sources = main_file + source_cpu
extension = CppExtension
compile_cpp_tests = os.getenv("WITH_CPP_MODELS_TEST", "0") == "1"
if compile_cpp_tests:
test_dir = os.path.join(this_dir, "test")
models_dir = os.path.join(this_dir, "torchvision", "csrc", "models")
test_file = glob.glob(os.path.join(test_dir, "*.cpp"))
source_models = glob.glob(os.path.join(models_dir, "*.cpp"))
test_file = [os.path.join(test_dir, s) for s in test_file]
source_models = [os.path.join(models_dir, s) for s in source_models]
tests = test_file + source_models
tests_include_dirs = [test_dir, models_dir]
define_macros = []
extra_compile_args = {"cxx": []}
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)]
nvcc_flags = os.getenv("NVCC_FLAGS", "")
if nvcc_flags == "":
nvcc_flags = []
else:
nvcc_flags = nvcc_flags.split(" ")
else:
define_macros += [("WITH_HIP", None)]
nvcc_flags = []
extra_compile_args["nvcc"] = nvcc_flags
if sys.platform == "win32":
define_macros += [("torchvision_EXPORTS", None)]
define_macros += [("USE_PYTHON", None)]
extra_compile_args["cxx"].append("/MP")
debug_mode = os.getenv("DEBUG", "0") == "1"
if debug_mode:
print("Compile in debug mode")
extra_compile_args["cxx"].append("-g")
extra_compile_args["cxx"].append("-O0")
if "nvcc" in extra_compile_args:
# we have to remove "-OX" and "-g" flag if exists and append
nvcc_flags = extra_compile_args["nvcc"]
extra_compile_args["nvcc"] = [f for f in nvcc_flags if not ("-O" in f or "-g" in f)]
extra_compile_args["nvcc"].append("-O0")
extra_compile_args["nvcc"].append("-g")
sources = [os.path.join(extensions_dir, s) for s in sources]
include_dirs = [extensions_dir]
ext_modules = [
extension(
"torchvision._C",
sorted(sources),
include_dirs=include_dirs,
define_macros=define_macros,
extra_compile_args=extra_compile_args,
)
]
if compile_cpp_tests:
ext_modules.append(
extension(
"torchvision._C_tests",
tests,
include_dirs=tests_include_dirs,
define_macros=define_macros,
extra_compile_args=extra_compile_args,
)
)
# ------------------- Torchvision extra extensions ------------------------
vision_include = os.environ.get("TORCHVISION_INCLUDE", None)
vision_library = os.environ.get("TORCHVISION_LIBRARY", None)
vision_include = vision_include.split(os.pathsep) if vision_include is not None else []
vision_library = vision_library.split(os.pathsep) if vision_library is not None else []
include_dirs += vision_include
library_dirs = vision_library
# Image reading extension
image_macros = []
image_include = [extensions_dir]
image_library = []
image_link_flags = []
if sys.platform == "win32":
image_macros += [("USE_PYTHON", None)]
# Locating libPNG
libpng = shutil.which("libpng-config")
pngfix = shutil.which("pngfix")
png_found = libpng is not None or pngfix is not None
print(f"PNG found: {png_found}")
if png_found:
if libpng is not None:
# Linux / Mac
png_version = subprocess.run([libpng, "--version"], stdout=subprocess.PIPE)
png_version = png_version.stdout.strip().decode("utf-8")
print(f"libpng version: {png_version}")
png_version = parse_version(png_version)
if png_version >= parse_version("1.6.0"):
print("Building torchvision with PNG image support")
png_lib = subprocess.run([libpng, "--libdir"], stdout=subprocess.PIPE)
png_lib = png_lib.stdout.strip().decode("utf-8")
if "disabled" not in png_lib:
image_library += [png_lib]
png_include = subprocess.run([libpng, "--I_opts"], stdout=subprocess.PIPE)
png_include = png_include.stdout.strip().decode("utf-8")
_, png_include = png_include.split("-I")
print(f"libpng include path: {png_include}")
image_include += [png_include]
image_link_flags.append("png")
else:
print("libpng installed version is less than 1.6.0, disabling PNG support")
png_found = False
else:
# Windows
png_lib = os.path.join(os.path.dirname(os.path.dirname(pngfix)), "lib")
png_include = os.path.join(os.path.dirname(os.path.dirname(pngfix)), "include", "libpng16")
image_library += [png_lib]
image_include += [png_include]
image_link_flags.append("libpng")
# Locating libjpeg
(jpeg_found, jpeg_conda, jpeg_include, jpeg_lib) = find_library("jpeglib", vision_include)
print(f"JPEG found: {jpeg_found}")
image_macros += [("PNG_FOUND", str(int(png_found)))]
image_macros += [("JPEG_FOUND", str(int(jpeg_found)))]
if jpeg_found:
print("Building torchvision with JPEG image support")
image_link_flags.append("jpeg")
if jpeg_conda:
image_library += [jpeg_lib]
image_include += [jpeg_include]
# Locating nvjpeg
# Should be included in CUDA_HOME for CUDA >= 10.1, which is the minimum version we have in the CI
nvjpeg_found = (
extension is CUDAExtension
and CUDA_HOME is not None
and os.path.exists(os.path.join(CUDA_HOME, "include", "nvjpeg.h"))
)
print(f"NVJPEG found: {nvjpeg_found}")
image_macros += [("NVJPEG_FOUND", str(int(nvjpeg_found)))]
if nvjpeg_found:
print("Building torchvision with NVJPEG image support")
image_link_flags.append("nvjpeg")
image_path = os.path.join(extensions_dir, "io", "image")
image_src = (
glob.glob(os.path.join(image_path, "*.cpp"))
+ glob.glob(os.path.join(image_path, "cpu", "*.cpp"))
+ glob.glob(os.path.join(image_path, "cuda", "*.cpp"))
)
if png_found or jpeg_found:
ext_modules.append(
extension(
"torchvision.image",
image_src,
include_dirs=image_include + include_dirs + [image_path],
library_dirs=image_library + library_dirs,
define_macros=image_macros,
libraries=image_link_flags,
extra_compile_args=extra_compile_args,
)
)
ffmpeg_exe = shutil.which("ffmpeg")
has_ffmpeg = ffmpeg_exe is not None
# FIXME: Building torchvision with ffmpeg on MacOS or with Python 3.9
# FIXME: causes crash. See the following GitHub issues for more details.
# FIXME: https://github.com/pytorch/pytorch/issues/65000
# FIXME: https://github.com/pytorch/vision/issues/3367
if sys.platform != "linux" or (sys.version_info.major == 3 and sys.version_info.minor == 9):
has_ffmpeg = False
if has_ffmpeg:
try:
# This is to check if ffmpeg is installed properly.
subprocess.check_output(["ffmpeg", "-version"])
except subprocess.CalledProcessError:
print("Error fetching ffmpeg version, ignoring ffmpeg.")
has_ffmpeg = False
use_ffmpeg = os.getenv("TORCHVISION_USE_FFMPEG", "1") == "1"
has_ffmpeg = has_ffmpeg and use_ffmpeg
print(f"FFmpeg found: {has_ffmpeg}")
if has_ffmpeg:
ffmpeg_libraries = {"libavcodec", "libavformat", "libavutil", "libswresample", "libswscale"}
ffmpeg_bin = os.path.dirname(ffmpeg_exe)
ffmpeg_root = os.path.dirname(ffmpeg_bin)
ffmpeg_include_dir = os.path.join(ffmpeg_root, "include")
ffmpeg_library_dir = os.path.join(ffmpeg_root, "lib")
gcc = os.environ.get("CC", shutil.which("gcc"))
platform_tag = subprocess.run([gcc, "-print-multiarch"], stdout=subprocess.PIPE)
platform_tag = platform_tag.stdout.strip().decode("utf-8")
if platform_tag:
# Most probably a Debian-based distribution
ffmpeg_include_dir = [ffmpeg_include_dir, os.path.join(ffmpeg_include_dir, platform_tag)]
ffmpeg_library_dir = [ffmpeg_library_dir, os.path.join(ffmpeg_library_dir, platform_tag)]
else:
ffmpeg_include_dir = [ffmpeg_include_dir]
ffmpeg_library_dir = [ffmpeg_library_dir]
has_ffmpeg = True
for library in ffmpeg_libraries:
library_found = False
for search_path in ffmpeg_include_dir + include_dirs:
full_path = os.path.join(search_path, library, "*.h")
library_found |= len(glob.glob(full_path)) > 0
if not library_found:
print(f"{library} header files were not found, disabling ffmpeg support")
has_ffmpeg = False
if has_ffmpeg:
print(f"ffmpeg include path: {ffmpeg_include_dir}")
print(f"ffmpeg library_dir: {ffmpeg_library_dir}")
# TorchVision base decoder + video reader
video_reader_src_dir = os.path.join(this_dir, "torchvision", "csrc", "io", "video_reader")
video_reader_src = glob.glob(os.path.join(video_reader_src_dir, "*.cpp"))
base_decoder_src_dir = os.path.join(this_dir, "torchvision", "csrc", "io", "decoder")
base_decoder_src = glob.glob(os.path.join(base_decoder_src_dir, "*.cpp"))
# Torchvision video API
videoapi_src_dir = os.path.join(this_dir, "torchvision", "csrc", "io", "video")
videoapi_src = glob.glob(os.path.join(videoapi_src_dir, "*.cpp"))
# exclude tests
base_decoder_src = [x for x in base_decoder_src if "_test.cpp" not in x]
combined_src = video_reader_src + base_decoder_src + videoapi_src
ext_modules.append(
CppExtension(
"torchvision.video_reader",
combined_src,
include_dirs=[
base_decoder_src_dir,
video_reader_src_dir,
videoapi_src_dir,
extensions_dir,
*ffmpeg_include_dir,
*include_dirs,
],
library_dirs=ffmpeg_library_dir + library_dirs,
libraries=[
"avcodec",
"avformat",
"avutil",
"swresample",
"swscale",
],
extra_compile_args=["-std=c++14"] if os.name != "nt" else ["/std:c++14", "/MP"],
extra_link_args=["-std=c++14" if os.name != "nt" else "/std:c++14"],
)
)
# Locating video codec
# CUDA_HOME should be set to the cuda root directory.
# TORCHVISION_INCLUDE and TORCHVISION_LIBRARY should include the location to
# video codec header files and libraries respectively.
video_codec_found = (
extension is CUDAExtension
and CUDA_HOME is not None
and any([os.path.exists(os.path.join(folder, "cuviddec.h")) for folder in vision_include])
and any([os.path.exists(os.path.join(folder, "nvcuvid.h")) for folder in vision_include])
and any([os.path.exists(os.path.join(folder, "libnvcuvid.so")) for folder in library_dirs])
)
print(f"video codec found: {video_codec_found}")
if (
video_codec_found
and has_ffmpeg
and any([os.path.exists(os.path.join(folder, "libavcodec", "bsf.h")) for folder in ffmpeg_include_dir])
):
gpu_decoder_path = os.path.join(extensions_dir, "io", "decoder", "gpu")
gpu_decoder_src = glob.glob(os.path.join(gpu_decoder_path, "*.cpp"))
cuda_libs = os.path.join(CUDA_HOME, "lib64")
cuda_inc = os.path.join(CUDA_HOME, "include")
ext_modules.append(
extension(
"torchvision.Decoder",
gpu_decoder_src,
include_dirs=include_dirs + [gpu_decoder_path] + [cuda_inc] + ffmpeg_include_dir,
library_dirs=ffmpeg_library_dir + library_dirs + [cuda_libs],
libraries=[
"avcodec",
"avformat",
"avutil",
"swresample",
"swscale",
"nvcuvid",
"cuda",
"cudart",
"z",
"pthread",
"dl",
"nppicc",
],
extra_compile_args=extra_compile_args,
)
)
else:
print(
"The installed version of ffmpeg is missing the header file 'bsf.h' which is "
"required for GPU video decoding. Please install the latest ffmpeg from conda-forge channel:"
" `conda install -c conda-forge ffmpeg`."
)
return ext_modules
class clean(distutils.command.clean.clean):
def run(self):
with open(".gitignore") as f:
ignores = f.read()
for wildcard in filter(None, ignores.split("\n")):
for filename in glob.glob(wildcard):
try:
os.remove(filename)
except OSError:
shutil.rmtree(filename, ignore_errors=True)
# It's an old-style class in Python 2.7...
distutils.command.clean.clean.run(self)
if __name__ == "__main__":
print(f"Building wheel {package_name}-{version}")
write_version_file()
with open("README.rst") as f:
readme = f.read()
setup(
# Metadata
name=package_name,
version=version,
author="PyTorch Core Team",
author_email="soumith@pytorch.org",
url="https://github.com/pytorch/vision",
description="image and video datasets and models for torch deep learning",
long_description=readme,
license="BSD",
# Package info
packages=find_packages(exclude=("test",)),
package_data={package_name: ["*.dll", "*.dylib", "*.so", "prototype/datasets/_builtin/*.categories"]},
zip_safe=False,
install_requires=requirements,
extras_require={
"scipy": ["scipy"],
},
ext_modules=get_extensions(),
python_requires=">=3.7",
cmdclass={
"build_ext": BuildExtension.with_options(no_python_abi_suffix=True),
"clean": clean,
},
)