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#!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import os
from setuptools import find_packages, setup
def get_version():
init_py_path = os.path.join(
os.path.abspath(os.path.dirname(__file__)), "pytorchvideo", "__init__.py"
)
init_py = open(init_py_path, "r").readlines()
version_line = [
lines.strip() for lines in init_py if lines.startswith("__version__")
][0]
version = version_line.split("=")[-1].strip().strip("'\"")
# Used by CI to build nightly packages. Users should never use it.
# To build a nightly wheel, run:
# BUILD_NIGHTLY=1 python setup.py sdist
if os.getenv("BUILD_NIGHTLY", "0") == "1":
from datetime import datetime
date_str = datetime.today().strftime("%Y%m%d")
# pip can perform proper comparison for ".post" suffix,
# i.e., "1.1.post1234" >= "1.1"
version = version + ".post" + 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_name():
name = "pytorchvideo"
if os.getenv("BUILD_NIGHTLY", "0") == "1":
name += "-nightly"
return name
setup(
name=get_name(),
version=get_version(),
license="Apache 2.0",
author="Facebook AI",
url="https://github.com/facebookresearch/pytorchvideo",
description="A video understanding deep learning library.",
python_requires=">=3.7",
install_requires=[
"fvcore",
"av",
"parameterized",
"iopath",
"networkx",
],
extras_require={
"test": ["coverage", "pytest", "opencv-python", "decord"],
"dev": [
"opencv-python",
"decord",
"black==20.8b1",
"sphinx",
"isort==4.3.21",
"flake8==3.8.1",
"flake8-bugbear",
"flake8-comprehensions",
"pre-commit",
"nbconvert",
"bs4",
"autoflake==1.4",
],
"opencv-python": [
"opencv-python",
],
},
packages=find_packages(exclude=("scripts", "tests")),
)
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