mirror of
https://github.com/vale981/ray
synced 2025-03-06 02:21:39 -05:00
231 lines
8 KiB
Python
231 lines
8 KiB
Python
from itertools import chain
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import os
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import re
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import shutil
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import subprocess
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import sys
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from setuptools import setup, find_packages, Distribution
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import setuptools.command.build_ext as _build_ext
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# Ideally, we could include these files by putting them in a
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# MANIFEST.in or using the package_data argument to setup, but the
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# MANIFEST.in gets applied at the very beginning when setup.py runs
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# before these files have been created, so we have to move the files
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# manually.
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exe_suffix = ".exe" if sys.platform == "win32" else ""
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# .pyd is the extension Python requires on Windows for shared libraries.
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# https://docs.python.org/3/faq/windows.html#is-a-pyd-file-the-same-as-a-dll
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pyd_suffix = ".pyd" if sys.platform == "win32" else ".so"
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# NOTE: The lists below must be kept in sync with ray/BUILD.bazel.
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ray_files = [
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"ray/core/src/ray/thirdparty/redis/src/redis-server",
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"ray/core/src/ray/gcs/redis_module/libray_redis_module.so",
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"ray/core/src/plasma/plasma_store_server" + exe_suffix,
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"ray/_raylet" + pyd_suffix,
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"ray/core/src/ray/raylet/raylet_monitor" + exe_suffix,
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"ray/core/src/ray/gcs/gcs_server" + exe_suffix,
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"ray/core/src/ray/raylet/raylet" + exe_suffix,
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"ray/streaming/_streaming.so",
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]
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build_java = os.getenv("RAY_INSTALL_JAVA") == "1"
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if build_java:
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ray_files.append("ray/jars/ray_dist.jar")
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# These are the directories where automatically generated Python protobuf
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# bindings are created.
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generated_python_directories = [
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"ray/core/generated",
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"ray/streaming/generated",
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]
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optional_ray_files = []
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ray_autoscaler_files = [
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"ray/autoscaler/aws/example-full.yaml",
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"ray/autoscaler/azure/example-full.yaml",
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"ray/autoscaler/azure/azure-vm-template.json",
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"ray/autoscaler/azure/azure-config-template.json",
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"ray/autoscaler/gcp/example-full.yaml",
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"ray/autoscaler/local/example-full.yaml",
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"ray/autoscaler/kubernetes/example-full.yaml",
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"ray/autoscaler/kubernetes/kubectl-rsync.sh",
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"ray/autoscaler/ray-schema.json"
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]
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ray_project_files = [
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"ray/projects/schema.json", "ray/projects/templates/cluster_template.yaml",
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"ray/projects/templates/project_template.yaml",
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"ray/projects/templates/requirements.txt"
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]
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ray_dashboard_files = [
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os.path.join(dirpath, filename)
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for dirpath, dirnames, filenames in os.walk("ray/dashboard/client/build")
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for filename in filenames
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]
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optional_ray_files += ray_autoscaler_files
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optional_ray_files += ray_project_files
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optional_ray_files += ray_dashboard_files
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if "RAY_USE_NEW_GCS" in os.environ and os.environ["RAY_USE_NEW_GCS"] == "on":
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ray_files += [
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"ray/core/src/credis/build/src/libmember.so",
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"ray/core/src/credis/build/src/libmaster.so",
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"ray/core/src/credis/redis/src/redis-server"
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]
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extras = {
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"debug": [],
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"dashboard": ["requests"],
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"serve": ["uvicorn", "flask", "blist"],
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"tune": ["tabulate", "tensorboardX", "pandas"]
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}
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extras["rllib"] = extras["tune"] + [
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"atari_py",
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"dm_tree",
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"gym[atari]",
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"lz4",
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"opencv-python-headless",
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"pyyaml",
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"scipy",
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]
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extras["streaming"] = ["msgpack >= 0.6.2"]
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extras["all"] = list(set(chain.from_iterable(extras.values())))
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class build_ext(_build_ext.build_ext):
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def run(self):
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# Note: We are passing in sys.executable so that we use the same
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# version of Python to build packages inside the build.sh script. Note
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# that certain flags will not be passed along such as --user or sudo.
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# TODO(rkn): Fix this.
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command = ["../build.sh", "-p", sys.executable]
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if sys.platform == "win32" and command[0].lower().endswith(".sh"):
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# We can't run .sh files directly in Windows, so find a shell.
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# Don't use "bash" instead of "sh", because that might run the Bash
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# from WSL! (We want MSYS2's Bash, which is also sh by default.)
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shell = os.getenv("BAZEL_SH", "sh") # NOT "bash"! (see above)
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command.insert(0, shell)
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if build_java:
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# Also build binaries for Java if the above env variable exists.
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command += ["-l", "python,java"]
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subprocess.check_call(command)
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# We also need to install pickle5 along with Ray, so make sure that the
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# relevant non-Python pickle5 files get copied.
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pickle5_files = self.walk_directory("./ray/pickle5_files/pickle5")
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thirdparty_files = self.walk_directory("./ray/thirdparty_files")
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files_to_include = ray_files + pickle5_files + thirdparty_files
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# Copy over the autogenerated protobuf Python bindings.
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for directory in generated_python_directories:
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for filename in os.listdir(directory):
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if filename[-3:] == ".py":
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files_to_include.append(os.path.join(directory, filename))
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for filename in files_to_include:
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self.move_file(filename)
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# Try to copy over the optional files.
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for filename in optional_ray_files:
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try:
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self.move_file(filename)
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except Exception:
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print("Failed to copy optional file {}. This is ok."
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.format(filename))
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def walk_directory(self, directory):
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file_list = []
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for (root, dirs, filenames) in os.walk(directory):
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for name in filenames:
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file_list.append(os.path.join(root, name))
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return file_list
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def move_file(self, filename):
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# TODO(rkn): This feels very brittle. It may not handle all cases. See
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# https://github.com/apache/arrow/blob/master/python/setup.py for an
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# example.
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source = filename
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destination = os.path.join(self.build_lib, filename)
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# Create the target directory if it doesn't already exist.
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os.makedirs(os.path.dirname(destination), exist_ok=True)
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if not os.path.exists(destination):
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print("Copying {} to {}.".format(source, destination))
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if sys.platform == "win32":
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# Does not preserve file mode (needed to avoid read-only bit)
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shutil.copyfile(source, destination, follow_symlinks=True)
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else:
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# Preserves file mode (needed to copy executable bit)
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shutil.copy(source, destination, follow_symlinks=True)
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class BinaryDistribution(Distribution):
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def has_ext_modules(self):
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return True
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def find_version(*filepath):
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# Extract version information from filepath
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here = os.path.abspath(os.path.dirname(__file__))
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with open(os.path.join(here, *filepath)) as fp:
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version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]",
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fp.read(), re.M)
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if version_match:
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return version_match.group(1)
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raise RuntimeError("Unable to find version string.")
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requires = [
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"aiohttp",
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"click",
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"colorama",
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"filelock",
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"google",
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"grpcio",
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"jsonschema",
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"msgpack >= 0.6.0, < 1.0.0",
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"numpy >= 1.16",
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"protobuf >= 3.8.0",
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"py-spy >= 0.2.0",
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"pyyaml",
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"redis >= 3.3.2, < 3.5.0",
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]
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setup(
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name="ray",
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version=find_version("ray", "__init__.py"),
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author="Ray Team",
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author_email="ray-dev@googlegroups.com",
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description=("A system for parallel and distributed Python that unifies "
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"the ML ecosystem."),
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long_description=open("../README.rst").read(),
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url="https://github.com/ray-project/ray",
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keywords=("ray distributed parallel machine-learning "
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"reinforcement-learning deep-learning python"),
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packages=find_packages(),
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cmdclass={"build_ext": build_ext},
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# The BinaryDistribution argument triggers build_ext.
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distclass=BinaryDistribution,
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install_requires=requires,
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setup_requires=["cython >= 0.29.14", "wheel"],
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extras_require=extras,
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entry_points={
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"console_scripts": [
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"ray=ray.scripts.scripts:main",
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"rllib=ray.rllib.scripts:cli [rllib]", "tune=ray.tune.scripts:cli"
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]
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},
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include_package_data=True,
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zip_safe=False,
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license="Apache 2.0")
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