ray/python/setup.py

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from itertools import chain
import os
import re
import shutil
import subprocess
import sys
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from setuptools import setup, find_packages, Distribution
import setuptools.command.build_ext as _build_ext
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# Ideally, we could include these files by putting them in a
# MANIFEST.in or using the package_data argument to setup, but the
# MANIFEST.in gets applied at the very beginning when setup.py runs
# before these files have been created, so we have to move the files
# manually.
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# NOTE: The lists below must be kept in sync with ray/BUILD.bazel.
ray_files = [
"ray/core/src/ray/thirdparty/redis/src/redis-server",
"ray/core/src/ray/gcs/redis_module/libray_redis_module.so",
"ray/core/src/plasma/plasma_store_server",
"ray/_raylet.so",
"ray/core/src/ray/raylet/raylet_monitor",
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"ray/core/src/ray/gcs/gcs_server",
"ray/core/src/ray/raylet/raylet",
"ray/dashboard/dashboard.py",
"ray/streaming/_streaming.so",
]
build_java = os.getenv("RAY_INSTALL_JAVA") == "1"
if build_java:
ray_files.append("ray/jars/ray_dist.jar")
# These are the directories where automatically generated Python protobuf
# bindings are created.
generated_python_directories = [
"ray/core/generated",
"ray/streaming/generated",
]
optional_ray_files = []
[autoscaler] GCP node provider (#2061) * Google Cloud Platform scaffolding * Add minimal gcp config example * Add googleapiclient discoveries, update gcp.config constants * Rename and update gcp.config key pair name function * Implement gcp.config._configure_project * Fix the create project get project flow * Implement gcp.config._configure_iam_role * Implement service account iam binding * Implement gcp.config._configure_key_pair * Implement rsa key pair generation * Implement gcp.config._configure_subnet * Save work-in-progress gcp.config._configure_firewall_rules. These are likely to be not needed at all. Saving them if we happen to need them later. * Remove unnecessary firewall configuration * Update example-minimal.yaml configuration * Add new wait_for_compute_operation, rename old wait_for_operation * Temporarily rename autoscaler tags due to gcp incompatibility * Implement initial gcp.node_provider.nodes * Still missing filter support * Implement initial gcp.node_provider.create_node * Implement another compute wait operation (wait_For_compute_zone_operation). TODO: figure out if we can remove the function. * Implement initial gcp.node_provider._node and node status functions * Implement initial gcp.node_provider.terminate_node * Implement node tagging and ip getter methods for nodes * Temporarily rename tags due to gcp incompatibility * Tiny tweaks for autoscaler.updater * Remove unused config from gcp node_provider * Add new example-full example to gcp, update load_gcp_example_config * Implement label filtering for gcp.node_provider.nodes * Revert unnecessary change in ssh command * Revert "Temporarily rename tags due to gcp incompatibility" This reverts commit e2fe634c5d11d705c0f5d3e76c80c37394bb23fb. * Revert "Temporarily rename autoscaler tags due to gcp incompatibility" This reverts commit c938ee435f4b75854a14e78242ad7f1d1ed8ad4b. * Refactor autoscaler tagging to support multiple tag specs * Remove missing cryptography imports * Update quote function import * Fix threading issue in gcp.config with the compute discovery object * Add gcs support for log_sync * Fix the labels/tags naming discrepancy * Add expanduser to file_mounts hashing * Fix gcp.node_provider.internal_ip * Add uuid to node name * Remove 'set -i' from updater ssh command * Also add TODO with the context and reason for the change. * Update ssh key creation in autoscaler.gcp.config * Fix wait_for_compute_zone_operation's threading issue Google discovery api's compute object is not thread safe, and thus needs to be recreated for each thread. This moves the `wait_for_compute_zone_operation` under `autoscaler.gcp.config`, and adds compute as its argument. * Address pr feedback from @ericl * Expand local file mount paths in NodeUpdater * Add ssh_user name to key names * Update updater ssh to attempt 'set -i' and fall back if that fails * Update gcp/example-full.yaml * Fix wait crm operation in gcp.config * Update gcp/example-minimal.yaml to match aws/example-minimal.yaml * Fix gcp/example-full.yaml comment indentation * Add gcp/example-full.yaml to setup files * Update example-full.yaml command * Revert "Refactor autoscaler tagging to support multiple tag specs" This reverts commit 9cf48409ca2e5b66f800153853072c706fa502f6. * Update tag spec to only use characters [0-9a-z_-] * Change the tag values to conform gcp spec * Add project_id in the ssh key name * Replace '_' with '-' in autoscaler tag names * Revert "Update updater ssh to attempt 'set -i' and fall back if that fails" This reverts commit 23a0066c5254449e49746bd5e43b94b66f32bfb4. * Revert "Remove 'set -i' from updater ssh command" This reverts commit 5fa034cdf79fa7f8903691518c0d75699c630172. * Add fallback to `set -i` in force_interactive command * Update autoscaler tests to match current implementation * Update GCPNodeProvider.create_node to include hash in instance name * Add support for creating multiple instance on one create_node call * Clean TODOs * Update styles * Replace single quotes with double quotes * Some minor indentation fixes etc. * Remove unnecessary comment. Fix indentation. * Yapfify files that fail flake8 test * Yapfify more files * Update project_id handling in gcp node provider * temporary yapf mod * Revert "temporary yapf mod" This reverts commit b6744e4e15d4d936d1a14f4bf155ed1d3bb14126. * Fix autoscaler/updater.py lint error, remove unused variable
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ray_autoscaler_files = [
"ray/autoscaler/aws/example-full.yaml",
"ray/autoscaler/gcp/example-full.yaml",
"ray/autoscaler/local/example-full.yaml",
"ray/autoscaler/kubernetes/example-full.yaml",
"ray/autoscaler/kubernetes/kubectl-rsync.sh",
[autoscaler] GCP node provider (#2061) * Google Cloud Platform scaffolding * Add minimal gcp config example * Add googleapiclient discoveries, update gcp.config constants * Rename and update gcp.config key pair name function * Implement gcp.config._configure_project * Fix the create project get project flow * Implement gcp.config._configure_iam_role * Implement service account iam binding * Implement gcp.config._configure_key_pair * Implement rsa key pair generation * Implement gcp.config._configure_subnet * Save work-in-progress gcp.config._configure_firewall_rules. These are likely to be not needed at all. Saving them if we happen to need them later. * Remove unnecessary firewall configuration * Update example-minimal.yaml configuration * Add new wait_for_compute_operation, rename old wait_for_operation * Temporarily rename autoscaler tags due to gcp incompatibility * Implement initial gcp.node_provider.nodes * Still missing filter support * Implement initial gcp.node_provider.create_node * Implement another compute wait operation (wait_For_compute_zone_operation). TODO: figure out if we can remove the function. * Implement initial gcp.node_provider._node and node status functions * Implement initial gcp.node_provider.terminate_node * Implement node tagging and ip getter methods for nodes * Temporarily rename tags due to gcp incompatibility * Tiny tweaks for autoscaler.updater * Remove unused config from gcp node_provider * Add new example-full example to gcp, update load_gcp_example_config * Implement label filtering for gcp.node_provider.nodes * Revert unnecessary change in ssh command * Revert "Temporarily rename tags due to gcp incompatibility" This reverts commit e2fe634c5d11d705c0f5d3e76c80c37394bb23fb. * Revert "Temporarily rename autoscaler tags due to gcp incompatibility" This reverts commit c938ee435f4b75854a14e78242ad7f1d1ed8ad4b. * Refactor autoscaler tagging to support multiple tag specs * Remove missing cryptography imports * Update quote function import * Fix threading issue in gcp.config with the compute discovery object * Add gcs support for log_sync * Fix the labels/tags naming discrepancy * Add expanduser to file_mounts hashing * Fix gcp.node_provider.internal_ip * Add uuid to node name * Remove 'set -i' from updater ssh command * Also add TODO with the context and reason for the change. * Update ssh key creation in autoscaler.gcp.config * Fix wait_for_compute_zone_operation's threading issue Google discovery api's compute object is not thread safe, and thus needs to be recreated for each thread. This moves the `wait_for_compute_zone_operation` under `autoscaler.gcp.config`, and adds compute as its argument. * Address pr feedback from @ericl * Expand local file mount paths in NodeUpdater * Add ssh_user name to key names * Update updater ssh to attempt 'set -i' and fall back if that fails * Update gcp/example-full.yaml * Fix wait crm operation in gcp.config * Update gcp/example-minimal.yaml to match aws/example-minimal.yaml * Fix gcp/example-full.yaml comment indentation * Add gcp/example-full.yaml to setup files * Update example-full.yaml command * Revert "Refactor autoscaler tagging to support multiple tag specs" This reverts commit 9cf48409ca2e5b66f800153853072c706fa502f6. * Update tag spec to only use characters [0-9a-z_-] * Change the tag values to conform gcp spec * Add project_id in the ssh key name * Replace '_' with '-' in autoscaler tag names * Revert "Update updater ssh to attempt 'set -i' and fall back if that fails" This reverts commit 23a0066c5254449e49746bd5e43b94b66f32bfb4. * Revert "Remove 'set -i' from updater ssh command" This reverts commit 5fa034cdf79fa7f8903691518c0d75699c630172. * Add fallback to `set -i` in force_interactive command * Update autoscaler tests to match current implementation * Update GCPNodeProvider.create_node to include hash in instance name * Add support for creating multiple instance on one create_node call * Clean TODOs * Update styles * Replace single quotes with double quotes * Some minor indentation fixes etc. * Remove unnecessary comment. Fix indentation. * Yapfify files that fail flake8 test * Yapfify more files * Update project_id handling in gcp node provider * temporary yapf mod * Revert "temporary yapf mod" This reverts commit b6744e4e15d4d936d1a14f4bf155ed1d3bb14126. * Fix autoscaler/updater.py lint error, remove unused variable
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]
ray_project_files = [
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"ray/projects/schema.json", "ray/projects/templates/cluster_template.yaml",
"ray/projects/templates/project_template.yaml",
"ray/projects/templates/requirements.txt"
]
ray_dashboard_files = [
os.path.join(dirpath, filename)
for dirpath, dirnames, filenames in os.walk("ray/dashboard/client/build")
for filename in filenames
]
optional_ray_files += ray_autoscaler_files
optional_ray_files += ray_project_files
optional_ray_files += ray_dashboard_files
if "RAY_USE_NEW_GCS" in os.environ and os.environ["RAY_USE_NEW_GCS"] == "on":
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ray_files += [
"ray/core/src/credis/build/src/libmember.so",
"ray/core/src/credis/build/src/libmaster.so",
"ray/core/src/credis/redis/src/redis-server"
]
extras = {
"debug": [],
"dashboard": [],
"serve": ["uvicorn", "pygments", "werkzeug", "flask", "pandas", "blist"],
"tune": ["tabulate", "tensorboardX"],
}
extras["rllib"] = extras["tune"] + [
[RLlib] SAC add discrete action support. (#7320) * Exploration API (+EpsilonGreedy sub-class). * Exploration API (+EpsilonGreedy sub-class). * Cleanup/LINT. * Add `deterministic` to generic Trainer config (NOTE: this is still ignored by most Agents). * Add `error` option to deprecation_warning(). * WIP. * Bug fix: Get exploration-info for tf framework. Bug fix: Properly deprecate some DQN config keys. * WIP. * LINT. * WIP. * Split PerWorkerEpsilonGreedy out of EpsilonGreedy. Docstrings. * Fix bug in sampler.py in case Policy has self.exploration = None * Update rllib/agents/dqn/dqn.py Co-Authored-By: Eric Liang <ekhliang@gmail.com> * WIP. * Update rllib/agents/trainer.py Co-Authored-By: Eric Liang <ekhliang@gmail.com> * WIP. * Change requests. * LINT * In tune/utils/util.py::deep_update() Only keep deep_updat'ing if both original and value are dicts. If value is not a dict, set * Completely obsolete syn_replay_optimizer.py's parameters schedule_max_timesteps AND beta_annealing_fraction (replaced with prioritized_replay_beta_annealing_timesteps). * Update rllib/evaluation/worker_set.py Co-Authored-By: Eric Liang <ekhliang@gmail.com> * Review fixes. * Fix default value for DQN's exploration spec. * LINT * Fix recursion bug (wrong parent c'tor). * Do not pass timestep to get_exploration_info. * Update tf_policy.py * Fix some remaining issues with test cases and remove more deprecated DQN/APEX exploration configs. * Bug fix tf-action-dist * DDPG incompatibility bug fix with new DQN exploration handling (which is imported by DDPG). * Switch off exploration when getting action probs from off-policy-estimator's policy. * LINT * Fix test_checkpoint_restore.py. * Deprecate all SAC exploration (unused) configs. * Properly use `model.last_output()` everywhere. Instead of `model._last_output`. * WIP. * Take out set_epsilon from multi-agent-env test (not needed, decays anyway). * WIP. * Trigger re-test (flaky checkpoint-restore test). * WIP. * WIP. * Add test case for deterministic action sampling in PPO. * bug fix. * Added deterministic test cases for different Agents. * Fix problem with TupleActions in dynamic-tf-policy. * Separate supported_spaces tests so they can be run separately for easier debugging. * LINT. * Fix autoregressive_action_dist.py test case. * Re-test. * Fix. * Remove duplicate py_test rule from bazel. * LINT. * WIP. * WIP. * SAC fix. * SAC fix. * WIP. * WIP. * WIP. * FIX 2 examples tests. * WIP. * WIP. * WIP. * WIP. * WIP. * Fix. * LINT. * Renamed test file. * WIP. * Add unittest.main. * Make action_dist_class mandatory. * fix * FIX. * WIP. * WIP. * Fix. * Fix. * Fix explorations test case (contextlib cannot find its own nullcontext??). * Force torch to be installed for QMIX. * LINT. * Fix determine_tests_to_run.py. * Fix determine_tests_to_run.py. * WIP * Add Random exploration component to tests (fixed issue with "static-graph randomness" via py_function). * Add Random exploration component to tests (fixed issue with "static-graph randomness" via py_function). * Rename some stuff. * Rename some stuff. * WIP. * update. * WIP. * Gumbel Softmax Dist. * WIP. * WIP. * WIP. * WIP. * WIP. * WIP. * WIP * WIP. * WIP. * Hypertune. * Hypertune. * Hypertune. * Lock-in. * Cleanup. * LINT. * Fix. * Update rllib/policy/eager_tf_policy.py Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com> * Update rllib/agents/sac/sac_policy.py Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com> * Update rllib/agents/sac/sac_policy.py Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com> * Update rllib/models/tf/tf_action_dist.py Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com> * Update rllib/models/tf/tf_action_dist.py Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com> * Fix items from review comments. * Add dm_tree to RLlib dependencies. * Add dm_tree to RLlib dependencies. * Fix DQN test cases ((Torch)Categorical). * Fix wrong pip install. Co-authored-by: Eric Liang <ekhliang@gmail.com> Co-authored-by: Kristian Hartikainen <kristian.hartikainen@gmail.com>
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"atari_py",
"dm_tree",
"gym[atari]",
"lz4",
[RLlib] SAC add discrete action support. (#7320) * Exploration API (+EpsilonGreedy sub-class). * Exploration API (+EpsilonGreedy sub-class). * Cleanup/LINT. * Add `deterministic` to generic Trainer config (NOTE: this is still ignored by most Agents). * Add `error` option to deprecation_warning(). * WIP. * Bug fix: Get exploration-info for tf framework. Bug fix: Properly deprecate some DQN config keys. * WIP. * LINT. * WIP. * Split PerWorkerEpsilonGreedy out of EpsilonGreedy. Docstrings. * Fix bug in sampler.py in case Policy has self.exploration = None * Update rllib/agents/dqn/dqn.py Co-Authored-By: Eric Liang <ekhliang@gmail.com> * WIP. * Update rllib/agents/trainer.py Co-Authored-By: Eric Liang <ekhliang@gmail.com> * WIP. * Change requests. * LINT * In tune/utils/util.py::deep_update() Only keep deep_updat'ing if both original and value are dicts. If value is not a dict, set * Completely obsolete syn_replay_optimizer.py's parameters schedule_max_timesteps AND beta_annealing_fraction (replaced with prioritized_replay_beta_annealing_timesteps). * Update rllib/evaluation/worker_set.py Co-Authored-By: Eric Liang <ekhliang@gmail.com> * Review fixes. * Fix default value for DQN's exploration spec. * LINT * Fix recursion bug (wrong parent c'tor). * Do not pass timestep to get_exploration_info. * Update tf_policy.py * Fix some remaining issues with test cases and remove more deprecated DQN/APEX exploration configs. * Bug fix tf-action-dist * DDPG incompatibility bug fix with new DQN exploration handling (which is imported by DDPG). * Switch off exploration when getting action probs from off-policy-estimator's policy. * LINT * Fix test_checkpoint_restore.py. * Deprecate all SAC exploration (unused) configs. * Properly use `model.last_output()` everywhere. Instead of `model._last_output`. * WIP. * Take out set_epsilon from multi-agent-env test (not needed, decays anyway). * WIP. * Trigger re-test (flaky checkpoint-restore test). * WIP. * WIP. * Add test case for deterministic action sampling in PPO. * bug fix. * Added deterministic test cases for different Agents. * Fix problem with TupleActions in dynamic-tf-policy. * Separate supported_spaces tests so they can be run separately for easier debugging. * LINT. * Fix autoregressive_action_dist.py test case. * Re-test. * Fix. * Remove duplicate py_test rule from bazel. * LINT. * WIP. * WIP. * SAC fix. * SAC fix. * WIP. * WIP. * WIP. * FIX 2 examples tests. * WIP. * WIP. * WIP. * WIP. * WIP. * Fix. * LINT. * Renamed test file. * WIP. * Add unittest.main. * Make action_dist_class mandatory. * fix * FIX. * WIP. * WIP. * Fix. * Fix. * Fix explorations test case (contextlib cannot find its own nullcontext??). * Force torch to be installed for QMIX. * LINT. * Fix determine_tests_to_run.py. * Fix determine_tests_to_run.py. * WIP * Add Random exploration component to tests (fixed issue with "static-graph randomness" via py_function). * Add Random exploration component to tests (fixed issue with "static-graph randomness" via py_function). * Rename some stuff. * Rename some stuff. * WIP. * update. * WIP. * Gumbel Softmax Dist. * WIP. * WIP. * WIP. * WIP. * WIP. * WIP. * WIP * WIP. * WIP. * Hypertune. * Hypertune. * Hypertune. * Lock-in. * Cleanup. * LINT. * Fix. * Update rllib/policy/eager_tf_policy.py Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com> * Update rllib/agents/sac/sac_policy.py Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com> * Update rllib/agents/sac/sac_policy.py Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com> * Update rllib/models/tf/tf_action_dist.py Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com> * Update rllib/models/tf/tf_action_dist.py Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com> * Fix items from review comments. * Add dm_tree to RLlib dependencies. * Add dm_tree to RLlib dependencies. * Fix DQN test cases ((Torch)Categorical). * Fix wrong pip install. Co-authored-by: Eric Liang <ekhliang@gmail.com> Co-authored-by: Kristian Hartikainen <kristian.hartikainen@gmail.com>
2020-03-06 19:37:12 +01:00
"opencv-python-headless",
"pyyaml",
"scipy",
]
extras["streaming"] = ["msgpack >= 0.6.2"]
extras["all"] = list(set(chain.from_iterable(extras.values())))
class build_ext(_build_ext.build_ext):
def run(self):
# 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
# that certain flags will not be passed along such as --user or sudo.
# TODO(rkn): Fix this.
command = ["../build.sh", "-p", sys.executable]
if build_java:
# Also build binaries for Java if the above env variable exists.
command += ["-l", "python,java"]
subprocess.check_call(command)
# We also need to install pickle5 along with Ray, so make sure that the
# relevant non-Python pickle5 files get copied.
pickle5_files = self.walk_directory("./ray/pickle5_files/pickle5")
thirdparty_files = self.walk_directory("./ray/thirdparty_files")
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files_to_include = ray_files + pickle5_files + thirdparty_files
# Copy over the autogenerated protobuf Python bindings.
for directory in generated_python_directories:
for filename in os.listdir(directory):
if filename[-3:] == ".py":
files_to_include.append(os.path.join(directory, filename))
for filename in files_to_include:
self.move_file(filename)
# Try to copy over the optional files.
for filename in optional_ray_files:
try:
self.move_file(filename)
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except Exception:
print("Failed to copy optional file {}. This is ok."
.format(filename))
def walk_directory(self, directory):
file_list = []
for (root, dirs, filenames) in os.walk(directory):
for name in filenames:
file_list.append(os.path.join(root, name))
return file_list
def move_file(self, filename):
# TODO(rkn): This feels very brittle. It may not handle all cases. See
# https://github.com/apache/arrow/blob/master/python/setup.py for an
# example.
source = filename
destination = os.path.join(self.build_lib, filename)
# Create the target directory if it doesn't already exist.
parent_directory = os.path.dirname(destination)
if not os.path.exists(parent_directory):
os.makedirs(parent_directory)
if not os.path.exists(destination):
print("Copying {} to {}.".format(source, destination))
shutil.copy(source, destination, follow_symlinks=True)
class BinaryDistribution(Distribution):
def has_ext_modules(self):
return True
def find_version(*filepath):
# Extract version information from filepath
here = os.path.abspath(os.path.dirname(__file__))
with open(os.path.join(here, *filepath)) as fp:
version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]",
fp.read(), re.M)
if version_match:
return version_match.group(1)
raise RuntimeError("Unable to find version string.")
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requires = [
"numpy >= 1.16",
"filelock",
"jsonschema",
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"funcsigs",
"click",
"colorama",
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"packaging",
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"pytest",
"pyyaml",
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"redis>=3.3.2",
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# NOTE: Don't upgrade the version of six! Doing so causes installation
# problems. See https://github.com/ray-project/ray/issues/4169.
"six >= 1.0.0",
"faulthandler;python_version<'3.3'",
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"protobuf >= 3.8.0",
"cloudpickle",
"py-spy >= 0.2.0",
"aiohttp",
"google",
"grpcio"
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]
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setup(
name="ray",
version=find_version("ray", "__init__.py"),
author="Ray Team",
author_email="ray-dev@googlegroups.com",
description=("A system for parallel and distributed Python that unifies "
"the ML ecosystem."),
long_description=open("../README.rst").read(),
url="https://github.com/ray-project/ray",
keywords=("ray distributed parallel machine-learning "
"reinforcement-learning deep-learning python"),
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packages=find_packages(),
cmdclass={"build_ext": build_ext},
# The BinaryDistribution argument triggers build_ext.
distclass=BinaryDistribution,
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install_requires=requires,
setup_requires=["cython >= 0.29"],
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extras_require=extras,
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entry_points={
"console_scripts": [
"ray=ray.scripts.scripts:main",
"rllib=ray.rllib.scripts:cli [rllib]", "tune=ray.tune.scripts:cli"
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]
},
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include_package_data=True,
zip_safe=False,
license="Apache 2.0")