mirror of
https://github.com/Farama-Foundation/Gymnasium.git
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c364506710
* Ditch most of the seeding.py and replace np_random with the numpy default_rng. Let's see if tests pass * Updated a bunch of RNG calls from the RandomState API to Generator API * black; didn't expect that, did ya? * Undo a typo * blaaack * More typo fixes * Fixed setting/getting state in multidiscrete spaces * Fix typo, fix a test to work with the new sampling * Correctly (?) pass the randomly generated seed if np_random is called with None as seed * Convert the Discrete sample to a python int (as opposed to np.int64) * Remove some redundant imports * First version of the compatibility layer for old-style RNG. Mainly to trigger tests. * Removed redundant f-strings * Style fixes, removing unused imports * Try to make tests pass by removing atari from the dockerfile * Try to make tests pass by removing atari from the setup * Try to make tests pass by removing atari from the setup * Try to make tests pass by removing atari from the setup * First attempt at deprecating `env.seed` and supporting `env.reset(seed=seed)` instead. Tests should hopefully pass but throw up a million warnings. * black; didn't expect that, didya? * Rename the reset parameter in VecEnvs back to `seed` * Updated tests to use the new seeding method * Removed a bunch of old `seed` calls. Fixed a bug in AsyncVectorEnv * Stop Discrete envs from doing part of the setup (and using the randomness) in init (as opposed to reset) * Add explicit seed to wrappers reset * Remove an accidental return * Re-add some legacy functions with a warning. * Use deprecation instead of regular warnings for the newly deprecated methods/functions
77 lines
2.4 KiB
Python
77 lines
2.4 KiB
Python
import os.path
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import sys
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import itertools
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from setuptools import find_packages, setup
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# Don't import gym module here, since deps may not be installed
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), "gym"))
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from version import VERSION
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# Environment-specific dependencies.
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extras = {
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"atari": ["ale-py~=0.7.1"],
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"accept-rom-license": ["autorom[accept-rom-license]~=0.4.2"],
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"box2d": ["box2d-py==2.3.5", "pyglet>=1.4.0"],
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"classic_control": ["pyglet>=1.4.0"],
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"mujoco": ["mujoco_py>=1.50, <2.0"],
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"robotics": ["mujoco_py>=1.50, <2.0"],
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"toy_text": ["scipy>=1.4.1"],
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"other": ["lz4>=3.1.0", "opencv-python>=3."],
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}
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# Meta dependency groups.
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nomujoco_blacklist = set(["mujoco", "robotics", "accept-rom-license", "atari"])
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nomujoco_groups = set(extras.keys()) - nomujoco_blacklist
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extras["nomujoco"] = list(
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itertools.chain.from_iterable(map(lambda group: extras[group], nomujoco_groups))
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)
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all_blacklist = set(["accept-rom-license"])
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all_groups = set(extras.keys()) - all_blacklist
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extras["all"] = list(
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itertools.chain.from_iterable(map(lambda group: extras[group], all_groups))
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)
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setup(
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name="gym",
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version=VERSION,
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description="Gym: A universal API for reinforcement learning environments.",
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url="https://github.com/openai/gym",
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author="Gym Community",
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author_email="jkterry@umd.edu",
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license="",
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packages=[package for package in find_packages() if package.startswith("gym")],
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zip_safe=False,
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install_requires=[
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"numpy>=1.18.0",
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"cloudpickle>=1.2.0",
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"importlib_metadata>=4.8.1; python_version < '3.8'",
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],
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extras_require=extras,
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package_data={
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"gym": [
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"envs/mujoco/assets/*.xml",
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"envs/classic_control/assets/*.png",
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"envs/robotics/assets/LICENSE.md",
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"envs/robotics/assets/fetch/*.xml",
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"envs/robotics/assets/hand/*.xml",
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"envs/robotics/assets/stls/fetch/*.stl",
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"envs/robotics/assets/stls/hand/*.stl",
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"envs/robotics/assets/textures/*.png",
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]
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},
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tests_require=["pytest", "mock"],
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python_requires=">=3.7",
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classifiers=[
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.7",
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"Programming Language :: Python :: 3.8",
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"Programming Language :: Python :: 3.9",
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"Programming Language :: Python :: 3.10",
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],
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)
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