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        "author": "Xingdong Zuo",
        "author_email": "zuoxingdong@hotmail.com",
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            "License :: OSI Approved :: MIT License",
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            "Topic :: Scientific/Engineering :: Artificial Intelligence"
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        "description": "# `dm2gym`: Convert DeepMind Control Suite to OpenAI gym environments.\n\nThis repository contains a lightweight wrapper to convert DeepMind Control Suite to OpenAI gym environments. \n\n# Installation\nOne can install directly from PyPI:\n```\npip install dm2gym\n```\nThe installation can also be done with:\n```\ngit clone https://github.com/zuoxingdong/dm2gym.git\ncd dm2gym\npip install -e .\n```\n\n# Getting started\nOne liner to create the environment:\n```python\nimport gym\nenv = gym.make('dm2gym:CheetahRun-v0')\n```\n\nMore examples to specify the environment:\n```python\nenv = gym.make('dm2gym:FishSwim-v0', environment_kwargs={'flat_observation': True})\nenv = gym.make('dm2gym:HopperHop-v0', visualize_reward=True)\n```\n\n# What's new\n- 2019-10-18 (v0.2.0)\n    - Sync to the latest API of DeepMind Control Suite\n    - Support gym registration: create all `dm_control` environments via `gym.make`\n\n- 2019-04-14 (v0.1.0)\n    - Initial release\n\n# Reference\nPlease use this bibtex if you want to cite this repository in your publications:\n\n    @misc{dm2gym,\n          author = {Zuo, Xingdong},\n          title = {dm2gym: Convert DeepMind Control Suite to OpenAI gym environments.},\n          year = {2019},\n          publisher = {GitHub},\n          journal = {GitHub repository},\n          howpublished = {\\url{https://github.com/zuoxingdong/dm2gym}},\n        }\n\n\n",
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