gym | A toolkit for developing and comparing reinforcement | Reinforcement Learning library

 by   openai Python Version: 0.26.2 License: Non-SPDX

kandi X-RAY | gym Summary

kandi X-RAY | gym Summary

gym is a Python library typically used in Artificial Intelligence, Reinforcement Learning applications. gym has no bugs, it has no vulnerabilities, it has build file available and it has medium support. However gym has a Non-SPDX License. You can install using 'pip install gym' or download it from GitHub, PyPI.

Gym is an open source Python library for developing and comparing reinforcement learning algorithms by providing a standard API to communicate between learning algorithms and environments, as well as a standard set of environments compliant with that API. Since its release, Gym's API has become the field standard for doing this.
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            kandi-support Support

              gym has a medium active ecosystem.
              It has 32193 star(s) with 8474 fork(s). There are 1041 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 55 open issues and 1712 have been closed. On average issues are closed in 54 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of gym is 0.26.2

            kandi-Quality Quality

              gym has 0 bugs and 0 code smells.

            kandi-Security Security

              gym has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              gym code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              gym has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              gym releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              gym saves you 5494 person hours of effort in developing the same functionality from scratch.
              It has 13639 lines of code, 885 functions and 151 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed gym and discovered the below as its top functions. This is intended to give you an instant insight into gym implemented functionality, and help decide if they suit your requirements.
            • Reset the game
            • Render the widget
            • Destroy the moon
            • Move wind to center
            • Resets the game
            • Step the mesh
            • Generate random clouds
            • Destroy the world
            • Reset the speaker
            • Move the robot
            • Forward the wheels
            • Creates a particle
            • Reset all environments
            • Perform a single action
            • Perform a single step
            • Wait for the action to finish
            • Wait for the child pipe to finish
            • Return a tuple of lower and high bounds
            • Run a single action
            • Calculate a single action
            • Performs an action on the cartesian system
            • Step in the mesh
            • Render the image
            • Render the scene
            • Helper function for worker functions
            • Register an entry point
            • Step the robot
            • Load Gym environment plugins
            Get all kandi verified functions for this library.

            gym Key Features

            No Key Features are available at this moment for gym.

            gym Examples and Code Snippets

            copy iconCopy
            from mlagents_envs.environment import UnityEnvironment
            from mlagents_envs.envs import UnityToGymWrapper
            from baselines.common.vec_env.subproc_vec_env import SubprocVecEnv
            from baselines.common.vec_env.dummy_vec_env import DummyVecEnv
            from baselines.b  
            copy iconCopy
            pip install git+git://github.com/openai/baselines
            
            import gym
            
            from baselines import deepq
            from baselines import logger
            
            from mlagents_envs.environment import UnityEnvironment
            from mlagents_envs.envs.unity_gym_env import UnityToGymWrapper
            
            
            def main(  
            Unity ML-Agents Gym Wrapper-Run Google Dopamine Algorithms-Hyperparameters
            C#dot img3Lines of Code : 32dot img3License : Non-SPDX (NOASSERTION)
            copy iconCopy
            import dopamine.agents.rainbow.rainbow_agent
            import dopamine.unity.run_experiment
            import dopamine.replay_memory.prioritized_replay_buffer
            import gin.tf.external_configurables
            
            RainbowAgent.num_atoms = 51
            RainbowAgent.stack_size = 1
            RainbowAgent.vmax   
            nupic - run-opf-clients-hotgym-prediction-one gym
            Pythondot img4Lines of Code : 99dot img4License : Non-SPDX (GNU Affero General Public License v3.0)
            copy iconCopy
            # ----------------------------------------------------------------------
            # Numenta Platform for Intelligent Computing (NuPIC)
            # Copyright (C) 2013, Numenta, Inc.  Unless you have an agreement
            # with Numenta, Inc., for a separate license for this soft  
            Play a Gym experiment .
            pythondot img5Lines of Code : 30dot img5no licencesLicense : No License
            copy iconCopy
            def main():
              env = gym.make('CartPole-v0')
              ft = FeatureTransformer(env)
              model = Model(env, ft)
              gamma = 0.99
            
              if 'monitor' in sys.argv:
                filename = os.path.basename(__file__).split('.')[0]
                monitor_dir = './' + filename + '_' + str(date  
            Initialize the gym .
            pythondot img6Lines of Code : 14dot img6no licencesLicense : No License
            copy iconCopy
            def __init__(self, env, k):
                    """Stack k last frames.
            
                    Returns lazy array, which is much more memory efficient.
            
                    See Also
                    --------
                    baselines.common.atari_wrappers.LazyFrames
                    """
                    gym.Wrapper.__init  
            Keras: AttributeError: 'Adam' object has no attribute '_name'
            Pythondot img7Lines of Code : 34dot img7License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            # !pip install keras-rl2
            import tensorflow as tf
            from keras.layers import Dense, Flatten
            import gym
            from rl.agents.dqn import DQNAgent
            from rl.policy import BoltzmannQPolicy
            from rl.memory import SequentialMemory
            
            env = gym.make('CartPole-
            Extracting specific JSON values in python
            Pythondot img8Lines of Code : 5dot img8License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            auth_response = requests.get(link, headers=header)
            items = auth_response.json()['tracks']['items']
            for d in items:
                print(d)
            
            Extracting specific JSON values in python
            Pythondot img9Lines of Code : 9dot img9License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            auth_response = requests.get(link, headers=header)
            for d in auth_response:
            
            auth_response = requests.get(link, headers=header)
            decoded_auth_response = json.loads(auth_response)
            data_by_user = {}
            for d in decoded_aut
            AttributeError: 'TaxiEnv' object has no attribute 's'
            Pythondot img10Lines of Code : 6dot img10License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            import gym
            
            env = gym.make("Taxi-v3")
            env.reset()
            env.render()
            

            Community Discussions

            QUESTION

            Keras: AttributeError: 'Adam' object has no attribute '_name'
            Asked 2022-Apr-16 at 15:05

            I want to compile my DQN Agent but I get error: AttributeError: 'Adam' object has no attribute '_name',

            ...

            ANSWER

            Answered 2022-Apr-16 at 15:05

            Your error came from importing Adam with from keras.optimizer_v1 import Adam, You can solve your problem with tf.keras.optimizers.Adam from TensorFlow >= v2 like below:

            (The lr argument is deprecated, it's better to use learning_rate instead.)

            Source https://stackoverflow.com/questions/71894769

            QUESTION

            How to split a column and assign values to different specific columns in pandas?
            Asked 2022-Apr-04 at 07:11

            I have a dataframe that looks like this:

            ...

            ANSWER

            Answered 2022-Apr-04 at 05:01

            for this you can use regex and split function to split the 1 column into 2.

            Source https://stackoverflow.com/questions/71732160

            QUESTION

            How do you swap a component with another after onclick event?
            Asked 2022-Apr-03 at 03:46

            Below, I have a code that is eventually rendered as a route in a react, single page, app. What I was hoping to get, was that depending on what div was clicked, each applying a 'filter', that the component variable, will change components, based off what was imported.

            ...

            ANSWER

            Answered 2022-Apr-02 at 02:02

            You're tripping up on the way you're using your component variable. You don't want to re-declare the variable, you just want to assign a new value

            Source https://stackoverflow.com/questions/71714279

            QUESTION

            I wanna use this pie chart but how to I change background color from white to grey
            Asked 2022-Mar-30 at 17:35

            I wanna use this pie chart but how to I change background color from white to grey (rgb(226, 226, 226)). Is it even possible? The pie chart is from https://www.w3schools.com/howto/tryit.asp?filename=tryhow_google_pie_chart.

            ...

            ANSWER

            Answered 2022-Mar-30 at 17:35

            I just added the backgroundcolor to the draw option backgroundColor: { fill: "#e2e2e2" }

            Source https://stackoverflow.com/questions/71681641

            QUESTION

            OpenAI-Gym and Keras-RL: DQN expects a model that has one dimension for each action
            Asked 2022-Mar-02 at 10:55

            I am trying to set a Deep-Q-Learning agent with a custom environment in OpenAI Gym. I have 4 continuous state variables with individual limits and 3 integer action variables with individual limits.

            Here is the code:

            ...

            ANSWER

            Answered 2021-Dec-23 at 11:19

            As we talked about in the comments, it seems that the Keras-rl library is no longer supported (the last update in the repository was in 2019), so it's possible that everything is inside Keras now. I take a look at Keras documentation and there are no high-level functions to build a reinforcement learning model, but is possible to use lower-level functions to this.

            • Here is an example of how to use Deep Q-Learning with Keras: link

            Another solution may be to downgrade to Tensorflow 1.0 as it seems the compatibility problem occurs due to some changes in version 2.0. I didn't test, but maybe the Keras-rl + Tensorflow 1.0 may work.

            There is also a branch of Keras-rl to support Tensorflow 2.0, the repository is archived, but there is a chance that it will work for you

            Source https://stackoverflow.com/questions/70261352

            QUESTION

            gym package not identifying ten-armed-bandits-v0 env
            Asked 2022-Feb-08 at 08:01

            Environment:

            • Python: 3.9
            • OS: Windows 10

            When I try to create the ten armed bandits environment using the following code the error is thrown not sure of the reason.

            ...

            ANSWER

            Answered 2022-Feb-08 at 08:01

            It could be a problem with your Python version: k-armed-bandits library was made 4 years ago, when Python 3.9 didn't exist. Besides this, the configuration files in the repo indicates that the Python version is 2.7 (not 3.9).

            If you create an environment with Python 2.7 and follow the setup instructions it works correctly on Windows:

            Source https://stackoverflow.com/questions/70858340

            QUESTION

            Error in importing environment OpenAI Gym
            Asked 2022-Jan-10 at 09:43

            I am trying to run an OpenAI Gym environment however I get the following error:

            ...

            ANSWER

            Answered 2021-Oct-05 at 01:37

            Code works for me with gym 0.18.0 and 0.19.0 but not with 0.20.0

            You may downgrade it with

            Source https://stackoverflow.com/questions/69442971

            QUESTION

            fastlane getting CommandPhaseScript execution error
            Asked 2022-Jan-04 at 12:59

            Hey guys is my first time when I use fastlane and after I've managed to configure fastlane successfully I ran 'fastlane beta' in my iOS folder and got into this error after 10 minutes of processing

            ...

            ANSWER

            Answered 2022-Jan-04 at 12:59

            I have managed to solve this problem by creating a fastlane folder in the root folder of my react-native project and inside that I have initiated the fastlane command. Before I used to have the fastlane folder inside iOS folder.

            Now the folder structure looks like this

            • Root
              • android
              • ios
              • fastlane
                • Appfile
                • Fastfile
                • Gemfile
                • Gymfile

            Source https://stackoverflow.com/questions/70392325

            QUESTION

            OpenAI Gym - AttributeError: module 'contextlib' has no attribute 'nullcontext'
            Asked 2021-Nov-10 at 09:22

            I'm running into this error when trying to run a command from docker a docker container on google compute engine.

            Here's the stacktrace:

            ...

            ANSWER

            Answered 2021-Oct-12 at 03:26

            It seems like this is an issue with python 3.6 and gym. Upgrading my container to python 3.7 fixed the issue.

            Source https://stackoverflow.com/questions/69520829

            QUESTION

            Prettier - new line between function and comment
            Asked 2021-Oct-25 at 12:11

            I would like to know if there's a rule to add a new line between function/statement and comment in typescript with prettier (.prettierrc at the root of the project).

            Current behaviour:

            ...

            ANSWER

            Answered 2021-Oct-25 at 09:57

            No, prettier doesn't have that rule.

            Prettier has a sparse list of options by design, and this isn't one of'm.

            Source https://stackoverflow.com/questions/69705929

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install gym

            To install the base Gym library, use pip install gym. This does not include dependencies for all families of environments (there's a massive number, and some can be problematic to install on certain systems). You can install these dependencies for one family like pip install gym[atari] or use pip install gym[all] to install all dependencies. We support Python 3.7, 3.8, 3.9 and 3.10 on Linux and macOS. We will accept PRs related to Windows, but do not officially support it.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
            Find more information at:

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            https://github.com/openai/gym.git

          • CLI

            gh repo clone openai/gym

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            git@github.com:openai/gym.git

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