keras-rl2 | Reinforcement learning with tensorflow 2 keras | Machine Learning library
kandi X-RAY | keras-rl2 Summary
kandi X-RAY | keras-rl2 Summary
keras-rl2 is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras applications. keras-rl2 has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install keras-rl2' or download it from GitHub, PyPI.
keras-rl2 implements some state-of-the art deep reinforcement learning algorithms in Python and seamlessly integrates with the deep learning library Keras. Furthermore, keras-rl2 works with OpenAI Gym out of the box. This means that evaluating and playing around with different algorithms is easy. Of course you can extend keras-rl2 according to your own needs. You can use built-in Keras callbacks and metrics or define your own. Even more so, it is easy to implement your own environments and even algorithms by simply extending some simple abstract classes. Documentation is available online.
keras-rl2 implements some state-of-the art deep reinforcement learning algorithms in Python and seamlessly integrates with the deep learning library Keras. Furthermore, keras-rl2 works with OpenAI Gym out of the box. This means that evaluating and playing around with different algorithms is easy. Of course you can extend keras-rl2 according to your own needs. You can use built-in Keras callbacks and metrics or define your own. Even more so, it is easy to implement your own environments and even algorithms by simply extending some simple abstract classes. Documentation is available online.
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keras-rl2 has a low active ecosystem.
It has 156 star(s) with 55 fork(s). There are 6 watchers for this library.
It had no major release in the last 12 months.
There are 15 open issues and 5 have been closed. On average issues are closed in 32 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of keras-rl2 is 1.0.5
Quality
keras-rl2 has no bugs reported.
Security
keras-rl2 has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
keras-rl2 is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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keras-rl2 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.
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keras-rl2 Key Features
No Key Features are available at this moment for keras-rl2.
keras-rl2 Examples and Code Snippets
ValueError: Input 0 of layer "max_pooling2d" is incompatible with the layer: expected ndim=4, found ndim=5. Full shape received: (None, 3, 51, 39, 32)
Python
Lines of Code : 48License : Strong Copyleft (CC BY-SA 4.0)
Lines of Code : 48License : Strong Copyleft (CC BY-SA 4.0)
Copyfrom tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Flatten, Convolution2D, MaxPooling2D, Activation
from tensorflow.keras.optimizers import Adam
input_shape = (3, 210, 160, 3)
model = Sequential()
mCommunity Discussions
Trending Discussions on keras-rl2
QUESTION
FailedPreconditionError while using DDPG RL algorithm, in python, with keras, keras-rl2
Asked 2021-Jun-10 at 07:00
I am training a DDPG agent on my custom environment that I wrote using openai gym. I am getting error during training the model.
When I search for a solution on web, I found that some people who faced similar issue were able to resolve it by initializing the variable.
...ANSWER
Answered 2021-Jun-10 at 07:00For now I was able to solve this error by replacing the imports from keras with imports from tensorflow.keras, although I don't know why keras itseld doesn't work
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install keras-rl2
Install Keras-RL2 from Pypi (recommended):
Install from Github source:
Install from Github source:
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For any new features, suggestions and bugs create an issue on GitHub.
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