Contents

parl 2.2.1

0

Reinforcement Learning Framework

Reinforcement Learning Framework

Stars: 3226, Watchers: 3226, Forks: 817, Open Issues: 136

The PaddlePaddle/PARL repo was created 6 years ago and the last code push was 2 weeks ago.
The project is very popular with an impressive 3226 github stars!

How to Install parl

You can install parl using pip

pip install parl

or add it to a project with poetry

poetry add parl

Package Details

Author
License
Homepage
https://github.com/PaddlePaddle/PARL
PyPi:
https://pypi.org/project/parl/
GitHub Repo:
https://github.com/PaddlePaddle/PARL

Classifiers

No  parl  pypi packages just yet.

Errors

A list of common parl errors.

Code Examples

Here are some parl code examples and snippets.

GitHub Issues

The parl package has 136 open issues on GitHub

  • train.py导入parl时报错怎么解决
  • fix core dump on aarch64
  • Bump paddlepaddle from 1.8.5 to 2.5.0 in /.teamcity
  • Bump paddlepaddle from 2.4.2 to 2.5.0 in /docs
  • Bump paddlepaddle from 2.2.0 to 2.5.0 in /examples/tutorials/parl2_dygraph
  • Bump paddlepaddle from 2.0.0 to 2.5.0 in /examples/AlphaZero
  • Bump paddlepaddle from 1.8.5 to 2.5.0 in /examples/tutorials
  • import parl时报错RuntimeError问题
  • ES单机多卡训练报错 ERR [xparl] lost connection with a job
  • 运用动态图的DDPG代码model部分报错ValueError: (InvalidArgument) The shape of input[0] and input[1] is expected to be equal.But received input[0]'s shape = [48, 8], input[1]'s shape = [48, 1, 2].
  • 运行后self.build_program()报错
  • Bump grpcio from 1.37.0 to 1.53.0
  • ppo_mujocov2
  • 使用Paddle Custom NPU训练SAC一段时间后reward一直不变
  • AttributeError: Can't pickle local object 'check_installed_framework.<locals>.check'

See more issues on GitHub

Related Packages & Articles

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A Toolkit for Reinforcement Learning in Card Games

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map and starmap implementations passing additional arguments and parallelizing if possible

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Horovod is a powerful distributed training framework for Python that allows you to train deep learning models across multiple GPUs and servers quickly and efficiently. It falls under the category of distributed computing libraries. Built on top of TensorFlow, PyTorch, and other popular deep learning frameworks, Horovod simplifies the process of scaling up your model training by handling the complexities of distributed training under the hood.