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DI-HPC: Decision Intelligence - High Performance Computation

DI-HPC is an acceleration operator component for general algorithm modules in reinforcement learning algorithms, such as GAE, n-step TD and LSTM, etc. The operators support forward and backward propagation, and can be used in training, data collection, and test modules.

Requirements

Setting 1

  • CUDA 9.2
  • PyTorch 1.5 (recommend)
  • python 3.6 or python 3.7 or python3.8
  • Linux Platform

Setting 2

  • CUDA 9.0
  • gcc 5.4.0
  • PyTorch 1.1.0
  • python 3.6 or python 3.7
  • Linux Platform

Note: We recommend that DI-HPC and DI-Engine share the same environment, and it should be fine with PyTorch from 1.1.0 to 1.10.0.

Quick Start

Install from whl

The easiest way to get DI-HPC is to use pip, and you can get .whl from

and then call

$ pip install <YOUR_WHL>

Install from source code

Alternatively you can install latest DI-HPC from git master branch:

$ python3 setup.py install

Run on Linux

You will get benchmark result by following commands:

$ python3 tests/test_gae.py

Feedback and Contribution

We appreciate all the feedbacks and contributions to improve DI-engine, both algorithms and system designs. And CONTRIBUTING.md offers some necessary information.

License

DI-hpc released under the Apache 2.0 license.

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  • Python 52.7%
  • C++ 24.4%
  • Cuda 22.2%
  • Dockerfile 0.7%