BipedalWalker OpenCL PPO Trainer

Note: This repository may be named python , but it is NOT a fork of the Python programming language. It is a standalone project containing an OpenCL-accelerated PPO trainer for the BipedalWalker-v3 Gymnasium environment, plus custom OpenCL kernels for neural network operations , Though text_trainer.py and setup_ocl.py needs Python.

How to Install

What this is

• PPO trainer for BipedalWalker-v3 with a custom laser hazard wrapper
• OpenCL acceleration for neural network forward/backward passes via libtorch tensors
• Tiled SGEMM kernel adapted from dlprimitives (MIT License, Artyom Beilis)
• Optional pygame rendering + ffmpeg video recording
• Config-driven hyperparameters (config.yaml)
• Optional SyncVectorEnv parallel environments
• CSV + TensorBoard logging
• Live web dashboard (dashboard_server.py) via Flask + SSE
• OpenCL cache limits configurable via opencl: section in config.yaml
• Per-update memory logging and dashboard cache stats

Key files

Build

python setup_ocl.py

Train

python text_trainer.py --train

Live dashboard

# terminal 1
python text_trainer.py --train

# terminal 2
python dashboard_server.py

# browser
http://127.0.0.1:8080

Run inference

python text_trainer.py --run

Requirements

• Python 3.12+
• PyTorch with libtorch
• OpenCL SDK / ICD
• pybind11
• gymnasium, pygame, numpy, pyyaml, psutil, flask

License

MIT — see LICENSE for details.

Attribution

Tiled SGEMM kernel adapted from dlprimitives (MIT License, Artyom Beilis).