Reinforcement Learning
ml-agents
TensorBoard
ONNX
Pyramids
deep-reinforcement-learning
ML-Agents-Pyramids
Instructions to use AnnaMats/ppo-Pyramids-Training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use AnnaMats/ppo-Pyramids-Training with ml-agents:
mlagents-load-from-hf --repo-id="AnnaMats/ppo-Pyramids-Training" --local-dir="./download: string[]s"
- Notebooks
- Google Colab
- Kaggle
| [coverage:run] | |
| omit = */tests/* | |
| [coverage:report] | |
| # Run "pytest --cov=ml-agents --cov=ml-agents-envs --cov=gym-unity" to see the current coverage percentage. | |
| # Run the above plus "--cov-report html" to get a nice visualization of what is/isn't covered in html format. | |
| fail_under = 60 | |
| [flake8] | |
| # black will apply a line length of 88 to code but not docstrings/comments | |
| # This seems like a decent compromise between readability and redoing all the docstrings. | |
| max-line-length=120 | |
| ignore = | |
| # Black tends to introduce things flake8 doesn't like, such as "line break before binary operator" | |
| # or whitespace before ':'. Rather than fight with black, just ignore these for now. | |
| W503, E203, | |
| # flake-tidy-import adds this warning, which we don't really care about for now | |
| I200, | |
| banned-modules = tensorflow = use mlagents.tf_utils instead (it handles tf2 compat). | |
| logging = use mlagents_envs.logging_util instead | |
| torch = use mlagents.torch_utils instead (handles GPU detection). | |