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* 📄 Renamed File for Better Understanding Renamed the 'rl' file to 'run_locomotion'. This change was made to improve the clarity and readability of the codebase. The 'rl' name was ambiguous, and 'run_locomotion' provides a more clear description of the file's purpose. Thanks 🙌 * 📁 [Docs] Renamed Directory for Better Clarity Renamed the 'rl' directory to 'reinforcement_learning'. This change provides a clearer understanding of the directory's purpose and its contents. * Update examples/reinforcement_learning/README.md Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * 📝 Update README --------- Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
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Overview
These examples show how to run Diffuser in Diffusers.
There are two ways to use the script, run_diffuser_locomotion.py.
The key option is a change of the variable n_guide_steps.
When n_guide_steps=0, the trajectories are sampled from the diffusion model, but not fine-tuned to maximize reward in the environment.
By default, n_guide_steps=2 to match the original implementation.
You will need some RL specific requirements to run the examples:
pip install -f https://download.pytorch.org/whl/torch_stable.html \
free-mujoco-py \
einops \
gym==0.24.1 \
protobuf==3.20.1 \
git+https://github.com/rail-berkeley/d4rl.git \
mediapy \
Pillow==9.0.0