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diffusers/examples/reinforcement_learning
Tolga Cangöz 98730c5dd7 Errata (#8322)
* Fix typos

* Trim trailing whitespaces

* Remove a trailing whitespace

* chore: Update MarigoldDepthPipeline checkpoint to prs-eth/marigold-lcm-v1-0

* Revert "chore: Update MarigoldDepthPipeline checkpoint to prs-eth/marigold-lcm-v1-0"

This reverts commit fd742b30b4.

* pokemon -> naruto

* `DPMSolverMultistep` -> `DPMSolverMultistepScheduler`

* Improve Markdown stylization

* Improve style

* Improve style

* Refactor pipeline variable names for consistency

* up style
2024-06-05 13:59:09 -07:00
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2024-06-05 13:59:09 -07:00

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