feat: integrate OpenPI π0.5-LIBERO inference and ROS2 evaluation - #1491
Open
Chernobyllight wants to merge 5 commits into
Open
feat: integrate OpenPI π0.5-LIBERO inference and ROS2 evaluation#1491Chernobyllight wants to merge 5 commits into
Chernobyllight wants to merge 5 commits into
Conversation
Integrate OpenPI pi0.5-LIBERO with local PyTorch inference, checkpoint conversion, runtime setup, and official single- and multi-GPU evaluation workflows.
Integrate pi0.5-LIBERO inference with local PyTorch execution, official-compatible evaluation, multi-GPU suite scheduling, and decoupled ROS2 policy/simulator nodes. Simplify the integration while preserving preprocessing, FP64 actions, and continuous policy RNG semantics.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Integrates OpenPI π0.5-LIBERO inference into LightX2V with local PyTorch execution, official-compatible evaluation, multi-GPU suite scheduling, and decoupled ROS2 policy/simulator nodes. The implementation preserves official preprocessing, FP64 action transport, and continuous policy RNG semantics.