- Copy openarm_bimanual_pybullet.urdf and all referenced STL/DAE meshes
into src/lerobot/robots/openarms/urdf/
- Update openarms_follower.py to prefer the bundled URDF over the
external ~/Documents/openarm_description path
- Includes visual and collision meshes for arm, body, and end-effector
- Force-add .stl and .urdf files past .gitignore
The previous implementation had a double-normalization bug: the
preprocessor normalized actions with absolute stats, then
convert_to_relative subtracted normalized state (wrong), then the
per-timestep normalizer re-normalized.
Now the correct flow is:
1. Convert batch to relative on raw data (before preprocessing)
2. Compute global relative stats (mean/std across all timesteps)
3. Hotswap the preprocessor normalizer to use relative stats
4. Preprocessor normalizes relative values correctly
This brings loss from ~3000+ down to ~0.5, matching the main branch.
Made-with: Cursor
When rename_map maps a dataset key to observation.state, the raw
dataset used for stats computation still has the original key.
Reverse the rename_map to find the correct key.
Made-with: Cursor
* pi fixes for dependencies
* add walls sarm conflict
* also add conflicts for pi
* fix(ci): use --extra all instead of --all-extras + --no-extra
---------
Co-authored-by: Steven Palma <steven.palma@huggingface.co>
* support wallx
* fix bugs in flow
* incorporate wallx model into lerobot
* update the policy methods
* reduce to least config and params & pass lerobot basic test
* fixed dtype bugs
* add wallx dependencies
* update
* remove flash-attn requirement && fix bug in inference and fast mode
* fix bug for inference
* add some small modifications
* fix pre-commit errors
* remove lerobot[wallx]
* fix ci
* fix precommit issues
* fix: exclude wallx extra properly in CI workflows
* fix: add uv conflicts for wallx transformers version
* fix: peft test import
* pre-commit
* only export WallXConfig from wall_x package to avoid peft import in CI
* remove torch dep
* precommit
* add import
---------
Co-authored-by: vincentchen <chenlufang@x2robot.com>
Co-authored-by: Geoffrey19 <sympathischmann35@gmail.com>
Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>
Co-authored-by: Pepijn <pepijn@huggingface.co>
* fix(optim): enable and resolve mypy type errors
Resolves#1729
build(deps): add mypy as dependency and update pre-commit hook
* change build's type annotation
* add initial modeling
* make rewind pretrained policy
* add annotation
* small fix
* add sarm
* subtasks
* fix spawn
* fix rewind discrepancies
* Add script to generate embedding for dataset (#2138)
* Add generate and validate script
* fix precommit
* Improve generate embeddings function by using dataset tools (#2206)
---------
Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co>
* cleanup
* change order train log
* print batch size
* update sarm processor
* add reward output
* change expected features
* add image validation
* change validation
* get state input from dataset stats
* raise if no state key is found
* pass stats
* cleanup and refactor
* add episode inddex to complementary data
* add subtask init and detection
* revert lerobot_train changes
* pass dataset metadata to policy
* change loadig subtasks
* add small logging
* fix progress conversion and adding initial frame
* use large offset for initial frame (ugly)
* Remove rewind, use clip tokenizer
* add tests, implement formula 1,2 correctly and cleanup
* use task from dataset, cleanup visualizer
* simplify
* simplify and cleanup code and move compute_temporal_proportions to utils
* fix normalization in visualization
* Fix visualization and change prompt
* fix formatting
* add visualize subtask annotations
* use qwen thinking
* try different prompt
* format
* update prompt
* higher temp, long output
* different settings
* use instruct
* show full resp
* split message
* Temp: increase tolerance dataset
* Fix RA-BC (#2572)
* Add next observation loading for RA-BC progress deltas
* Compute weights based on temporal progress deltas instead of static rewards
* Add hard-masking for negative progress deltas in weight computation
* Feat/add dual head (#2582)
* Add dual dense sparse head and annotation
* Add docs
* add dual to procesor
* cleanup
* change sampling in visualize and cleanup
* remove validation
* remove compile
* Feat/test uniform (#2587)
* test uniform
* add different string for misaligned
* Fix rewind and add tests
* uncomment text implementation
* run precommit
* Add head mode for ra-bc
* fix visalization of single task
* add
* return per sample loss
* Fix RA_BC (#2602)
* update rabc implementation
* compute rabc beforehand
* fix import
* add only progress calulation
* use precomputed progress
* multi gpu processing
* import
* fix dataset meta data extraction
* add logging
* logging
* log
* progress per episode
* split differently
* move clip to gpu
* pre decode frames for an episode
* fix cuda initalization
* fix import
* multi processing
* rename
* fix import
* fix
* fix rabc
* use last known progress if oob
* use last known progress if oob
* add misalignment loss with random embeddings
* discard previous changes
* add selection of models to docs for ra_bc
* add transformers dep
* extend tolerance
* initial commit with new codebase
* add tests
* fix
* remove temporal sampler
* drop last frame for sampler
* use original ref
* some fixes
* fix visualization
* remove smoothing and fix order subtasks
* add stride rabc computation
* add push to hub
* add explanation
* add kappa expllaination
* better rabc logging
* feedback pr
* remove dataset tolerance
* revert dataset tool
* revert dataset changes
* add credit
* run precommit
* change path for generate ra_bc
* fix type
* include sarm in all in pyproject
* fix precommit
* lazy import matplotlib
* lazy import qwen
* remove rich console
* skip if transformers is not installed?
* run only when we have faker
* place transformer lazy loading
* Dont test if low transformer version
* fix
* increase transformer
* increase as 4.57.0 is yanked
* remove pi from all
* go back
---------
Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co>
Co-authored-by: s1lent4gnt <kmeftah.khalil@gmail.com>
