Commit Graph

8 Commits

Author SHA1 Message Date
Steven Palma df0763a2bc feat(dependencies): minimal default tag install (#3362) 2026-04-12 20:03:04 +02:00
Pepijn 15934d8d08 feat(policies): add relative action support for pi0, pi0.5, and pi0_fast (#2970)
* Add option for pi family models to train with relative actions (relative to state)

* formatting

* add recomputation of stats and option to compute delta stats

* normalzie after delta conversion

* only recompute state for stats

* calulate chunk based stats

* sample 100k

* load from parquet

* sample 1m

* stats per chunck

* fix

* use quantiles

* stats for entire dataset

* fix

* max 1m frames

* compute before dist

* fix multi gpu processor bug

* Fix RTC with delta actions and OpenArms motor_type wiring

* feat: align pi0_fast delta actions with pi0/pi05 and add RTC integration tests

- Add delta_exclude_joints and action_feature_names to PI0FastConfig
- Move to_absolute_actions from modeling to processor pipeline for pi0_fast
- Add delta action detection and logging to eval_with_real_robot.py
- Add delta actions documentation to pi0 and pi05 READMEs
- Fix ruff lint issues in test_delta_actions.py
- Add test_rtc_delta_actions.py (24 tests) covering:
  - ActionQueue with delta vs absolute actions
  - RTC denoise step with delta leftovers
  - Full pipeline roundtrip (delta → RTC → absolute)
  - State rebasing approximation bounds
  - Non-delta policy compatibility
  - Multi-chunk consistency

* chore: clean up test comments, add OpenPI attribution, remove debug logging

- Replace decorative comment separators in test files with plain section headers
- Add attribution comments for 1e-6 epsilon in normalize_processor.py (from OpenPI)
- Remove debug logging blocks from lerobot_train.py

* refactor: extract compute_delta_action_stats into compute_stats.py

Move the ~70-line inline delta action stats block from lerobot_train.py
into a dedicated function in compute_stats.py, where all other stats
computation already lives. The training script now calls it in 6 lines.

* refactor: remove unused get_processed_left_over from ActionQueue

This method was never called outside of tests. Leftover actions for RTC
guidance are always retrieved via get_left_over() (delta/original space).

* revert: remove logging-only changes from eval_with_real_robot.py

The delta actions detection helper and log message added no functional
value — the script already handles delta policies correctly via the
processor pipeline.

* refactor: use ACTION/OBS_STATE constants instead of hardcoded strings

Replace hardcoded "action" and "observation.state" with ACTION and
OBS_STATE from utils.constants in compute_stats.py, dataset_tools.py,
and lerobot_train.py.

* style: remove stray blank lines in training loop

* refactor: move delta action stats to preprocessing step, remove on-the-fly computation

- Remove on-the-fly compute_delta_action_stats from lerobot_train.py
- Rewrite recompute_stats to delegate action stats to compute_delta_action_stats
  (chunk-based sampling matching what the model sees during training)
- Add chunk_size parameter to recompute_stats for delta action computation
- Add delta actions documentation to pi0.mdx and pi05.mdx

* feat: add recompute_stats CLI operation to lerobot-edit-dataset

* fix(tests): relax quantile normalization test tolerance for 1e-6 epsilon

* chore: remove agents_memory/pr_details.md from repo

* refactor: rename delta actions to relative actions throughout

What OpenPI calls "DeltaActions" is actually UMI's "relative trajectory"
representation: each action in the chunk is an offset from the current
state, not from the previous action. This avoids error accumulation.

Renamed across all source, tests, docs, and CLI:
- DeltaActionsProcessorStep → RelativeActionsProcessorStep
- to_delta_actions → to_relative_actions
- use_delta_actions → use_relative_actions
- delta_exclude_joints → relative_exclude_joints
- compute_delta_action_stats → compute_relative_action_stats
- delta_action_processor.py → relative_action_processor.py
- test_delta_actions.py → test_relative_actions.py

Kept as-is: AbsoluteActionsProcessorStep (converts TO absolute),
registry ID "delta_actions_processor" (backward compat), and unrelated
delta references (IK pipeline, Robosuite, RA-BC metrics, gym envs).

* docs: add Action Representations guide

Dedicated page explaining absolute, relative, and delta actions with
numerical examples, joint vs EE space, and how to use kinematics
pipelines and the relative action processor. References UMI paper
(Chi et al., 2024) for the terminology.

* docs: remove redundant OpenPI naming note from action representations

* docs: remove opinionated OpenPI reference from delta actions section

* docs: replace ASCII diagram with UMI paper figure

* docs: remove OpenPI reference from action representations

* docs: use HF-hosted image instead of local asset

* docs: clarify figure attribution

* revert: restore original normalization epsilon behavior

The 1e-6 unconditional epsilon change perturbed all normalized values,
breaking backward compatibility tests. The original approach (1e-8 eps
for MEAN_STD, conditional torch.where for QUANTILES) already handles
division by zero correctly without affecting non-degenerate cases.

* fix: restore delta_action_processor.py used by phone/RL teleop

The rename commit incorrectly deleted delta_action_processor.py and
duplicated its classes into relative_action_processor.py. Restore the
original file and import from it instead.

* fix(processor): address PR #2970 review comments

- Remove shebang from relative_action_processor.py (library module, not script)
- Add device alignment in to_relative_actions/to_absolute_actions so _last_state
  on CPU doesn't cause cross-device errors when actions are on CUDA
- Rename delta_step → relative_step in AbsoluteActionsProcessorStep for naming
  consistency; update factory.py, all processor files, and tests
- Expand _reconnect_relative_absolute_steps docstring to explain why post-hoc
  rewiring is needed after deserialization
- Fix off-by-one in compute_stats.py: sample_upper_bound = total_frames - chunk_size + 1
  so last valid start index is included and total_frames == chunk_size is not rejected
- Remove redundant NOTE comment in processor_pi05.py (duplicated two lines below)
- Fix pi0_fast processor ordering: move relative_step before NormalizerProcessorStep
  so normalizer sees delta actions (matching pi0/pi05); flip postprocessor to
  unnormalize → absolute accordingly. Relative stats are now required for all pi models
- Revert use_relative_joint_actions_aloha → use_delta_joint_actions_aloha in
  configuration_smolvla.py (preserve existing public API)
- Update action_representations.mdx: add missing joint to 6-DOF example, fix
  'based on a figure', clarify pi family ordering, add RTC compatibility section

* update rtc link

* feat: compute relative action stats over full dataset with optional parallelism

Remove the 100k sample cap from compute_relative_action_stats and process
all valid chunks. Vectorize with numpy (pre-load actions/states, fancy
indexing + broadcasting) for a large speedup over the per-index HF dataset
loop. Add num_workers param for thread-based parallelism (numpy releases
the GIL). Update docs to show --push_to_hub for recompute_stats.

* style: apply ruff formatting to compute_stats.py

* testing on real robot

* style: fix ruff format and remove redundant .keys() calls
2026-04-01 12:59:12 +02:00
Steven Palma a4c66e530b chore(docs): remove pi installation note (#3095) 2026-03-06 15:52:54 +01:00
Steven Palma 5f15232271 chore: remove usernames + use entrypoints in docs, comments & sample commands (#2988) 2026-02-18 22:46:12 +01:00
arya 9701b9c273 feat(pi0): add train_expert_only and freeze_vision_encoder flags to pi0 and pi0.5 (#2727)
* feat(pi0): add train_expert_only and freeze_vision_encoder options

* pi_05: train_expert_only and freeze_vision_encoder flags

* comment clean up

* docs: add finetuning parameters to pi0 and pi05 docs

* updating docs to follow standards
2025-12-31 15:54:28 +01:00
Steven Palma d1548e1d13 docs(install): imrpove groot and libero installation instructions (#2314) 2025-10-26 15:37:41 +08:00
Pepijn a4bed41132 Improve docs pi (#2110)
* Improve docs and add numpy to pi install requirments

* fix formatting

* update command

* remvoe numpy dep
2025-10-03 12:06:18 +02:00
Pepijn abde7be3b3 Add OpenPi, Pi0 and Pi0.5 (#1910)
* initial commit

* change device in test

* do detailed import

* adhere to python 3.11 syntax

* fix autodocstring

* additionally

* do same in other files

* add model. prefix to all keys in state dict

* use dummy stats

* add pi05

* also shorten action_steps

* fix test

* all test pass! and fix tokenizer max length between 05 and 0

* remove test

* fix transformer dependency

* fix test

* split pi0 and pi05 policy in seperate files

* fix test

* fix push to hub test

* add some comments, license and readme

* remove warning in config

* add pi05 to factory

* remove check

* rename action_horizon to chunk_size

* clean up padding of state and action (more in line with lerobot pi0)

* add openpi image transforms for training and add more flexibility to _preprocess_images similar to lerobot pi0

* fix key match from pytorch state dict (similar keys to openpi implementation now)

* also for pi05

* update to python 3.11

* revert to openpi transformer replace python 3.11

* fix(modeling pi0): nit  warning message

* use safeauto_docstring

* fix: remove unused param

* fix from pretrained

* add preprocess tests

* also compile forward method

* Do not add model prefix to normalization

* use same name for action and state dim as lerobot pi0 and remove fixed image keys

* load from pretrained_path

* temp: hardcode base model

* fix override self.pretrained_path = None overwrite

* rename to loss

* remove additional image augmentations, lerobot dataset already does this

* Add docs

* put tests in test folder

* Add test to instatiate all base models

* go back to python 3.10

* update docs

* adapt docs pi05

* change docs: finetune base model options

* minor docs fixes and dependencies

* remove todo

* cast float64 to float32 for mps

* skip if no transformers

* fix tests

* add new models to modelcard

* add back init

* fix circular input

* feat: only run pi test on GPU

* remove require_nightly_gpu

* replace decorator test_pi0_openpi

* rename action_dim, state_dim to max_action_dim, max_state_dim

* fix doc and constants

* cleanup tests

* fix from pretrained

* fix tests

* add comment pi0 pi05 tests, add image features to pi0 pi05 hub tests

* fix, state is included in language not in flow head

* Move test to specific folder

* and paligemma task with newline

* remove add_special_tokens, not needed

* feedback pr

* Remove previous pi0 and rename pi0_openpi and pi05_openpi

* Add Quantile stats to LeRobotDataset (#1985)

* - Add RunningQuantileStats class for efficient histogram-based quantile computation
- Integrate quantile parameters (compute_quantiles, quantiles) into LeRobotDataset
- Support quantile computation during episode collection and aggregation
- Add comprehensive function-based test suite (24 tests) for quantile functionality
- Maintain full backward compatibility with existing stats computation
- Enable configurable quantiles (default: [0.01, 0.99]) for robust normalization

* style fixes, make quantiles computation by default to new datasets

* fix tests

* - Added DEFAULT_QUANTILES=[0.01, 0.10, 0.50, 0.90, 0.99] to be computed for each features instead of being chosen by the user
- Fortified tests.

* - add helper functions to reshape stats
- add missing test for quantiles

* - Add QUANTILE normalization mode to normalize the data with the 1st and 99th percentiles.
- Add QUANTILE10 normalization mode to normalize the data with the 10th and 90th percentiles.

* style fixes

* Added missing lisence

* Simplify compute_stats

* - added script `augment_dataset_quantile_stats.py` so that we can add quantile stats to existing v3 datasets that dont have quatniles
- modified quantile computation instead of using the edge for the value, interpolate the values in the bin

* rename pi0/pi05 files

* Remove open pi patch and use custom transformer branch for now

* renaming

* fix

* Revert "fix"

This reverts commit 1ea65730ac.

* fix naming

* feet(pi0/pi0.5): add pipeline (#2009)

* feat(processor): convert openpi model with processor

* TODO: Make test works

* fix(modeling_pi0openpi): update attention mask value and time scaling; improve task handling in tests

- Changed the attention mask value from `self.config.attention_mask_value` to a fixed value of `-2.3819763e38`.
- Updated time scaling in the `sample_noise` method to use a constant factor of `0.999` and an offset of `0.001`.
- Enhanced task handling in tests to ensure proper formatting and batch size consistency.
- Cleaned up commented-out test code for clarity.

* refactor(pi0): rename PI0OpenPIConfig and PI0OpenPIPolicy to PI0Config and PI0Policy

- Updated imports and references throughout the codebase to reflect the new naming convention.
- Introduced a new processor file for PI0 to handle pre-processing and post-processing steps.
- Adjusted tests to utilize the renamed classes, ensuring consistency and functionality.
- Enhanced clarity and maintainability by removing outdated naming conventions.

* refactor(pi05): rename PI0OpenPIPolicy to PI0Policy and update configuration

- Renamed `PI0OpenPIPolicy` to `PI0Policy` for consistency with naming conventions.
- Updated the `PI05OpenPIConfig` to include a new `tokenizer_max_length` attribute and changed the normalization mode for state from `MEAN_STD` to `QUANTILES`.
- Simplified model initialization in `PI05OpenPIPolicy` by removing unused `dataset_stats` parameter.
- Added a new processor class for `Pi05PrepareStateTokenizerProcessorStep` with `@dataclass` for improved readability.
- Introduced a test script to compare the integration of the PI0OpenPI policy with the original implementation, ensuring local testing compatibility.

* feat(processor): convert openpi model with processor

* TODO: Make test works

* fix(modeling_pi0openpi): update attention mask value and time scaling; improve task handling in tests

- Changed the attention mask value from `self.config.attention_mask_value` to a fixed value of `-2.3819763e38`.
- Updated time scaling in the `sample_noise` method to use a constant factor of `0.999` and an offset of `0.001`.
- Enhanced task handling in tests to ensure proper formatting and batch size consistency.
- Cleaned up commented-out test code for clarity.

* refactor(pi0): rename PI0OpenPIConfig and PI0OpenPIPolicy to PI0Config and PI0Policy

- Updated imports and references throughout the codebase to reflect the new naming convention.
- Introduced a new processor file for PI0 to handle pre-processing and post-processing steps.
- Adjusted tests to utilize the renamed classes, ensuring consistency and functionality.
- Enhanced clarity and maintainability by removing outdated naming conventions.

* refactor(pi05): rename PI0OpenPIPolicy to PI0Policy and update configuration

- Renamed `PI0OpenPIPolicy` to `PI0Policy` for consistency with naming conventions.
- Updated the `PI05OpenPIConfig` to include a new `tokenizer_max_length` attribute and changed the normalization mode for state from `MEAN_STD` to `QUANTILES`.
- Simplified model initialization in `PI05OpenPIPolicy` by removing unused `dataset_stats` parameter.
- Added a new processor class for `Pi05PrepareStateTokenizerProcessorStep` with `@dataclass` for improved readability.
- Introduced a test script to compare the integration of the PI0OpenPI policy with the original implementation, ensuring local testing compatibility.

* refactor(pi05): update imports and rename configuration classes

- Changed imports to reflect the new naming convention for PI05 configuration and policy classes.
- Renamed `PI05OpenPIConfig` to `PI05Config` and `PI05OpenPIPolicy` to `PI05Policy` for consistency.
- Introduced a new processor file for PI05, implementing pre-processing and post-processing steps.
- Updated tests to utilize the renamed classes, ensuring functionality and consistency across the codebase.

* update(pi05): increase tokenizer_max_length for improved processing

- Changed the `tokenizer_max_length` from 48 to 200 to enhance the model's capability in handling longer sequences.
- This adjustment aims to improve the overall performance and flexibility of the PI05 configuration.

* add default for state (max_state_dim)

* correct naming

* fix import

* cleanup code

* remove unused test

* us quantiles for action

* move to device

* remove discrete state assert

* fix pi05 test

* move pi05 to device

* use base models in comparison tests

* small renames for tests

* change number of tokens pi05 test

* fix openpi tokenization in test

* fix hub test

* fix test

* assert lerobot vs openpi tests

---------

Co-authored-by: Pepijn <pepijn@huggingface.co>

* add headers

* add back previously removed imports

* update if statement load processor with dataset stats

* remove to avoid circular import

* inject dataset stats for pretrained models

* check normalization before applying

* add link to  quantile augument script

* fix(policies): transformers import for ci in PI0 & PI05 (#2039)

* fix(policies): transformers import for ci in PI0

* fix(policies): transformers import for ci in PI05

* test(processor): fix expected raise when normalization types are missing (#2040)

* switch normalization order pipeline for pi05

* Fix/quantiles script (#2064)

* refactor augment stats with quantiles script
add parallelization for faster processing
shift the quantile normalization between -1 1

* fix replay buffer tests

* fix comment

* overwrite the pipeline normalization features with the policy features

* remove double normalization overwrite

* cleanup from pretrained

* remove typo

* also set norm_map

* fix(augment_quantiles) images incorrectly divided by 255

* clamp quantiles

* link to lerobot base models

* rename tests

* encorperate PR feedback

* update docstring for RunningQuantileStats

* update doc links

* Revert "clamp quantiles"

This reverts commit 172207471c.

* fix self.paligemma

* fix tests related to quantiles that were scaled to [0,1], the new range is [-1, 1]

* fix libero doc and use different transformer branch

* use fix branch instead of feat

* update results libero

* add new line

* fix formatting

* precommit

* update results libero

* update libero doc

* update title

* final changes

* add quantiles to test

* run pre commit

---------

Signed-off-by: Steven Palma <imstevenpmwork@ieee.org>
Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co>
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com>
Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
Co-authored-by: Steven Palma <steven.palma@huggingface.co>
2025-10-02 13:14:45 +02:00