Commit Graph

4 Commits

Author SHA1 Message Date
Steven Palma f0d2b37beb chore(dependencies): bump transformers v5 (#2964)
* chore(dependencies): upgrade transformers + hggingface-hub + peft + scipy

* chore(dependencies): bump pi0 family to transformers v5

* chore(dependencies): bump wall x to transformers v5

* chore(dependencies): bump gr00t to transformers v5

* chore(style): fix pre-commit

* fix(policy): xvla forced_bos_token missing

* test(rl): skip ci tests for resnet10

* Fix: full pi models support for transformer v5 (#2967)

* fix(pi): remove loss truncation

* fix(pi): remove state padding before tokenization

* fix(pi): fix image padding value

* fix from_pretrain

* add transformer v5 changes

* remove reference

* more fixes

* make it work

* add support for rest of pi family

* add pifast work

* more changes

* more changes

* more cleanup

* fix torch params

* dtype fix

* torch compile

* embed mismatch fix

* revert groot

* more nit fixes

* remove unused classes

* more fixes

* revert

* nit

* torch dtype warning fix

* but back dynamic renaming

* add tie embedding

---------

Co-authored-by: Yufei Sun <skieyfly@gmail.com>

* chore: fix XVLA in transformers v5 (#3006)

* test(policies): enable wall x CI testing

* style(test): pre-commit check

* style(test): pre-commit

* fix wall x for transformer v5 (#3008)

* tv5 fix

* various wall x fixes

* Delete tests/policies/pi0_pi05/print_pi05_output_logits.py

Signed-off-by: Jade Choghari <chogharijade@gmail.com>

* sync modeling_florence2.py with chore/bump_transformers_v5

* more

* more fixes

* more

* remove comment

* more

---------

Signed-off-by: Jade Choghari <chogharijade@gmail.com>

* chore(dependencies): adjust dependencies versioning after transformers v5 (#3034)

* chore(dependecies): adjust dependecies versioning after transformers v5

* fix(policies): remove deprecated input_embeds

* fix(policies): dict _tied_weights_keys

* chore(depedencies): common qwen-vl-utils

* chore(dependencies): bump transformers to 5.2

* Fix policy testing for tv5 (#3032)

* fix ci logger

* other fix

* fix mypy

* change logits to torch2.10

* skip wallx|

* remove logging

---------

Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>

* feat(ci): log into HF to unblock some CI tests (#3007)

* feat(ci): log into HF to unblock some CI tests

* chore(ci): change hf call + secret name

* fix(ci): temp fix for pi0 rtc test

* test(policies): require_cuda for unblocked tests

* test(policies): require_cuda wall_x

* fic(tests): require_cuda outter most for pi0

* fix(test): return instead of yield

---------

Signed-off-by: Steven Palma <imstevenpmwork@ieee.org>

* style(test): fix pre-commit

* chore(deps): upgrade transformers (#3050)

* chore(test): use lerobot model

* fix(policies): change default action tokenizer for wall x

* sample on cpu

* Revert "Merge branch 'chore/bump_transformers_v5' of https://github.com/huggingface/lerobot into chore/bump_transformers_v5"

This reverts commit d9b76755f7, reversing
changes made to 89359cb0b6.

* Reapply "Merge branch 'chore/bump_transformers_v5' of https://github.com/huggingface/lerobot into chore/bump_transformers_v5"

This reverts commit c9914db78b.

---------

Signed-off-by: Jade Choghari <chogharijade@gmail.com>
Signed-off-by: Steven Palma <imstevenpmwork@ieee.org>
Co-authored-by: Jade Choghari <chogharijade@gmail.com>
Co-authored-by: Yufei Sun <skieyfly@gmail.com>
Co-authored-by: Pepijn <pepijn@huggingface.co>
2026-03-05 09:25:26 +01:00
Eugene Mironov 8a915c6b6f [RTC] Real Time Chunking for Pi0, Smolvla, Pi0.5 (#1698)
* Add Real-Time Chunking (RTC) support for flow matching models

Implement Real-Time Chunking (RTC) for action chunking policies using flow
matching denoising. RTC enables smooth action transitions between consecutive
chunks by using prefix guidance during denoising.

Key features:
- RTCProcessor class with denoise_step method for RTC guidance
- Tracker system for debug tracking using time-based dictionary storage
- RTCDebugVisualizer with comprehensive visualization utilities
- Integration with SmolVLA policy for flow matching models
- Support for multiple prefix attention schedules (ZEROS, ONES, LINEAR, EXP)
- Configurable execution horizon and max guidance weight
- Example scripts for dataset evaluation and real-time control

Technical details:
- Uses autograd-based gradient computation for RTC corrections
- Time-based tracking eliminates duplicate step issues
- Proxy methods in RTCProcessor for cleaner API
- Full integration with LeRobot's policy and dataset systems

Files added/modified:
- src/lerobot/configs/types.py: Add RTCAttentionSchedule enum
- src/lerobot/policies/rtc/: Core RTC implementation
  - configuration_rtc.py: RTC configuration
  - modeling_rtc.py: RTCProcessor with denoise_step
  - debug_handler.py: Tracker for debug information
  - debug_visualizer.py: Visualization utilities
- src/lerobot/policies/smolvla/modeling_smolvla.py: RTC integration
- examples/rtc/: Example scripts and evaluation tools

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Alexander Soare <alexander.soare159@gmail.com>
Co-Authored-By: Claude <noreply@anthropic.com>

* Fix rtc_config attribute access in SmolVLA

Use getattr() to safely check for rtc_config attribute existence
instead of direct attribute access. This fixes AttributeError when
loading policies without rtc_config in their config.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Alexander Soare <alexander.soare159@gmail.com>
Co-Authored-By: Claude <noreply@anthropic.com>

* fixup! Fix rtc_config attribute access in SmolVLA

* Add RTCConfig field to SmolVLAConfig

Add rtc_config as an optional field in SmolVLAConfig to properly
support Real-Time Chunking configuration. This replaces the previous
getattr() workarounds with direct attribute access, making the code
cleaner and more maintainable.

Changes:
- Import RTCConfig in configuration_smolvla.py
- Add rtc_config: RTCConfig | None = None field
- Revert getattr() calls to direct attribute access in modeling_smolvla.py

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Alexander Soare <alexander.soare159@gmail.com>
Co-Authored-By: Claude <noreply@anthropic.com>

* Refactor RTC enabled checks to use _rtc_enabled helper

Add _rtc_enabled() helper method in VLAFlowMatching class to simplify
and clean up RTC enabled checks throughout the code. This reduces
code duplication and improves readability.

Changes:
- Add _rtc_enabled() method in VLAFlowMatching
- Replace verbose rtc_config checks with _rtc_enabled() calls
- Maintain exact same functionality with cleaner code

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Alexander Soare <alexander.soare159@gmail.com>
Co-Authored-By: Claude <noreply@anthropic.com>

* Rename track_debug method to track

Simplify the method name from track_debug to just track for better
readability and consistency. The method already has clear documentation
about its debug tracking purpose.

Changes:
- Rename RTCProcessor.track_debug() to track()
- Update all call sites in modeling_smolvla.py and modeling_rtc.py

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Alexander Soare <alexander.soare159@gmail.com>
Co-Authored-By: Claude <noreply@anthropic.com>

* Use output_dir for saving all evaluation images

Update eval_dataset.py to save all comparison images to the
configured output_dir instead of the current directory. This provides
better organization and allows users to specify where outputs should be
saved.

Changes:
- Add os import at top level
- Create output_dir at start of run_evaluation()
- Save all comparison images to output_dir
- Remove duplicate os imports
- Update init_rtc_processor() docstring to be more concise

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Alexander Soare <alexander.soare159@gmail.com>
Co-Authored-By: Claude <noreply@anthropic.com>

* fixup! Use output_dir for saving all evaluation images

* Fix logging buffering and enable tracking when RTC config provided

- Add force=True to logging.basicConfig to override existing configuration
- Enable line buffering for stdout/stderr for real-time log output
- Modify init_rtc_processor to create processor when rtc_config exists
  even if RTC is disabled, allowing tracking of denoising data

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Co-Authored-By: Alexander Soare <alexander.soare159@gmail.com>

* Refactor SmolVLA plotting to use tracker data instead of local variables

Remove local tracking variables (correction, x1_t, error) from the
denoising loop and instead retrieve plotting data from the RTC tracker
after each denoise step. This makes the code cleaner and uses the
tracker as the single source of truth for debug/visualization data.

Changes:
- Remove initialization of correction, x1_t, error before denoising loop
- After each Euler step, retrieve most recent debug step from tracker
- Extract correction, x1_t, err from debug step for plotting
- Update tracking condition to use is_debug_enabled() method

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Co-Authored-By: Alexander Soare <alexander.soare159@gmail.com>

* Move plotting logic from modeling_smolvla to eval_dataset script

Refactor to improve separation of concerns:

modeling_smolvla.py changes:
- Remove all plotting logic from sample_actions method
- Remove viz_xt_axs, viz_vt_axs, viz_x1t_axs parameters
- Remove matplotlib and RTCDebugVisualizer imports
- Remove viz_fig, viz_axs, denoise_step_counter instance variables
- Simplify denoising loop to only track data in rtc_processor

eval_dataset.py changes:
- Add _plot_denoising_steps_from_tracker helper method
- Retrieve debug steps from tracker after inference
- Plot x_t, v_t, x1_t, correction, and error from tracker data
- Enable debug tracking (cfg.rtc.debug = True) for visualization
- Remove viz axes parameters from predict_action_chunk calls

modeling_rtc.py changes:
- Remove v_t from track() call (handled by user change)

Benefits:
- Cleaner modeling code focused on inference
- Evaluation script owns all visualization logic
- Better separation of concerns
- Tracker is single source of truth for debug data

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Co-Authored-By: Alexander Soare <alexander.soare159@gmail.com>

* Refactor plotting loging

* fixup! Refactor plotting loging

* Improve visualization: separate correction plot and fix axis scaling

Changes:
- Create separate figure for correction data instead of overlaying on v_t
- Add _rescale_axes helper method to properly scale all axes
- Add 10% margin to y-axis for better visualization
- Fix v_t chart vertical compression issue

Benefits:
- Clearer v_t plot without correction overlay
- Better axis scaling with proper margins
- Separate correction figure for focused analysis
- Improved readability of all denoising visualizations

Output files:
- denoising_xt_comparison.png (x_t trajectories)
- denoising_vt_comparison.png (v_t velocity - now cleaner)
- denoising_correction_comparison.png (NEW - separate corrections)
- denoising_x1t_comparison.png (x1_t state with error)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Co-Authored-By: Alexander Soare <alexander.soare159@gmail.com>

* fixup! Improve visualization: separate correction plot and fix axis scaling

* fixup! fixup! Improve visualization: separate correction plot and fix axis scaling

* fixup! fixup! fixup! Improve visualization: separate correction plot and fix axis scaling

* Fix traacking

* Right kwargs for the policy

* Add tests for tracker

* Fix tests

* Drop not required methods

* Add torch compilation for eval_dataset

* delete policies

* Add matplotliv to dev

* fixup! Add matplotliv to dev

* Experiemnt with late detach

* Debug

* Fix compilation

* Add RTC to PI0

* Pi0

* Pi0 eval dataset

* fixup! Pi0 eval dataset

* Turn off compilation for pi0/pi05

* fixup! Turn off compilation for pi0/pi05

* fixup! fixup! Turn off compilation for pi0/pi05

* fixup! fixup! fixup! Turn off compilation for pi0/pi05

* fixup! fixup! fixup! fixup! Turn off compilation for pi0/pi05

* fixup! fixup! fixup! fixup! fixup! Turn off compilation for pi0/pi05

* Add workable flow

* Small fixes

* Add more tests

* Add validatio at the end

* Update README

* Silent validation

* Fix tests

* Add tests for modeling_rtc

* Add tests for flow matching models with RTC

* fixup! Add tests for flow matching models with RTC

* fixup! fixup! Add tests for flow matching models with RTC

* Add one more test

* fixup! Add one more test

* Fix test to use _rtc_enabled() instead of is_rtc_enabled()

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* fixup! Fix test to use _rtc_enabled() instead of is_rtc_enabled()

* fixup! fixup! Fix test to use _rtc_enabled() instead of is_rtc_enabled()

* Add RTC initialization tests without config for PI0.5 and SmolVLA

Add test_pi05_rtc_initialization_without_rtc_config and
test_smolvla_rtc_initialization_without_rtc_config to verify that
policies can initialize without RTC config and that _rtc_enabled()
returns False in this case.

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Co-Authored-By: Claude <noreply@anthropic.com>

* Fix PI0.5 init_rtc_processor to use getattr instead of direct model access

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* Fix SmolVLA init_rtc_processor to use getattr instead of direct model access

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* Fix PI0.5 RTC tests to use quantile stats (q01, q99) for normalization

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* fixup! Fix PI0.5 RTC tests to use quantile stats (q01, q99) for normalization

* Fixup eval with real robot

* fixup! Fixup eval with real robot

* fixup! fixup! Fixup eval with real robot

* Extract simulator logic from eval_with real robot and add proper headers to files

* Update images

* Fix tests

* fixup! Fix tests

* add docs for rtc

* enhance doc and add images

* Fix instal instructions

---------
Co-authored-by: Ben Zhang <benzhangniu@gmail.com>
Co-authored-by: Alexander Soare <alexander.soare159@gmail.com>
Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co>
2025-11-19 11:19:48 +01:00
Steven Palma 6c28ef894a chore(docs): add missing license headers (#2140) 2025-10-08 14:27:52 +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