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>
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>
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>
- 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>
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>
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>
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>
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>
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>
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>
* add env from the hub support
* add safe loading
* changes
* add tests, docs
* more
* style/cleaning
* order
---------
Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co>
* (unscrewing things up) (#2288)
* fix: expose a function explicitly building a frame for inference
* fix: first make dataset frame, then make ready for inference
* fix: reducing reliance on lerobot record for policy's ouptuts too
* fix: encapsulating squeezing out + device handling from predict action
* fix: remove duplicated call to build_inference_frame and add a function to only perform data type handling (whole conversion is: keys matching + data type conversion)
* refactor(envs): add custom-observation-size (#2167)
* fix: add MockMotorBus to MockRobot
* rl: first drafts
* add: all components of HIL SERL
* fix: actor block works
* fix: less friction, less friction
* add: hil-serl complete example
* fix: dataset names
* fix: restructuring example folder
* fix: act works but found bug in how ACT works
* fix: same path for both pre and postprocessors
* fix: paths
* add: example usage for act
* add: using ACT example
* fix: training examples
* fix: using examples
* fix: camera index
* fix: rename workflows into tutorial so that the path of the files is lerobot/examples/tutorial/...
* fix: upload everything in one repo
* fix: model name
* fix: simplify model path
* add: VLAs example
---------
Signed-off-by: Francesco Capuano <74058581+fracapuano@users.noreply.github.com>
* fix: minor fix using named attributes
* fix: change model to act
* fix: named attributes for inference frame building
* fix: minor fixes to smolvla
* fix: small changes to pi0
* remove: old file that should have never been committed (ups sorry sorry)
---------
Signed-off-by: Francesco Capuano <74058581+fracapuano@users.noreply.github.com>
Set camera width/height 1st before FPS setting, to avoid FPS set failure alike:
ERROR:__main__:Failed to connect or configure OpenCV camera /dev/video2: OpenCVCamera(/dev/video2) failed to set fps=30 (actual_fps=25.0).
Eugene Mironov