* modeld: add laneline_helper for plan X indices calculation
* spacing
* keep type hints
* openpilot
* sunnypilot/models/helpers
add modeld helpers to helpers
* Send it from each fill message
---------
Co-authored-by: Jason Wen <haibin.wen3@gmail.com>
* Add modelDataV2SP and lane turn logic implementation
Note: still need to hook up to other modeld's create unit test, fix stuff, and do the UI for it
* add unit tests for lane turn logic
* Add lane turn desire controls to models panel
* use `events_sp` instead of `events`
* integrate modelDataV2SP messaging to the other modeld controllers
* move this to that
* use min for general population here, on custom branches, change this to max :)
* Update events.py
Co-authored-by: royjr <royjr96@gmail.com>
* Update events.py
Co-authored-by: royjr <royjr96@gmail.com>
* refactor lane turn value control into one method
* Update selfdrive/ui/sunnypilot/qt/offroad/settings/models_panel.cc
* add integration tests for lane turn desire
* 10 updates is possibly more representative of real life
* real objects ofc
* desc: add toggle description for clarity
---------
Co-authored-by: royjr <royjr96@gmail.com>
* wrap the params
* just 1 class and use a single param for now
* refactor
* fix
* cache itself
* no longer
* rename
* type hint
* in helpers instead
* lint
* all
* init as 0 to pass ci
* init as 0 to pass ci
* return_default
* fix init
* add LAT_SMOOTH_SECONDS directly in modeld, temp remove dynamic desc, red difffffffff
* Introduce zero inputs for Lead, and plan to conform with new SP model introduced Monday, July 7, 2025
* Clean this up
* We can revert this after dev-c3-new testing and ready to merge.
* This needs to be apart of the conditional else fail
* Add full conditional
* Update longitudinal_planner.py
* Mypy from myphone!
* red diff
* Make generation a property for clarity
* Even clearer!
* Affix to generation, while allowing older models to use this IF param is set.
* seems a bit repetitive yea?
* dynamic
* Make most outputs dynamic
* Rm toggle from refactor
* refactor(modeld): simplify MHP output parsing logic
- Introduced `_parse_mhp_output` helper to remove redundancy and streamline `parse_dynamic_outputs`.
- Ensures improved code maintainability and clarity.
* refactor(longitudinal_planner): streamline generation handling logic
- Simplified `generation` assignment with inline conditional for better readability.
- Adjusted `mlsim` logic to default to model simulation when `generation` is unset.
* for ease of syncs from now on
* fix
---------
Co-authored-by: DevTekVE <devtekve@gmail.com>
* Add live delay toggle to torqued.py and twilsonco NNLC
* Set this in init
* Clean up
* Live delay toggle refactor
* ModeldLagd -> LagdToggle
* This is for lagd_toggle.py
* Add to NNLC
* Lagd toggle:
Display current values on UI
* Add break
* LagdToggleDelay
Live edit software_delay when livedelay is toggled `off`
* Always show description
* Add description as to why values don't update offroad
---------
Co-authored-by: Kumar <36933347+rav4kumar@users.noreply.github.com>
* Model panel
* Get this outta here and use sunnylink instead
* Remove space
* 'not' because we want gas gating to use e2e/mpc blend
* Add toggles to models_panel.cc
* "keep enabled for stock behavior"
* Add this here
* Cloudlog result
* change cloudlog to debug, and add latsmooth to steer actuator delay.
Need to edit json. Will do locally so when this is merged its a simple ready to go push.
* Cleanup
* Update longitudinal_planner.py
* Remove gasgating for now.. may need to be placed in model
---------
Co-authored-by: DevTekVE <devtekve@gmail.com>
* Refactor model runner methods for improved abstraction.
Moved slicing logic to a private `_slice_outputs` method and decoupled `_run_model` for clearer subclass implementation. Removed redundant `output` attribute in `ModelState` to streamline data handling.
* Add output parsing to model_runner and remove duplicate logic
Integrates an output parser directly into `model_runner` for streamlined inference and parsing. Removes redundant parser initialization from `modeld` to avoid duplication and enhance maintainability.
* Reordering
* linter
* linter
* Refactor model handling with `ModelData` abstraction
Introduce a `ModelData` class to encapsulate model and metadata logic, improving code clarity and modularity. Refactor `ModelRunner` to manage multiple models and add conditional handling for fallback scenarios. Adjust `TinygradRunner` to validate and use the new `ModelData` structure.
* Refactor model handling to use dictionary-based structure
Replaces the model list with a dictionary keyed by model type to improve clarity and maintainability. Updates related logic and ensures consistent handling of model metadata and inputs. Adds `slice_outputs` implementation to the `TinygradRunner` for proper output parsing.
* Refactor model runners to support policy and vision separation
Introduced `TinygradPolicyRunner`, `TinygradVisionRunner`, and `TinygradSplitRunner` to enable separate handling of policy and vision models. Updated `TinygradRunner` initialization and input preparation to accommodate modular processing. Adjusted `modeld` to utilize the new runners, ensuring compatibility with separated model workflows.
* Refactor model runner initialization and simplify logic
Introduce `get_model_runner` to centralize model runner selection logic, replacing multiple conditional instantiations. Simplify the handling of model metadata by removing fallback logic and restructuring output slicing to enforce proper loading of model data. These changes improve code maintainability and clarity.
* Refactor model data access for TinygradRunner initialization
Update references to access nested artifact properties and align with structural changes to the model data schema. This simplifies input shapes handling and ensures compatibility with updated model attributes.
* Refactor imports and clean up redundant code.
Removed unused imports and improved formatting for clarity and maintainability. These changes simplify the codebase by eliminating unnecessary dependencies and ensuring consistency.
* Refactor model output parsing with specialized parsers.
Introduce abstract `_parse_outputs` method to standardize parsing logic. Add `SplitParser` for specialized parsing in `TinygradVisionRunner` and `TinygradPolicyRunner`. This improves modularity and paves the way for easier parser customization.
* Add parser for model output processing in modeld_v2
Introduce a new `Parser` class to handle parsing and processing of model outputs, including MDN, binary cross-entropy, and categorical cross-entropy outputs. This modularizes the logic, improves clarity, and prepares for handling various types of model data.
* Add `input_shapes` property to model runners
Introduce a new `input_shapes` property in the abstract base class and its implementation in derived classes. This provides a standardized way to access the input shapes of models, improving clarity and consistency in the model runners.
* Refactor model runner to use private `_model_data` attribute
Replaced public `model_data` with private `_model_data` for improved encapsulation. Updated all references and property accessors accordingly. Simplified model type handling by using raw types where applicable.
* Remove debug print statement from model_runner.py
The unnecessary `print(model_type)` statement was removed as it served no functional purpose in the code. This improves code cleanliness and avoids unintended console output during execution.
* Refactor `_parse_outputs` call in `run_model`.
Replaced the use of `self.parser.parse_outputs` with `self._parse_outputs` for clarity and consistency. Updated method signature to align with the revised usage.
* Refactor model output parsing for clarity and scope separation
Moved specific parsing logic (e.g., lane_lines, lead) from `parse_model_outputs` to `parse_policy_outputs` to better align with functional responsibilities. This improves modularity and readability while maintaining existing functionality.
* Refactor model_runner to simplify result handling
Renamed variable `result` to `parsed_result` for clarity and removed unnecessary slicing during model output parsing. These changes improve code readability and maintain consistency within the `run_model` method.
* Adjust _parse_outputs method signature in model_runner
Updated the method signature of _parse_outputs to accept a single np.ndarray instead of a dictionary. This aligns with the intended data structure and ensures consistency across subclasses implementing this abstract method.
* Refactor ModelRunner to enforce abstract base class compliance
Updated `ModelRunner` and its subclasses to properly inherit from `ABC` while refactoring methods to ensure compliance with Python's abstract base class standards. Streamlined the handling of `_parse_outputs` and added a new `input_shapes` property for improved functionality.
* Fix buffer length issue in 20Hz model initialization
Adjusted `FULL_HISTORY_BUFFER_LEN` by adding +1 for `full_features_20Hz` to address compatibility issues with the current FoF model. Added a comment noting potential failure for other models with this adjustment.
* Refactor TinygradRunner to remove abstract methods.
Simplified the TinygradRunner class by removing unnecessary @abstractmethod decorators and redundant method definitions. This streamlines the code and aligns it more effectively with its current usage and implementation.
* Refactor model runner classes and enhance type annotations
Simplified model runner implementations, added type annotations, and improved code readability and maintainability. Introduced new type definitions, updated metadata handling, and standardized input/output parsing across all runner classes. Minor comment update in `modeld.py` for clarity.
* Refactor model runner classes with detailed docstrings.
Enhanced class and function docstrings across model_runner.py for better clarity and maintainability. Descriptions now include detailed explanations of attributes, purposes, and workflows to aid understanding and future development.
* Refactor model runner classes and add TICI hardware optimization
Simplified and clarified class definitions, comments, and functionality for ModelRunner subclasses. Introduced the use of QCOM environment variable on TICI for potential hardware acceleration. Enhanced input/output handling and error reporting across Tinygrad and ONNX implementations.
* Update parser import and usage to use CombinedParser
Replaced the Parser class with CombinedParser in model_runner.py. This change ensures consistency with the updated parsing logic, aligning with the latest requirements for combined model output handling.
* Refactor TinygradRunner hierarchy for modular parsers
Reorganized the TinygradRunner and its specialized runners (Vision, Policy, and Supercombo) into a cleaner, modular structure using composable classes. This consolidates parser logic, removes redundancy, and simplifies initialization by leveraging a shared base class with a dictionary-based parser method.
* Refactor model runners to use ModularRunner as abstract base.
Introduce a new `ModularRunner` class to enforce a consistent interface across model runners. Updated existing runners, including `ModelRunner`, `SupercomboTinygrad`, `PolicyTinygrad`, and `VisionTinygrad`, to extend `ModularRunner`. Added abstract methods and properties to enhance modularity and code maintainability.
* Refactor model runners into modular components.
This commit separates the logic for Tinygrad, ONNX, and split runners into clearly defined modules and components. It introduces `PolicyTinygrad`, `VisionTinygrad`, `SupercomboTinygrad`, and centralized helpers for cleaner architecture. The changes improve modularity and maintainability of the model running and parsing workflows.
* Simplify imports and clean up unused code in ONNXRunner.
Removed unused imports and redundant environmental variables to streamline the codebase. Consolidated necessary imports and organized type definitions for improved readability and maintenance.
* Standardize imports and add model data validation.
Updated import paths to ensure consistency across modules by using `openpilot` as the base. Introduced validation in `_parse_outputs` methods to handle cases where `_model_data` is not initialized, preventing potential runtime errors.
* Remove unused import and fix whitespace in runners
The unused import `ModelData` was removed from `tinygrad_runner.py` to clean up the code. Additionally, extraneous whitespace was corrected in `onnx_runner.py` for improved readability and consistency.
* Remove unnecessary blank line in import statements
Cleaned up import section by removing an extra blank line. This helps maintain consistency and adheres to code style conventions.
* BROKEN!! Staging code but its not gonna work. Also I realized we need to run the split models in 2 stages because the output of one is immediately needed for the input of the other. We might handle it inside of the model_runner instead
* update smooth
* Revert "update smooth"
This reverts commit c335712e6e1ee189459ce34dfc9d4028feb9470f.
* match case made this very hard to read.
* shouldnt be there
* Refactor to allow TR (soon TM)
* TR 7 is .1
* metadata
* .2=3
* Remove redundant comments and clean up conditional blocks in modeld.py.
* Undoing wrong buffer
* Refactor model initialization and adjust ONNX runner import
Reorganized numpy input buffer initialization and updated `temporal_idxs` logic for better clarity and efficiency. Conditional import for ONNXRunner added for non-TICI platforms to optimize imports. These changes improve maintainability and compatibility across platforms.
* Update CURRENT_SELECTOR_VERSION to 4
Bump the CURRENT_SELECTOR_VERSION constant from 3 to 4 to reflect changes in the selector logic or requirements. This ensures compatibility with the updated selector version while maintaining the minimum required version as 2.
* Add output_slices property to model runners
Introduce output_slices property to provide access to the output slices for individual and combined models. This ensures consistent handling of output slices across vision and policy models, improving modularity and usability.
* Refactor imports to use SplitModelConstants consistently
Updated import references to use the renamed `SplitModelConstants` class for consistency across files. This change ensures clarity and better alignment with the updated class naming convention.
* Refactor buffer initialization and desired curvature handling
Refactored model input buffer initialization for improved clarity and consistency, leveraging dynamic shape calculations. Extracted `process_desired_curvature` method to encapsulate logic for handling 3D and non-3D cases. Simplified temporal index generation and related calculations for better maintainability.
* Refactor desire reshape dims logic in modeld.py
Adjust logic for setting desire reshape dimensions to handle `is_20hz_3d` separately. This improves clarity and ensures proper handling of different model runner configurations.
* Fix off-by-one error in full_desire buffer initialization
The full_desire buffer length was mistakenly set to full_history_buffer_len + 1. This change corrects it to match the intended full_history_buffer_len, ensuring proper alignment with other buffers.
* Simplify desire reshape logic by removing unused condition.
Removed the `is_20hz_3d` condition and associated reshape logic since it is no longer needed. This streamlines the code and avoids unnecessary checks for unused configurations.
* Refactor buffer initialization for 20Hz model variants
Reorganized buffer initialization logic to prioritize the 20Hz_3D condition. This improves clarity and ensures specific handling of different 20Hz configurations. Adjusted the order of conditions to streamline execution flow.
* Refactor: Move `get_action_from_model` and constants to `Model` class to improve encapsulation and readability.
* 12 line reshaping red diff
* .2 to match old models delay
* mypy fixes
* Revert "12 line reshaping red diff"
This reverts commit 8c7280f629043f0485749e2536a20af74c9209b2.
* mypy
* remove this
* Fix desired curvature for models which do not output desired_curvature
* fix FoF
* flip policy and vision outs to allow FoF and tomb raider to live in harmony using conditional `if 'this' in outs:'`
* noqa
* single
* sunnypilot modeld.py
* action
* overrides methodology
* combine split outputs to its own method
* comments
* Fix static checker line length
* static will fail on line length
lines:
286,
206,
70 - 77,
159,
168
* Address E501 line length violations
* This will make TR better while not effecting FoF/VFF at all
* Reduce this to one conditional and just call normally in vision/policy
* Align with upstream in our own way.
* check for desired curvature in outputs first
* outputs
* Use a cleaner import method
* Fix output
* Clean up some values
* Only call on init
* slight cleanup
* names!!!!!!!!!
* Refactor overrides structure to support key-value pairs.
The overrides structure now uses a list of key-value pairs instead of fixed lat/long fields. This change improves flexibility, allowing dynamic addition of override parameters. Code adjustments ensure backward compatibility and consistent behavior throughout the application.
* Refactor: Use local variable for SplitModelConstants
Introduce a local `constants` variable to replace repeated access to `SplitModelConstants`. This simplifies code readability and adheres to linter recommendations for line length.
* Refactor model constant handling to improve modularity
Replaced direct usage of model constants with dynamic access through model runners for better scalability and maintainability. This change centralizes constant definitions, reduces redundancy, and ensures clearer integration with different model types.
---------
Co-authored-by: discountchubbs <alexgrant990@gmail.com>
Co-authored-by: Discountchubbs <159560811+Discountchubbs@users.noreply.github.com>
Co-authored-by: Jason Wen <haibin.wen3@gmail.com>
* Refactor model and artifact structures with version compatibility filtering
- Introduced `Artifact` struct and nested it within the `Model` struct for improved clarity and organization.
- Updated enums, logic, and parsing to align with the new struct definitions.
- Implemented version compatibility filtering for model bundles using the `is_bundle_version_compatible` helper.
- Enhanced artifact download handling by adding checks for missing URIs, better error management, and improved logging.
- Adjusted model fetching to point to the latest endpoint (`v3`).
* Make linter happy
* Make linter happy
* Refactor model data parsing to improve readability.
Replaced kwargs-based data extraction with explicit parameter passing for clarity. This enhances code readability and reduces ambiguities in method calls, making the parsing logic more maintainable and straightforward.
* Refactor error handling in active model bundle retrieval.
Wrapped the logic to fetch the active model bundle in a try-except block to prevent unhandled exceptions. This ensures more robust error handling and avoids potential crashes when retrieving or processing model data.
* Refactor exception handling in get_active_model_bundle
Replace bare except with Exception to improve specificity and clarity. This ensures better debugging practices and aligns with recommended coding standards. Other minor whitespace adjustments were made for improved readability.
* Update model path to use artifact fileName property
Replaced `fileName` with `artifact.fileName` in the custom model path construction. This ensures compatibility with updated drive model structures and avoids potential file resolution issues.
* Remove supercombo model ONNX file.
Deleted the large `supercombo.onnx` model file from the repository. This cleanup reduces repository size and dependency on unused or outdated files for this version.
* Disable tinygrad model compilation on macos temporarily
* Remove unused dmonitoring model file.
Deleted the ONNX model for dmonitoring as it is no longer required. This eliminates unnecessary assets and reduces repository size.
* Removing the model also from the snpe build, we have them, prebuilt
Replaced occurrences of `openpilot.common.numpy_fast` with direct imports from `numpy` across multiple files. This simplifies dependencies and ensures consistency with standard Python library usage. Adjusted tests to mock `numpy` functions accordingly.
This function logs detailed build failure information, including the status and build log retrieved from OpenCL. It provides better debugging support for diagnosing issues with OpenCL program compilation.
Introduce `clutil_legacy` to handle OpenCL program creation from binaries and error string mapping. This improves modularity and prepares for enhanced OpenCL compatibility across platforms.
* Add support for TinyGrad model runner processing
Introduced a new function `is_tinygrad_model` to detect TinyGrad as an active model runner. Updated the `is_stock_model` logic to account for TinyGrad models and added a new process entry for TinyGrad in the model manager. This enables handling TinyGrad models alongside existing configurations.
adding modeld back
Add support for `modeld_v2` and update paths for consistency
Updated `SConscript` files to integrate `modeld_v2` alongside `modeld` and adjusted script paths for correct metadata handling. Adjusted various configurations and scripts, such as `labeler.yaml` and `build_release.sh`, to include `modeld_v2` and ensure cohesive project structure.
Refactor imports to use updated `modeld_v2` paths.
Replaced outdated `modeld` references with their `modeld_v2` counterparts for consistency and clarity across the codebase. Also updated `.gitignore` to accommodate new directory structure. This change ensures better maintainability and alignment with the new directory schema.
Refactor and reorganize modeld to sunnypilot/modeld_v2 structure.
Moved and renamed `modeld` components to the new `sunnypilot/modeld_v2` directory for better organization and modularity. Updated imports and file references to align with the new structure, ensuring compatibility and functionality. Streamlined project structure to improve maintainability and future development.
* typo
* Use `stock` model runner and refactor model checks.
Replaces outdated model detection logic with unified `stock` runner integration, simplifying the decision flow for model selection. Includes `stock` as a new enum in the `Runner` type and updates affected references accordingly.
* Handle missing 'sim_pose' in model outputs gracefully.
Added conditional checks to ensure the code handles cases where 'sim_pose' is absent in the model outputs. Fallback behaviors use 'plan' data when 'sim_pose' is unavailable, preventing potential errors and enhancing robustness.
* modeld: script to generate new default model hash and name
* break CI intentionally to trigger new changes
* more verbose and fix
* more verbose hehe
* modeld: Retain pre-20hz drive model support
* Method not available anymore on OP
* some fixes
* Revert "Long planner get accel: new function args (#34288)"
* Revert "Fix low-speed allow_throttle behavior in long planner (#33894)"
* Revert "long planner: allow throttle reflects usage (#33792)"
* Revert "Gate acceleration on model gas press predictions (#33643)"
* Reapply "Gate acceleration on model gas press predictions (#33643)"
This reverts commit 76b08e37cb8eb94266ad9f6fed80db227e7c3428.
* Reapply "long planner: allow throttle reflects usage (#33792)"
This reverts commit c75244ca4e9c48084b0205b7c871e1a4e0f4e693.
* Reapply "Fix low-speed allow_throttle behavior in long planner (#33894)"
This reverts commit b2b7d21b7b685a2785d1beede3d223f0bb954807.
* Reapply "Long planner get accel: new function args (#34288)"
This reverts commit 74dca2fccf4da59cc8ac62ba9c0ad10ba3fc264b.
* don't need
* retain snpe
* wrong
* they're symlinks
* remove
* put back into VCS
* add back
* don't include built
* Refactor model runner retrieval with caching support
Added caching for active model runner type via `ModelRunnerTypeCache` to enhance performance and avoid redundant checks. Introduced a `force_check` flag to bypass the cache when necessary. Updated related code to handle cache clearing during onroad transitions.
* Update model runner determination logic with caching fix
Enhances `get_active_model_runner` to utilize caching more effectively by ensuring type consistency and updating cache only when necessary. Also updates `is_snpe_model` to pass the `started` state to the runner determination function, improving behavior for dynamic checks.
* parse inputs via metadata
* load model and metadata dynamically
* cherry pick from devtekve as base
* lateral_control_params & prev_desired_curv: MLSIM V0 to Null Pointer
* old desired_curv data: MLSIM V1 to Postal Service
* Bringing what was on master back then
* Cleaning up
* Refactor model pipeline for modularity and dynamic input handling
Refactored the model pipeline by introducing helper functions to modularize model loading, metadata extraction, and input preparation. Improved flexibility in handling dynamic input keys and parsing outputs based on model configuration. Removed deprecated or unused code segments for cleaner and more maintainable structure.
* Push NDv2 because why not and fix modeld
* `Refactor model parsing and clean unused code dependencies`
Simplified `parse_outputs` by removing unnecessary `input_keys` parameter, ensuring cleaner logic. Updated `PROCESS_NAME` for standardization and eliminated deprecated `Pathlib` dependencies in model paths. Minor adjustments improve input handling for lateral control parameters.
* Refactor model and metadata loading functions.
Simplified and clarified `load_model` by renaming it to `get_model_path` and removing redundant variable assignments. Streamlined `load_metadata` by directly returning the loaded metadata without intermediate variables. These changes improve code readability and maintainability.
* Refactor modeld process selection based on SNPE support.
Introduce conditional logic to determine and start the appropriate modeld process (SNPE or default) based on hardware support. This improves flexibility and ensures correct process management.
* Walrus baby
* Update longitudinal_planner.py
* Improve model download progress handling and translations
Refactored model download status handling logic for better clarity and added mechanisms to track status changes efficiently. Updated UI text and translations across multiple languages to reflect consistent and accurate model download states.
* Revert "Update longitudinal_planner.py"
This reverts commit b44a687e4cfb1e2708457478e8626c731f42db0c.
* Fix variable naming for curvature size in modeld.py
Renamed the variable `len` to `length` to avoid conflict with the built-in `len()` function, improving code clarity and preventing potential errors. Also removed trailing spaces in commented-out sections for better formatting consistency.
* sync with upstream
* some are different
* should work
* sim_pose only exists in in ndv3 and prior
* dynamic meta constants
* fix
* uiview: disable power saving
* fix this
* ain't coasting for y'all
* Static analysis
* Refactor initialization of model inputs for clarity.
Removed redundant pre-initialization of `driving_style`, `nav_features`, and `nav_instructions` variables. Instead, directly initialize these within their respective conditional blocks for better readability and reduced memory usage.
* default to none
* enable in next PR
* more
* Revert "more"
This reverts commit f5a4220588c5b014b29173f8f89e1fecdec25336.
* Revert "enable in next PR"
This reverts commit 621cc4f18ead8489cb05a22a73b48e5e4fe33787.
* no need to cast bool
* nuke
* fix desired curvature for pre LAv1 models
* mypy
* static
* fix
* new json
* Going to a test branch with a different model json list
* renamed model json
* Update model runner handling in custom.capnp and helpers
Refactored model runner logic by introducing a `runner` field in `custom.capnp` and simplifying `get_active_model_runner` logic. Removed deprecated function `get_model_runner_by_filename` and added a temporary filter in `fetcher.py` to enforce `snpe` until full tinygrad support is implemented.
* Revert "Update model runner handling in custom.capnp and helpers"
This reverts commit f34d872c1369fa5479496ba4e0cce7b3063ab358.
* Revert "renamed model json"
This reverts commit 15c6ed303b01ab78d1a576dc1d4ad105db7518df.
* Revert "Going to a test branch with a different model json list"
This reverts commit 4c1408fee524656049ac6502ac4f578e5b632d54.
* Reapply "renamed model json"
This reverts commit c6fec6912a1517d161dc9b23dce43ddf46866312.
Reapply "Going to a test branch with a different model json list"
This reverts commit 83e253e9a3b6573191d907584d6368d991395b0a.
* Add 'runner' property to 'ModelBundle' and update relevant functions
The 'ModelBundle' class in 'custom.capnp' has been extended to include a 'runner' property. This required updating 'fetcher.py' to handle the 'runner' property when parsing model bundles. Additionally, the helper function 'get_model_runner_by_filename' has been removed from 'helpers.py' as it is no longer needed because the 'runner' property provides this information. The 'get_active_model_runner' function has also been updated in light of these changes.
* Refine bundle selection logic in SoftwarePanelSP
Improve logic for determining which model bundle to display by considering download status and failure state. Remove unnecessary function call to enhance clarity and maintainability.
* tmp
* Add retrieval of active model bundle in manager loop
Introduce a call to `get_active_bundle` to fetch the active model bundle and store it in `self.active_bundle`. This ensures the active bundle is always up-to-date during the model management process.
* Add "Use Default" option for model selection
Introduced a "Use Default" option in the model selection dropdown, allowing users to reset to the default model. Adjusted logic to handle default selection and ensure proper parameter updates. Fixed bundle status handling during the download process in the model manager.
* Refactor type hint in active_bundle assignment.
Removed an unnecessary type hint in the active_bundle assignment for cleaner and more maintainable code. This change does not affect functionality but improves code readability.
* no nested
* update json url
* split out
* format
* condense
* more
---------
Co-authored-by: Jason Wen <haibin.wen3@gmail.com>
Co-authored-by: Kumar <36933347+rav4kumar@users.noreply.github.com>
* modeld: Retain pre-20hz drive model support
* Method not available anymore on OP
* some fixes
* Revert "Long planner get accel: new function args (#34288)"
* Revert "Fix low-speed allow_throttle behavior in long planner (#33894)"
* Revert "long planner: allow throttle reflects usage (#33792)"
* Revert "Gate acceleration on model gas press predictions (#33643)"
* Reapply "Gate acceleration on model gas press predictions (#33643)"
This reverts commit 76b08e37cb8eb94266ad9f6fed80db227e7c3428.
* Reapply "long planner: allow throttle reflects usage (#33792)"
This reverts commit c75244ca4e9c48084b0205b7c871e1a4e0f4e693.
* Reapply "Fix low-speed allow_throttle behavior in long planner (#33894)"
This reverts commit b2b7d21b7b685a2785d1beede3d223f0bb954807.
* Reapply "Long planner get accel: new function args (#34288)"
This reverts commit 74dca2fccf4da59cc8ac62ba9c0ad10ba3fc264b.
* don't need
* retain snpe
* wrong
* they're symlinks
* remove
* put back into VCS
* add back
* don't include built
* Refactor model runner retrieval with caching support
Added caching for active model runner type via `ModelRunnerTypeCache` to enhance performance and avoid redundant checks. Introduced a `force_check` flag to bypass the cache when necessary. Updated related code to handle cache clearing during onroad transitions.
* Update model runner determination logic with caching fix
Enhances `get_active_model_runner` to utilize caching more effectively by ensuring type consistency and updating cache only when necessary. Also updates `is_snpe_model` to pass the `started` state to the runner determination function, improving behavior for dynamic checks.
* default to none
* enable in next PR
* more
---------
Co-authored-by: DevTekVE <devtekve@gmail.com>
* modeld: Retain pre-20hz drive model support
* Method not available anymore on OP
* some fixes
* Revert "Long planner get accel: new function args (#34288)"
* Revert "Fix low-speed allow_throttle behavior in long planner (#33894)"
* Revert "long planner: allow throttle reflects usage (#33792)"
* Revert "Gate acceleration on model gas press predictions (#33643)"
* Reapply "Gate acceleration on model gas press predictions (#33643)"
This reverts commit 76b08e37cb8eb94266ad9f6fed80db227e7c3428.
* Reapply "long planner: allow throttle reflects usage (#33792)"
This reverts commit c75244ca4e9c48084b0205b7c871e1a4e0f4e693.
* Reapply "Fix low-speed allow_throttle behavior in long planner (#33894)"
This reverts commit b2b7d21b7b685a2785d1beede3d223f0bb954807.
* Reapply "Long planner get accel: new function args (#34288)"
This reverts commit 74dca2fccf4da59cc8ac62ba9c0ad10ba3fc264b.
* don't need
* retain snpe
* wrong
* they're symlinks
* remove
* put back into VCS
* add back
* don't include built
* Refactor model runner retrieval with caching support
Added caching for active model runner type via `ModelRunnerTypeCache` to enhance performance and avoid redundant checks. Introduced a `force_check` flag to bypass the cache when necessary. Updated related code to handle cache clearing during onroad transitions.
* Update model runner determination logic with caching fix
Enhances `get_active_model_runner` to utilize caching more effectively by ensuring type consistency and updating cache only when necessary. Also updates `is_snpe_model` to pass the `started` state to the runner determination function, improving behavior for dynamic checks.
* default to none
* enable in next PR
* more
---------
Co-authored-by: DevTekVE <devtekve@gmail.com>
* tinygrad with snpe
* force with snpe to validate
* fix path
* fix more paths
* Adjust modeld execution logic based on active model runner
Introduced a check to conditionally execute `modeld` based on the active model runner. Added support for distinguishing between SNPE and TinyGrad runners using new helper functions and updated `custom.capnp` definitions. This change optimizes process management by ensuring compatibility with the selected model runner.
* Refactor modeld process function checks.
Introduce `is_stock_model` to clarify logic and replace direct uses of `is_snpe_model` where the stock model condition is needed. Additionally, rename the duplicate "modeld" process in sunnyPilot to "modeld_snpe" for clarity and consistency.
* ignore tg
* fix process name
* ruff
* fix thneed paths
* mypy
* remove our own
* use upstream compile3
* fix thneed
* try this
* Revert "remove our own"
This reverts commit 1cf4f57502565c274628e185c66f1eb04c4d9bbe.
* try using compile2.py again
* add back symlink
* fix path
* more fix
* wrong path again
* Revert "wrong path again"
This reverts commit f5301c19d594defb23cda2604168bcb02c830f3e.
* update
* hardcode path to our submodule
* force path
* try this
* fix file name
* try this
* again
* Revert "again"
This reverts commit 17c8cd73768a2de5aaf2a34d202aa6f03d59d72d.
* Revert "try this"
This reverts commit 767f78bbcf17b08edbc20f283d10a1990bf4264f.
* Revert "fix file name"
This reverts commit 485eef68da981da571fe9a9ebf3aecdb95e5588c.
* Revert "try this"
This reverts commit 41fef87680cdda1ba8cbd7e5c59256e6c57010a0.
* Revert "force path"
This reverts commit 5c3b408937bff0f61b150971b328d127501c5bf0.
* Revert "hardcode path to our submodule"
This reverts commit 5ee1950b6f4fce73e7e73b6971b996a9989d0a93.
* Revert "update"
This reverts commit fb313bd7fbeb50111f3c4a11137b4cfd9cabc3fa.
* Reapply "wrong path again"
This reverts commit 309639aeb3575e20b215bbbcc27e48923ee95c87.
* Revert "wrong path again"
This reverts commit f5301c19d594defb23cda2604168bcb02c830f3e.
* Revert "more fix"
This reverts commit 23dd423e78e60bd6a0bd73e921bfba9a5aad88bd.
* Revert "fix path"
This reverts commit 75d338f2bda2dfa77044e33f4c6553390621b13b.
* Revert "add back symlink"
This reverts commit 9f71ad0b8ae2068e431c455af9d4f954d024eec7.
* Revert "try using compile2.py again"
This reverts commit 914117d2e1c6c4270f7bef1a5305847a1d7bab17.
* Reapply "remove our own"
This reverts commit b1996377b346658f2094cba9032a66230784cb3e.
* don't even compile anymore
* need it for default snpe model
* add to lfs
* bring onnx back for sim
* must add this back
* need this
---------
Co-authored-by: DevTekVE <devtekve@gmail.com>
James Vecellio-Grant