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sunnypilot models: support for on-policy models

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This commit is contained in:
Jason Wen
2026-04-02 21:14:39 -04:00
parent d398f9951e
commit b5d2026fc7
12 changed files with 74 additions and 25 deletions
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1
cereal/custom.capnp
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@@ -154,6 +154,7 @@ struct ModelManagerSP @0xaedffd8f31e7b55d {
vision @2;
policy @3;
offPolicy @4;
onPolicy @5;
}
}

2
common/model.h
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@@ -1 +1 @@
#define DEFAULT_MODEL "CD210 (Default)"
#define DEFAULT_MODEL "OP Model (Default)"

2
release/ci/model_generator.py
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@@ -104,7 +104,7 @@ def generate_metadata(model_path: Path, output_dir: Path, short_name: str):
metadata_file = metadata_file.rename(output_path / f"{base}_{short_name.lower()}_metadata.pkl")
# Build the metadata structure
model_type = "offPolicy" if "off_policy" in base else base.split("_")[-1]
model_type = "offPolicy" if "off_policy" in base else "onPolicy" if "on_policy" in base else base.split("_")[-1]
model_metadata = {
"type": model_type,

8
selfdrive/ui/sunnypilot/layouts/settings/models.py
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@@ -58,6 +58,8 @@ class ModelsLayout(Widget):
self.supercombo_label = progress_item(tr("Driving Model"))
self.vision_label = progress_item(tr("Vision Model"))
self.policy_label = progress_item(tr("Policy Model"))
self.off_policy_label = progress_item(tr("Off-Policy Model"))
self.on_policy_label = progress_item(tr("On-Policy Model"))
self.refresh_item = button_item(tr("Refresh Model List"), tr("REFRESH"), "",
lambda: (ui_state.params.put("ModelManager_LastSyncTime", 0),
@@ -91,7 +93,7 @@ class ModelsLayout(Widget):
self.lagd_toggle = toggle_item_sp(tr("Live Learning Steer Delay"), "", param="LagdToggle")
self.items = [self.current_model_item, self.cancel_download_item, self.supercombo_label, self.vision_label,
self.policy_label, self.refresh_item, self.clear_cache_item, self.lane_turn_desire_toggle,
self.policy_label, self.off_policy_label, self.on_policy_label, self.refresh_item, self.clear_cache_item, self.lane_turn_desire_toggle,
self.lane_turn_value_control, self.lagd_toggle, self.delay_control]
def _update_lagd_description(self, lagd_toggle: bool):
@@ -129,7 +131,9 @@ class ModelsLayout(Widget):
def _handle_bundle_download_progress(self):
labels = {custom.ModelManagerSP.Model.Type.supercombo: self.supercombo_label,
custom.ModelManagerSP.Model.Type.vision: self.vision_label,
custom.ModelManagerSP.Model.Type.policy: self.policy_label}
custom.ModelManagerSP.Model.Type.policy: self.policy_label,
custom.ModelManagerSP.Model.Type.offPolicy: self.off_policy_label,
custom.ModelManagerSP.Model.Type.onPolicy: self.on_policy_label}
for label in labels.values():
label.set_visible(False)
self.cancel_download_item.set_visible(False)

2
sunnypilot/modeld_v2/install_models_pc.py
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@@ -30,7 +30,7 @@ def generate_metadata_pkl(model_path, output_path):
def install_models(model_dir):
model_dir = Path(model_dir)
models = ["driving_off_policy", "driving_policy", "driving_vision"]
models = ["driving_off_policy", "driving_on_policy", "driving_vision"]
found_models = []
for model in models:

8
sunnypilot/models/default_model.py
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@@ -8,14 +8,16 @@ from openpilot.sunnypilot import get_file_hash
DEFAULT_MODEL_NAME_PATH = os.path.join(BASEDIR, "common", "model.h")
MODEL_HASH_PATH = os.path.join(BASEDIR, "sunnypilot", "models", "tests", "model_hash")
VISION_ONNX_PATH = os.path.join(BASEDIR, "selfdrive", "modeld", "models", "driving_vision.onnx")
POLICY_ONNX_PATH = os.path.join(BASEDIR, "selfdrive", "modeld", "models", "driving_policy.onnx")
OFF_POLICY_ONNX_PATH = os.path.join(BASEDIR, "selfdrive", "modeld", "models", "driving_off_policy.onnx")
ON_POLICY_ONNX_PATH = os.path.join(BASEDIR, "selfdrive", "modeld", "models", "driving_on_policy.onnx")
def update_model_hash():
vision_hash = get_file_hash(VISION_ONNX_PATH)
policy_hash = get_file_hash(POLICY_ONNX_PATH)
off_policy_hash = get_file_hash(OFF_POLICY_ONNX_PATH)
on_policy_hash = get_file_hash(ON_POLICY_ONNX_PATH)
combined_hash = hashlib.sha256((vision_hash + policy_hash).encode()).hexdigest()
combined_hash = hashlib.sha256((vision_hash + off_policy_hash + on_policy_hash).encode()).hexdigest()
with open(MODEL_HASH_PATH, "w") as f:
f.write(combined_hash)

2
sunnypilot/models/fetcher.py
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@@ -116,7 +116,7 @@ class ModelCache:
class ModelFetcher:
"""Handles fetching and caching of model data from remote source"""
MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v15.json"
MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v16.json"
def __init__(self, params: Params):
self.params = params

5
sunnypilot/models/runners/helpers.py
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@@ -16,8 +16,9 @@ def get_model_runner() -> ModelRunner:
bundle = get_active_bundle()
if bundle and bundle.models:
model_types = {m.type.raw for m in bundle.models}
# Check if the bundle uses separate vision and policy models
if ModelType.vision in model_types or ModelType.policy in model_types:
# Check if the bundle uses separate vision and policy models (legacy or new split format)
split_types = {ModelType.vision, ModelType.policy, ModelType.offPolicy, ModelType.onPolicy}
if model_types & split_types:
return TinygradSplitRunner()
# Otherwise, assume a single model (likely supercombo)
if bundle.models:

16
sunnypilot/models/runners/tinygrad/model_types.py
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@@ -29,6 +29,22 @@ class OffPolicyTinygrad(ModularRunner, ABC):
return result
class OnPolicyTinygrad(ModularRunner, ABC):
"""
A TinygradRunner specialized for on-policy models.
Uses a SplitParser to handle outputs specific to the on-policy part of a split model setup.
"""
def __init__(self):
self._on_policy_parser = SplitParser()
self.parser_method_dict[ModelType.onPolicy] = self._parse_on_policy_outputs
def _parse_on_policy_outputs(self, model_outputs: np.ndarray) -> NumpyDict:
"""Parses on-policy model outputs using SplitParser."""
result: NumpyDict = self._on_policy_parser.parse_policy_outputs(self._slice_outputs(model_outputs))
return result
class PolicyTinygrad(ModularRunner, ABC):
"""
A TinygradRunner specialized for policy-only models.

44
sunnypilot/models/runners/tinygrad/tinygrad_runner.py
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@@ -3,14 +3,14 @@ import pickle
import numpy as np
from openpilot.sunnypilot.models.runners.constants import NumpyDict, ModelType, ShapeDict, CUSTOM_MODEL_PATH, SliceDict
from openpilot.sunnypilot.models.runners.model_runner import ModelRunner
from openpilot.sunnypilot.models.runners.tinygrad.model_types import PolicyTinygrad, VisionTinygrad, SupercomboTinygrad, OffPolicyTinygrad
from openpilot.sunnypilot.models.runners.tinygrad.model_types import PolicyTinygrad, VisionTinygrad, SupercomboTinygrad, OffPolicyTinygrad, OnPolicyTinygrad
from openpilot.sunnypilot.models.split_model_constants import SplitModelConstants
from openpilot.sunnypilot.modeld_v2.constants import ModelConstants
from tinygrad.tensor import Tensor
class TinygradRunner(ModelRunner, SupercomboTinygrad, PolicyTinygrad, VisionTinygrad, OffPolicyTinygrad):
class TinygradRunner(ModelRunner, SupercomboTinygrad, PolicyTinygrad, VisionTinygrad, OffPolicyTinygrad, OnPolicyTinygrad):
"""
A ModelRunner implementation for executing Tinygrad models.
@@ -26,6 +26,7 @@ class TinygradRunner(ModelRunner, SupercomboTinygrad, PolicyTinygrad, VisionTiny
PolicyTinygrad.__init__(self)
VisionTinygrad.__init__(self)
OffPolicyTinygrad.__init__(self)
OnPolicyTinygrad.__init__(self)
self._constants = ModelConstants
self._model_data = self.models.get(model_type)
if not self._model_data or not self._model_data.model:
@@ -98,20 +99,30 @@ class TinygradSplitRunner(ModelRunner):
super().__init__()
self.is_20hz_3d = True
self.vision_runner = TinygradRunner(ModelType.vision)
self.policy_runner = TinygradRunner(ModelType.policy)
self.policy_runner = TinygradRunner(ModelType.policy) if self.models.get(ModelType.policy) else None
self.off_policy_runner = TinygradRunner(ModelType.offPolicy) if self.models.get(ModelType.offPolicy) else None
self.on_policy_runner = TinygradRunner(ModelType.onPolicy) if self.models.get(ModelType.onPolicy) else None
self._constants = SplitModelConstants
def _run_model(self) -> NumpyDict:
"""Runs both vision and policy models and merges their parsed outputs."""
policy_output = self.policy_runner.run_model()
vision_output = self.vision_runner.run_model()
outputs = {**policy_output, **vision_output}
outputs = {**vision_output}
if self.policy_runner:
policy_output = self.policy_runner.run_model()
outputs.update(policy_output)
if self.off_policy_runner:
off_policy_output = self.off_policy_runner.run_model()
if self.on_policy_runner:
off_policy_output.pop('plan', None)
outputs.update(off_policy_output)
if self.on_policy_runner:
on_policy_output = self.on_policy_runner.run_model()
outputs.update(on_policy_output)
if 'planplus' in outputs and 'plan' in outputs:
outputs['plan'] = outputs['plan'] + outputs['planplus']
@@ -125,31 +136,44 @@ class TinygradSplitRunner(ModelRunner):
@property
def input_shapes(self) -> ShapeDict:
"""Returns the combined input shapes from both vision and policy models."""
shapes = {**self.policy_runner.input_shapes, **self.vision_runner.input_shapes}
shapes = {**self.vision_runner.input_shapes}
if self.policy_runner:
shapes.update(self.policy_runner.input_shapes)
if self.off_policy_runner:
shapes.update(self.off_policy_runner.input_shapes)
if self.on_policy_runner:
shapes.update(self.on_policy_runner.input_shapes)
return shapes
@property
def output_slices(self) -> SliceDict:
"""Returns the combined output slices from both vision and policy models."""
slices = {**self.policy_runner.output_slices, **self.vision_runner.output_slices}
slices = {**self.vision_runner.output_slices}
if self.policy_runner:
slices.update(self.policy_runner.output_slices)
if self.off_policy_runner:
slices.update(self.off_policy_runner.output_slices)
if self.on_policy_runner:
slices.update(self.on_policy_runner.output_slices)
return slices
def prepare_inputs(self, numpy_inputs: NumpyDict) -> dict:
"""Prepares inputs for both vision and policy models."""
# Policy inputs only depend on numpy_inputs
self.policy_runner.prepare_policy_inputs(numpy_inputs)
if self.policy_runner:
self.policy_runner.prepare_policy_inputs(numpy_inputs)
for key in self.vision_input_names:
if key in self.inputs:
self.vision_runner.inputs[key] = self.inputs[key].cast(self.vision_runner.input_to_dtype[key])
inputs = {**self.policy_runner.inputs, **self.vision_runner.inputs}
inputs = {**self.vision_runner.inputs}
if self.policy_runner:
inputs.update(self.policy_runner.inputs)
if self.off_policy_runner:
self.off_policy_runner.prepare_policy_inputs(numpy_inputs)
inputs.update(self.off_policy_runner.inputs)
if self.on_policy_runner:
self.on_policy_runner.prepare_policy_inputs(numpy_inputs)
inputs.update(self.on_policy_runner.inputs)
return inputs

2
sunnypilot/models/tests/model_hash
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@@ -1 +1 @@
32f57bdc91f910df1f48ddae7c59aaf6e751f9df6756da481a210577dbce8bcf
adfcb5ccac9cfaf291af6091d12e71be3f543c7694fc29d80caa561dc32194d7

7
sunnypilot/models/tests/test_default_model.py
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@@ -6,16 +6,17 @@ See the LICENSE.md file in the root directory for more details.
"""
from openpilot.sunnypilot import get_file_hash
from openpilot.sunnypilot.models.default_model import MODEL_HASH_PATH, VISION_ONNX_PATH, POLICY_ONNX_PATH
from openpilot.sunnypilot.models.default_model import MODEL_HASH_PATH, VISION_ONNX_PATH, OFF_POLICY_ONNX_PATH, ON_POLICY_ONNX_PATH
import hashlib
class TestDefaultModel:
def test_compare_onnx_hashes(self):
vision_hash = get_file_hash(VISION_ONNX_PATH)
policy_hash = get_file_hash(POLICY_ONNX_PATH)
off_policy_hash = get_file_hash(OFF_POLICY_ONNX_PATH)
on_policy_hash = get_file_hash(ON_POLICY_ONNX_PATH)
combined_hash = hashlib.sha256((vision_hash + policy_hash).encode()).hexdigest()
combined_hash = hashlib.sha256((vision_hash + off_policy_hash + on_policy_hash).encode()).hexdigest()
with open(MODEL_HASH_PATH) as f:
current_hash = f.read().strip()