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modeld: send_raw_pred under a flag (#30298)

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* modeld: SEND_RAW_PRED under a flag

* not twice
old-commit-hash: b7cc6983c31b158e2552192ee6f9fdf6116adc8e
This commit is contained in:
YassineYousfi
2023-10-20 13:53:22 -07:00
committed by GitHub
parent 9affc1c0c9
commit 8ea8f8710c
2 changed files with 14 additions and 1 deletions
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7
selfdrive/modeld/fill_model_msg.py
View File

@@ -1,9 +1,12 @@
import os
import capnp
import numpy as np
from typing import Dict
from cereal import log
from openpilot.selfdrive.modeld.constants import ModelConstants, Plan, Meta
SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
ConfidenceClass = log.ModelDataV2.ConfidenceClass
class PublishState:
@@ -163,6 +166,10 @@ def fill_model_msg(msg: capnp._DynamicStructBuilder, net_output_data: Dict[str,
else:
modelV2.confidence = ConfidenceClass.red
# raw prediction if enabled
if SEND_RAW_PRED:
modelV2.rawPredictions = net_output_data['raw_pred'].tobytes()
def fill_pose_msg(msg: capnp._DynamicStructBuilder, net_output_data: Dict[str, np.ndarray],
vipc_frame_id: int, vipc_dropped_frames: int, timestamp_eof: int, live_calib_seen: bool) -> None:
msg.valid = live_calib_seen & (vipc_dropped_frames < 1)

8
selfdrive/modeld/modeld.py
View File

@@ -1,5 +1,6 @@
#!/usr/bin/env python3
import sys
import os
import time
import pickle
import numpy as np
@@ -20,6 +21,8 @@ from openpilot.selfdrive.modeld.fill_model_msg import fill_model_msg, fill_pose_
from openpilot.selfdrive.modeld.constants import ModelConstants
from openpilot.selfdrive.modeld.models.commonmodel_pyx import ModelFrame, CLContext
SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
MODEL_PATHS = {
ModelRunner.THNEED: Path(__file__).parent / 'models/supercombo.thneed',
ModelRunner.ONNX: Path(__file__).parent / 'models/supercombo.onnx'}
@@ -70,7 +73,10 @@ class ModelState:
self.model.addInput(k, v)
def slice_outputs(self, model_outputs: np.ndarray) -> Dict[str, np.ndarray]:
return {k: model_outputs[np.newaxis, v] for k,v in self.output_slices.items()}
parsed_model_outputs = {k: model_outputs[np.newaxis, v] for k,v in self.output_slices.items()}
if SEND_RAW_PRED:
parsed_model_outputs['raw_pred'] = model_outputs.copy()
return parsed_model_outputs
def run(self, buf: VisionBuf, wbuf: VisionBuf, transform: np.ndarray, transform_wide: np.ndarray,
inputs: Dict[str, np.ndarray], prepare_only: bool) -> Optional[Dict[str, np.ndarray]]: