From f7efd7c64182f1e01c4c043ed58cbb4fc535220b Mon Sep 17 00:00:00 2001 From: discountchubbs Date: Mon, 14 Jul 2025 16:34:36 -0700 Subject: [PATCH] seems a bit repetitive yea? --- sunnypilot/modeld_v2/parse_model_outputs_split.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/sunnypilot/modeld_v2/parse_model_outputs_split.py b/sunnypilot/modeld_v2/parse_model_outputs_split.py index fa3167af83..00895e738d 100644 --- a/sunnypilot/modeld_v2/parse_model_outputs_split.py +++ b/sunnypilot/modeld_v2/parse_model_outputs_split.py @@ -125,8 +125,6 @@ class Parser: out_shape=(SplitModelConstants.NUM_ROAD_EDGES,SplitModelConstants.IDX_N,SplitModelConstants.LANE_LINES_WIDTH)) if 'sim_pose' in outs: self.parse_mdn('sim_pose', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.POSE_WIDTH,)) - for k in ['lead_prob', 'lane_lines_prob']: - self.parse_binary_crossentropy(k, outs) def parse_vision_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]: self.parse_mdn('pose', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.POSE_WIDTH,)) @@ -136,6 +134,11 @@ class Parser: self.split_outputs(outs) self.parse_categorical_crossentropy('desire_pred', outs, out_shape=(SplitModelConstants.DESIRE_PRED_LEN,SplitModelConstants.DESIRE_PRED_WIDTH)) self.parse_binary_crossentropy('meta', outs) + if self.generation >= 13: + self.parse_binary_crossentropy('lane_lines_prob', outs) + else: + for k in ['lead_prob', 'lane_lines_prob']: + self.parse_binary_crossentropy(k, outs) return outs def parse_policy_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]: @@ -146,6 +149,8 @@ class Parser: if 'desired_curvature' in outs: self.parse_mdn('desired_curvature', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.DESIRED_CURV_WIDTH,)) self.parse_categorical_crossentropy('desire_state', outs, out_shape=(SplitModelConstants.DESIRE_PRED_WIDTH,)) + if self.generation >= 13: + self.parse_binary_crossentropy('lead_prob', outs) return outs def parse_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]: