Make most outputs dynamic

This commit is contained in:
discountchubbs
2025-07-15 06:30:23 -07:00
parent 079ce94cb4
commit d5b59d2b19
@@ -118,18 +118,28 @@ class Parser:
out_shape=(SplitModelConstants.IDX_N,SplitModelConstants.PLAN_WIDTH))
def split_outputs(self, outs: dict[str, np.ndarray]) -> None:
if 'desired_curvature' in outs:
self.parse_mdn('desired_curvature', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.DESIRED_CURV_WIDTH,))
if 'desire_pred' in outs:
self.parse_categorical_crossentropy('desire_pred', outs, out_shape=(SplitModelConstants.DESIRE_PRED_LEN,SplitModelConstants.DESIRE_PRED_WIDTH))
if 'desire_state' in outs:
self.parse_categorical_crossentropy('desire_state', outs, out_shape=(SplitModelConstants.DESIRE_PRED_WIDTH,))
if 'lane_lines' in outs:
self.parse_mdn('lane_lines', outs, in_N=0, out_N=0,
out_shape=(SplitModelConstants.NUM_LANE_LINES,SplitModelConstants.IDX_N,SplitModelConstants.LANE_LINES_WIDTH))
if 'lane_lines_prob' in outs:
self.parse_binary_crossentropy('lane_lines_prob', outs)
if 'lead_prob' in outs:
self.parse_binary_crossentropy('lead_prob', outs)
if 'lat_planner_solution' in outs:
self.parse_mdn('lat_planner_solution', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.IDX_N,SplitModelConstants.LAT_PLANNER_SOLUTION_WIDTH))
if 'meta' in outs:
self.parse_binary_crossentropy('meta', outs)
if 'road_edges' in outs:
self.parse_mdn('road_edges', outs, in_N=0, out_N=0,
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,))
if 'lane_lines_prob' in outs:
self.parse_binary_crossentropy('lane_lines_prob', outs)
if 'lead_prob' in outs:
self.parse_binary_crossentropy('lead_prob', 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,))
@@ -137,18 +147,11 @@ class Parser:
self.parse_mdn('road_transform', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.POSE_WIDTH,))
self.parse_dynamic_outputs(outs)
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)
return outs
def parse_policy_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
self.parse_dynamic_outputs(outs)
self.split_outputs(outs)
if 'lat_planner_solution' in outs:
self.parse_mdn('lat_planner_solution', outs, in_N=0, out_N=0, out_shape=(SplitModelConstants.IDX_N,SplitModelConstants.LAT_PLANNER_SOLUTION_WIDTH))
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,))
return outs
def parse_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]: