modeld: desire->desire_pulse (#36076)

consistent naming

selfdrive/modeld/modeld.py

@@ -106,7 +106,7 @@ class ModelState:
 
     # policy inputs
     self.numpy_inputs = {
-      'desire': np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN, ModelConstants.DESIRE_LEN), dtype=np.float32),
+      'desire_pulse': np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN, ModelConstants.DESIRE_LEN), dtype=np.float32),
       'traffic_convention': np.zeros((1, ModelConstants.TRAFFIC_CONVENTION_LEN), dtype=np.float32),
       'features_buffer': np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN,  ModelConstants.FEATURE_LEN), dtype=np.float32),
     }
@@ -131,13 +131,13 @@ class ModelState:
   def run(self, bufs: dict[str, VisionBuf], transforms: dict[str, np.ndarray],
                 inputs: dict[str, np.ndarray], prepare_only: bool) -> dict[str, np.ndarray] | None:
     # Model decides when action is completed, so desire input is just a pulse triggered on rising edge
-    inputs['desire'][0] = 0
-    new_desire = np.where(inputs['desire'] - self.prev_desire > .99, inputs['desire'], 0)
-    self.prev_desire[:] = inputs['desire']
+    inputs['desire_pulse'][0] = 0
+    new_desire = np.where(inputs['desire_pulse'] - self.prev_desire > .99, inputs['desire_pulse'], 0)
+    self.prev_desire[:] = inputs['desire_pulse']
 
     self.full_desire[0,:-1] = self.full_desire[0,1:]
     self.full_desire[0,-1] = new_desire
-    self.numpy_inputs['desire'][:] = self.full_desire.reshape((1,ModelConstants.INPUT_HISTORY_BUFFER_LEN,ModelConstants.TEMPORAL_SKIP,-1)).max(axis=2)
+    self.numpy_inputs['desire_pulse'][:] = self.full_desire.reshape((1,ModelConstants.INPUT_HISTORY_BUFFER_LEN,ModelConstants.TEMPORAL_SKIP,-1)).max(axis=2)
 
     self.numpy_inputs['traffic_convention'][:] = inputs['traffic_convention']
     imgs_cl = {name: self.frames[name].prepare(bufs[name], transforms[name].flatten()) for name in self.vision_input_names}
@@ -313,7 +313,7 @@ def main(demo=False):
     bufs = {name: buf_extra if 'big' in name else buf_main for name in model.vision_input_names}
     transforms = {name: model_transform_extra if 'big' in name else model_transform_main for name in model.vision_input_names}
     inputs:dict[str, np.ndarray] = {
-      'desire': vec_desire,
+      'desire_pulse': vec_desire,
       'traffic_convention': traffic_convention,
     }