Add causal person track GRU residual experiment

infer_turn_head.py

@@ -149,7 +149,13 @@ def _predict_states(
                 start,
                 min(start + batch_size, len(states)),
             )
-            person_batch, person_mask = local_person_features.padded(rows)
+            if head.local_fusion == "track-gru-residual":
+                person_batch, person_mask = local_person_features.padded_history(
+                    rows,
+                    max_observations=head.person_history_frames,
+                )
+            else:
+                person_batch, person_mask = local_person_features.padded(rows)
             person_batch = person_batch.to(
                 device=device,
                 dtype=torch.float32,
@@ -440,6 +446,7 @@ def main() -> None:
             local_modalities=local_contract["modalities"] if local_contract else "av",
             local_contract=local_contract,
             local_fusion=head.local_fusion,
+            person_track_max_gap_seconds=head.person_track_max_gap_seconds,
         )
         if data.hidden_size != int(head_config["hidden_size"]):
             raise ValueError(
@@ -519,12 +526,18 @@ def main() -> None:
             "prediction_layout": "[target_time, class, future_horizon]",
             "checkpoint": str(args.checkpoint.resolve()),
             "checkpoint_epoch": checkpoint_payload.get("epoch"),
+            "checkpoint_training_epochs": checkpoint_payload.get(
+                "training_config",
+                {},
+            ).get("epochs"),
             "checkpoint_train_sessions": checkpoint_payload.get("train_sessions"),
             "checkpoint_dev_sessions": checkpoint_payload.get("dev_sessions"),
             "layer_fusion": head.layer_fusion,
             "local_fusion": head.local_fusion,
             "local_fusion_scope": LOCAL_FUSION_SCOPES[head.local_fusion],
             "person_interaction_gates": head.person_interaction_gates(),
+            "person_history_frames": head.person_history_frames,
+            "person_track_max_gap_seconds": head.person_track_max_gap_seconds,
             "local_contract": local_contract,
             "transition_auxiliary": head.transition_auxiliary,
             "transition_objective": checkpoint_payload.get(