refactored training approaches

engine/lib/behavior.py

@@ -3,11 +3,16 @@ from pathlib import Path
 
 sys.path.insert(0, str(Path(__file__).parents[2]))
 
-from sim.rl.behavior_loader.models import (
-    BehaviorModel,
-    AgentBehaviorModel,
-    aggregate_event_transitions,
-)
+try:
+    from sim.rl.behavior_loader.models import (
+        BehaviorModel,
+        AgentBehaviorModel,
+        aggregate_event_transitions,
+    )
+except ImportError:
+    BehaviorModel = None
+    AgentBehaviorModel = None
+    aggregate_event_transitions = None
 import pandas as pd
 import numpy as np
 from .demand import generate_demand_for_actor
@@ -20,6 +25,12 @@ _cache = {}  # lazy cache for models and base pivots
 
 
 def _get_base_pivot(human: bool):
+    if (
+        BehaviorModel is None
+        or AgentBehaviorModel is None
+        or aggregate_event_transitions is None
+    ):
+        raise ImportError("behavior loader dependencies are unavailable")
     key = "human" if human else "agent"
     if key not in _cache:
         model = BehaviorModel(human_dir) if human else AgentBehaviorModel(agent_dir)
@@ -34,6 +45,13 @@ def get_transition_models():
     returns:
         tuple: (human_transitions, agent_transitions) as dicts of event->event->prob
     """
+    if (
+        BehaviorModel is None
+        or AgentBehaviorModel is None
+        or aggregate_event_transitions is None
+    ):
+        raise ImportError("behavior loader dependencies are unavailable")
+
     human_model = BehaviorModel(human_dir)
     agent_model = AgentBehaviorModel(agent_dir)