making general-purpose metric function

src/main.py

@@ -4,7 +4,7 @@ import intersim
 import numpy as np
 import os
 opj = os.path.join
-from src import InteractionDatasetSingleAgent
+from src import InteractionDatasetSingleAgent, metrics
 
 def basestr(**kwargs):
     """
@@ -31,15 +31,13 @@ def main(method='bc', train=False, test=False, loc=0, **kwargs):
         os.mkdir(outdir)
     filestr = opj(outdir, basestr(**kwargs))
    
-    # define transforms
-    transforms={}
+
     
     # method-based training
     if method=='bc':
         from src import bc
         policy_class = bc.BehaviorCloningPolicy
         load_policy_fn = bc.load_policy
-        metrics_fn = bc.metrics
         train_fn = bc.train
     else:
         raise NotImplementedError
@@ -60,8 +58,8 @@ def main(method='bc', train=False, test=False, loc=0, **kwargs):
         simulate_policy(policy, loc=loc, track=track, filestr=filestr)
 
         # run test metrics
-        # test_dataset = InteractionDatasetSingleAgent(loc=loc, tracks=[4])
-        # metrics_fn(test_dataset, policy)
+        test_dataset = InteractionDatasetSingleAgent(loc=loc, tracks=[4])
+        metrics(filestr, test_dataset, policy)
 
 
 def simulate_policy(policy, loc=0, track=0, filestr=''):