adding function to load experts and combine them into single transition list

requirements.txt

@@ -4,6 +4,7 @@ sklearn
 pytest
 json5
 tqdm
-tensorboard
 ray[tune]
 hyperopt
+psutil
+fire

scratch/arec/intersimple/data/load_experts.py

@@ -0,0 +1,23 @@
+import pickle
+import imitation.data.rollout as rollout
+from tqdm import tqdm
+
+def load_experts(expert_files=[]):
+    """
+    Load expert trajectories from files and combine their transitions into a single RB
+
+    Args:
+        expert_files (list): list of expert file strings
+    Returns:
+        transitions (list): list of combined expert episode transitions 
+    """
+    transitions = []
+    for file in tqdm(expert_files):
+        with open(file, "rb") as f:
+            trajectories = pickle.load(f)
+        transitions = transitions + rollout.flatten_trajectories(trajectories)
+    return transitions
+
+if __name__=='__main__':
+    import fire
+    fire.Fire(load_experts)

scratch/etienne/intersimple/gail_options_image.py

@@ -303,6 +303,8 @@ if __name__ == '__main__':
  
     with open("data/NormalizedIntersimpleExpertMu.001_NRasterizedAgent51w36h36mppx2.pkl", "rb") as f:
         trajectories = pickle.load(f)
+    import pdb 
+    pdb.set_trace()
     transitions = rollout.flatten_trajectories(trajectories)
     generator = train(transitions)