Add diffusion policy (train and eval works, TODO: reproduce results)

lerobot/scripts/train.py

@@ -122,11 +122,6 @@ def train(cfg: dict, out_dir=None, job_name=None):
     start_time = time.time()
     step = 0  # number of policy update
 
-    print("First eval_policy_and_log with a random model or pretrained")
-    eval_policy_and_log(
-        env, td_policy, step, online_episode_idx, start_time, cfg, L, is_offline=True
-    )
-
     for offline_step in range(cfg.offline_steps):
         if offline_step == 0:
             print("Start offline training on a fixed dataset")