Add option for random policy

lerobot/scripts/eval.py

@@ -4,9 +4,9 @@ import hydra
 import imageio
 import numpy as np
 import torch
-from tensordict import TensorDict
 from tensordict.nn import TensorDictModule
 from termcolor import colored
+from torchrl.envs import EnvBase
 
 from lerobot.common.envs.factory import make_env
 from lerobot.common.tdmpc import TDMPC
@@ -14,7 +14,12 @@ from lerobot.common.utils import set_seed
 
 
 def eval_policy(
-    env, policy, num_episodes: int, save_video: bool = False, video_dir: Path = None
+    env: EnvBase,
+    policy: TensorDictModule = None,
+    num_episodes: int = 10,
+    max_steps: int = 30,
+    save_video: bool = False,
+    video_dir: Path = None,
 ):
     rewards = []
     successes = []
@@ -31,7 +36,7 @@ def eval_policy(
         rendering_callback(env)
 
         rollout = env.rollout(
-            max_steps=30,
+            max_steps=max_steps,
             policy=policy,
             callback=rendering_callback,
             auto_reset=False,
@@ -73,9 +78,10 @@ def eval(cfg: dict):
         out_keys=["action"],
     )
 
+    # policy can be None to rollout a random policy
     metrics = eval_policy(
         env,
-        policy,
+        policy=policy,
         num_episodes=10,
         save_video=True,
         video_dir=Path("tmp/2023_01_29_xarm_lift_final"),