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# graders.py
def get_info_efficiency(env):
if hasattr(env, "episode_stats") and env.episode_stats:
return env.episode_stats[-1].get("info_efficiency", 0)
return 0
def grade_easy(env, success=None, steps=None, rewards=None):
score = 0.3 + 0.1 * (len(rewards) if rewards else 0)
#print(f"\nrewards: {rewards}")
#print(f"\nlen rewards: {len(rewards)}")
#print(f"\nscore: {score}")
return max(0.01, min(0.99, score))
def grade_medium(env, success=None, steps=None, rewards=None):
info_eff = get_info_efficiency(env)
score = 0.5 * info_eff
#print(f"\ninfo_eff: {info_eff}")
#print(f"\nscore: {score}")
return max(0.01, min(0.99, score))
def grade_hard(env, success=None, steps=None, rewards=None):
info_eff = get_info_efficiency(env)
score = (
0.5 * (1 if success else 0) +
0.3 * info_eff +
0.2 * (1 / (1 + (steps or 1)))
)
#print(f"\nsteps: {steps}")
#print(f"\ninfo_eff: {info_eff}")
#print(f"\nlen trajectory: {len(trajectory or [])}")
#print(f"\nscore: {score}")
return max(0.01, min(0.99, score))
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