Commit 35e0e64e authored by Eric Hambro's avatar Eric Hambro
Browse files

Add ascension counter

parent 88c416dc
......@@ -35,6 +35,7 @@ def run_batched_rollout(num_episodes, batched_env, agent):
episode_count = 0
pbar = tqdm(total=num_episodes)
ascension_count = 0
all_returns = []
returns = [0.0 for _ in range(num_envs)]
# The evaluator will automatically stop after the episodes based on the development/test phase
......@@ -55,11 +56,12 @@ def run_batched_rollout(num_episodes, batched_env, agent):
active_envs[done_idx] = (num_remaining > 0)
num_remaining -= 1
ascension_count += int(infos[done_idx]["is_ascended"])
pbar.update(1)
returns[done_idx] = 0.0
pbar.close()
return all_returns
return ascension_count, all_returns
if __name__ == "__main__":
# AIcrowd will cut the assessment early duing the dev phase
......
......@@ -37,4 +37,4 @@ class TestEvaluationConfig:
# Change this to locally check a different number of rollouts
# The AIcrowd submission evaluator will not use this
# It is only for your local evaluation
NUM_EPISODES = 64
NUM_EPISODES = 512
......@@ -25,8 +25,12 @@ def evaluate():
agent = Agent(num_envs, batched_env.num_actions)
scores = run_batched_rollout(num_episodes, batched_env, agent)
print(f"Median Score: {np.median(scores)}, Mean Score: {np.mean(scores)}")
ascensions, scores = run_batched_rollout(num_episodes, batched_env, agent)
print(
f"Ascensions: {ascensions} "
f"Median Score: {np.median(scores)}, "
f"Mean Score: {np.mean(scores)}"
)
if __name__ == "__main__":
......
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