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This commit is contained in:
Jade Choghari
2025-08-10 01:32:28 -04:00
parent 4c19a71d7c
commit a25480d363
7 changed files with 35 additions and 22 deletions
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10
src/lerobot/scripts/eval.py
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@@ -143,7 +143,7 @@ def rollout(
leave=False,
)
check_env_attributes_and_types(env)
while not np.all(done):
while not np.all(done) and step < max_steps:
# Numpy array to tensor and changing dictionary keys to LeRobot policy format.
observation = preprocess_observation(observation)
if return_observations:
@@ -185,8 +185,11 @@ def rollout(
all_successes.append(torch.tensor(successes))
step += 1
print(step)
running_success_rate = (
einops.reduce(torch.stack(all_successes, dim=1), "b n -> b", "any").numpy().mean()
# einops.reduce(torch.stack(all_successes, dim=1), "b n -> b", "any").numpy().mean() #TODO: changed by jade
einops.reduce(torch.stack(all_successes, dim=1), "b n -> b", "max")
)
progbar.set_postfix({"running_success_rate": f"{running_success_rate.item() * 100:.1f}%"})
progbar.update()
@@ -315,7 +318,8 @@ def eval_policy(
sum_rewards.extend(batch_sum_rewards.tolist())
batch_max_rewards = einops.reduce((rollout_data["reward"] * mask), "b n -> b", "max")
max_rewards.extend(batch_max_rewards.tolist())
batch_successes = einops.reduce((rollout_data["success"] * mask), "b n -> b", "any")
# batch_successes = einops.reduce((rollout_data["success"] * mask), "b n -> b", "any")
batch_successes = einops.reduce((rollout_data["success"] * mask).float(), "b n -> b", "max")
all_successes.extend(batch_successes.tolist())
if seeds:
all_seeds.extend(seeds)