diff --git a/rllib/agents/marwil/tests/test_bc.py b/rllib/agents/marwil/tests/test_bc.py index 31a9b3818..b84ad14e9 100644 --- a/rllib/agents/marwil/tests/test_bc.py +++ b/rllib/agents/marwil/tests/test_bc.py @@ -39,20 +39,28 @@ class TestBC(unittest.TestCase): config["evaluation_config"] = {"input": "sampler"} # Learn from offline data. config["input"] = [data_file] - num_iterations = 300 + num_iterations = 350 + min_reward = 70.0 # Test for all frameworks. for _ in framework_iterator(config, frameworks=("tf", "torch")): trainer = marwil.BCTrainer(config=config, env="CartPole-v0") + learnt = False for i in range(num_iterations): eval_results = trainer.train()["evaluation"] print("iter={} R={}".format( i, eval_results["episode_reward_mean"])) - # Learn until some reward is reached on an actual live env. - if eval_results["episode_reward_mean"] > 60.0: + # Learn until good reward is reached on an actual live env. + if eval_results["episode_reward_mean"] > min_reward: print("learnt!") + learnt = True break + if not learnt: + raise ValueError( + "BCTrainer did not reach {} reward from expert offline " + "data!".format(min_reward)) + check_compute_single_action( trainer, include_prev_action_reward=True) diff --git a/rllib/agents/marwil/tests/test_marwil.py b/rllib/agents/marwil/tests/test_marwil.py index 5cb19595f..acd0fe725 100644 --- a/rllib/agents/marwil/tests/test_marwil.py +++ b/rllib/agents/marwil/tests/test_marwil.py @@ -43,20 +43,28 @@ class TestMARWIL(unittest.TestCase): config["evaluation_config"] = {"input": "sampler"} # Learn from offline data. config["input"] = [data_file] - num_iterations = 300 + num_iterations = 350 + min_reward = 70.0 # Test for all frameworks. for _ in framework_iterator(config): trainer = marwil.MARWILTrainer(config=config, env="CartPole-v0") + learnt = False for i in range(num_iterations): eval_results = trainer.train()["evaluation"] print("iter={} R={}".format( i, eval_results["episode_reward_mean"])) # Learn until some reward is reached on an actual live env. - if eval_results["episode_reward_mean"] > 60.0: + if eval_results["episode_reward_mean"] > min_reward: print("learnt!") + learnt = True break + if not learnt: + raise ValueError( + "MARWILTrainer did not reach {} reward from expert " + "offline data!".format(min_reward)) + check_compute_single_action( trainer, include_prev_action_reward=True) diff --git a/rllib/tests/data/cartpole/large.json b/rllib/tests/data/cartpole/large.json index f49ceb547..7bfab1ee1 100644 --- a/rllib/tests/data/cartpole/large.json +++ b/rllib/tests/data/cartpole/large.json @@ -1,21 +1,20 @@ -{"type": "SampleBatch", "eps_id": [199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 199910694, 1662335932, 1662335932, 1662335932, 1662335932, 1662335932, 1662335932, 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