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[RLlib] Fix test_bc.py test case. (#11722)
* Fix large json test file. * Fix large json test file. * WIP.
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Sven Mika authored and GitHub committed
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@@ -39,20 +39,28 @@ class TestBC(unittest.TestCase):
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config["evaluation_config"] = {"input": "sampler"}
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# Learn from offline data.
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config["input"] = [data_file]
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num_iterations = 300
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num_iterations = 350
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min_reward = 70.0
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# Test for all frameworks.
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for _ in framework_iterator(config, frameworks=("tf", "torch")):
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trainer = marwil.BCTrainer(config=config, env="CartPole-v0")
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learnt = False
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for i in range(num_iterations):
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eval_results = trainer.train()["evaluation"]
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print("iter={} R={}".format(
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i, eval_results["episode_reward_mean"]))
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# Learn until some reward is reached on an actual live env.
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if eval_results["episode_reward_mean"] > 60.0:
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# Learn until good reward is reached on an actual live env.
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if eval_results["episode_reward_mean"] > min_reward:
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print("learnt!")
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learnt = True
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break
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if not learnt:
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raise ValueError(
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"BCTrainer did not reach {} reward from expert offline "
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"data!".format(min_reward))
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check_compute_single_action(
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trainer, include_prev_action_reward=True)
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@@ -43,20 +43,28 @@ class TestMARWIL(unittest.TestCase):
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config["evaluation_config"] = {"input": "sampler"}
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# Learn from offline data.
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config["input"] = [data_file]
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num_iterations = 300
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num_iterations = 350
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min_reward = 70.0
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# Test for all frameworks.
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for _ in framework_iterator(config):
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trainer = marwil.MARWILTrainer(config=config, env="CartPole-v0")
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learnt = False
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for i in range(num_iterations):
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eval_results = trainer.train()["evaluation"]
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print("iter={} R={}".format(
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i, eval_results["episode_reward_mean"]))
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# Learn until some reward is reached on an actual live env.
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if eval_results["episode_reward_mean"] > 60.0:
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if eval_results["episode_reward_mean"] > min_reward:
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print("learnt!")
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learnt = True
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break
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if not learnt:
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raise ValueError(
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"MARWILTrainer did not reach {} reward from expert "
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"offline data!".format(min_reward))
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check_compute_single_action(
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trainer, include_prev_action_reward=True)
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@@ -1,21 +1,20 @@
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[0.002636209363117814, -0.5560387372970581, 0.0007858205353841186, 0.9154497981071472], [-0.008484565652906895, -0.7511712908744812, 0.019094815477728844, 1.2083796262741089], [-0.023507991805672646, -0.9465346336364746, 0.043262407183647156, 1.5069847106933594], [-0.04243868589401245, -0.7519631385803223, 0.07340209931135178, 1.2281156778335571], [-0.05747794732451439, -0.5578585863113403, 0.09796441346406937, 0.9593037366867065], [-0.06863512098789215, -0.36418038606643677, 0.11715049296617508, 0.6989348530769348], [-0.07591872662305832, -0.5607149600982666, 0.131129190325737, 1.026079535484314], [-0.087133027613163, -0.7573157548904419, 0.1516507863998413, 1.3568905591964722], [-0.10227934271097183, -0.9539796113967896, 0.17878858745098114, 1.692915439605713], [-0.04606005176901817, -0.0012466305634006858, 0.0029205239843577147, -0.017267948016524315], [-0.04608498141169548, -0.19641034305095673, 0.002575164893642068, 0.2763350009918213], [-0.050013188272714615, -0.0013252266217023134, 0.008101864717900Line truncated
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{"type": "SampleBatch", "eps_id": [589830065, 589830065, 589830065, 589830065, 589830065, 589830065, 589830065, 589830065, 589830065, 589830065, 691935141, 691935141, 691935141, 691935141, 691935141, 691935141, 691935141, 691935141, 691935141, 691935141, 691935141, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 8696792, 1908216693, 1908216693, 1908216693, 1908216693, 1908216693, 1908216693, 1908216693, 1908216693, 1908216693, 1908216693, 1908216693, 1908216693, 1908216693, 1908216693, 1908216693, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 853010846, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 236504457, 1092921004, 1092921004, 1092921004, 1092921004, 1092921004, 1092921004, 1092921004, 1092921004, 1092921004, 1092921004, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 364237636, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 1771447307, 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0.040872037410736084], [0.03826127Line truncated
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[-0.08876916021108627, -0.16118653118610382, Line truncated
|
||||
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[0.0351799875497818, 0.210302531719207Line truncated
|
||||
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0.3487701117992401, 0.06628210842609406, -Line truncated
|
||||
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-0.03920303285121918, -0.0025Line truncated
|
||||
Reference in new issue
Block a user