3438ce7e09
- Added test_seeded_learning test and test_deterministic_evaluation test. - Passed config values seed and deterministic to ppo agent - Dropped deterministic override in evaluate functions - TempPrimaiteSession now writes files to a UUID folder rather than datetime - Added seed to Ray RLlib agent setup in rllib.py - Added seed to SB3 agent setup in sb3.py
58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
import pytest as pytest
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from primaite.config.lay_down_config import dos_very_basic_config_path
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from tests import TEST_CONFIG_ROOT
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@pytest.mark.parametrize(
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"temp_primaite_session",
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[[
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TEST_CONFIG_ROOT / "ppo_seeded_training_config.yaml",
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dos_very_basic_config_path()
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]],
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indirect=True,
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)
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def test_seeded_learning(temp_primaite_session):
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"""Test running seeded learning produces the same output when ran twice."""
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expected_mean_reward_per_episode = {
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1: -90.703125,
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2: -91.15234375,
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3: -87.5,
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4: -92.2265625,
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5: -94.6875,
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6: -91.19140625,
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7: -88.984375,
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8: -88.3203125,
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9: -112.79296875,
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10: -100.01953125
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}
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with temp_primaite_session as session:
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assert session._training_config.seed == 67890, \
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"Expected output is based upon a agent that was trained with " \
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"seed 67890"
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session.learn()
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actual_mean_reward_per_episode = session.learn_av_reward_per_episode()
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assert actual_mean_reward_per_episode == expected_mean_reward_per_episode
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@pytest.mark.skip(reason="Inconsistent results. Needs someone with RL "
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"knowledge to investigate further.")
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@pytest.mark.parametrize(
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"temp_primaite_session",
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[[
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TEST_CONFIG_ROOT / "ppo_seeded_training_config.yaml",
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dos_very_basic_config_path()
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]],
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indirect=True,
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)
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def test_deterministic_evaluation(temp_primaite_session):
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"""Test running deterministic evaluation gives same av eward per episode."""
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with temp_primaite_session as session:
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# do stuff
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session.learn()
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session.evaluate()
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eval_mean_reward = session.eval_av_reward_per_episode_csv()
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assert len(set(eval_mean_reward.values())) == 1
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