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import argparse |
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import numpy as np |
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from mlagents_envs.environment import UnityEnvironment |
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EPSILON = 0.001 |
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def test_run_environment(env_name): |
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""" |
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Run the low-level API test of compressed sensors using the specified environment |
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:param env_name: Name of the Unity environment binary to launch |
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""" |
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env = UnityEnvironment( |
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file_name=env_name, no_graphics=True, additional_args=["-logFile", "-"] |
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) |
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try: |
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# Reset the environment |
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env.reset() |
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env.step() |
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# Set the default brain to work with |
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group_name = list(env.behavior_specs.keys())[0] |
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# Get the state of the agents |
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decision_steps, _ = env.get_steps(group_name) |
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# One observation comes from compressed sensor while the other comes |
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# from an uncompressed sensor |
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obs_1 = decision_steps.obs[0][0, :, :, :] |
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obs_2 = decision_steps.obs[0][1, :, :, :] |
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diff = np.abs(obs_1 - obs_2) |
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# make sure both are identical |
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assert np.max(diff) < EPSILON |
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# make sure an actual observation was collected |
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assert np.max(obs_1) > EPSILON |
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print("Observations were identical") |
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finally: |
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env.close() |
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if __name__ == "__main__": |
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parser = argparse.ArgumentParser() |
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parser.add_argument("--env", default="artifacts/testPlayer") |
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args = parser.parse_args() |
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test_run_environment(args.env) |
Chris Elion