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* Move tests to root with automatic PyCharm import refactoring. This will likely fail some tests * Changed entry point for a registration test env. * Move a stray lunar_lander test to tests/envs/... * black * Change the version from which importlib_metadata is replaced with importlib.metadata. Also requiring installing importlib_metadata for python 3.8 now. ??????????? * Undo last commit
64 lines
1.6 KiB
Python
64 lines
1.6 KiB
Python
import pytest
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import numpy as np
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import gym
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from gym.wrappers import TransformReward
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@pytest.mark.parametrize("env_id", ["CartPole-v1", "Pendulum-v1"])
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def test_transform_reward(env_id):
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# use case #1: scale
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scales = [0.1, 200]
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for scale in scales:
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env = gym.make(env_id)
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wrapped_env = TransformReward(gym.make(env_id), lambda r: scale * r)
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action = env.action_space.sample()
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env.seed(0)
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env.reset()
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wrapped_env.seed(0)
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wrapped_env.reset()
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_, reward, _, _ = env.step(action)
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_, wrapped_reward, _, _ = wrapped_env.step(action)
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assert wrapped_reward == scale * reward
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del env, wrapped_env
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# use case #2: clip
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min_r = -0.0005
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max_r = 0.0002
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env = gym.make(env_id)
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wrapped_env = TransformReward(gym.make(env_id), lambda r: np.clip(r, min_r, max_r))
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action = env.action_space.sample()
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env.seed(0)
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env.reset()
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wrapped_env.seed(0)
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wrapped_env.reset()
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_, reward, _, _ = env.step(action)
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_, wrapped_reward, _, _ = wrapped_env.step(action)
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assert abs(wrapped_reward) < abs(reward)
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assert wrapped_reward == -0.0005 or wrapped_reward == 0.0002
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del env, wrapped_env
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# use case #3: sign
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env = gym.make(env_id)
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wrapped_env = TransformReward(gym.make(env_id), lambda r: np.sign(r))
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env.seed(0)
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env.reset()
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wrapped_env.seed(0)
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wrapped_env.reset()
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for _ in range(1000):
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action = env.action_space.sample()
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_, wrapped_reward, done, _ = wrapped_env.step(action)
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assert wrapped_reward in [-1.0, 0.0, 1.0]
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if done:
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break
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del env, wrapped_env
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