mirror of
https://github.com/Farama-Foundation/Gymnasium.git
synced 2025-08-22 07:02:19 +00:00
c364506710
* Ditch most of the seeding.py and replace np_random with the numpy default_rng. Let's see if tests pass * Updated a bunch of RNG calls from the RandomState API to Generator API * black; didn't expect that, did ya? * Undo a typo * blaaack * More typo fixes * Fixed setting/getting state in multidiscrete spaces * Fix typo, fix a test to work with the new sampling * Correctly (?) pass the randomly generated seed if np_random is called with None as seed * Convert the Discrete sample to a python int (as opposed to np.int64) * Remove some redundant imports * First version of the compatibility layer for old-style RNG. Mainly to trigger tests. * Removed redundant f-strings * Style fixes, removing unused imports * Try to make tests pass by removing atari from the dockerfile * Try to make tests pass by removing atari from the setup * Try to make tests pass by removing atari from the setup * Try to make tests pass by removing atari from the setup * First attempt at deprecating `env.seed` and supporting `env.reset(seed=seed)` instead. Tests should hopefully pass but throw up a million warnings. * black; didn't expect that, didya? * Rename the reset parameter in VecEnvs back to `seed` * Updated tests to use the new seeding method * Removed a bunch of old `seed` calls. Fixed a bug in AsyncVectorEnv * Stop Discrete envs from doing part of the setup (and using the randomness) in init (as opposed to reset) * Add explicit seed to wrappers reset * Remove an accidental return * Re-add some legacy functions with a warning. * Use deprecation instead of regular warnings for the newly deprecated methods/functions
31 lines
740 B
Python
31 lines
740 B
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 RescaleAction
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def test_rescale_action():
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env = gym.make("CartPole-v1")
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with pytest.raises(AssertionError):
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env = RescaleAction(env, -1, 1)
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del env
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env = gym.make("Pendulum-v1")
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wrapped_env = RescaleAction(gym.make("Pendulum-v1"), -1, 1)
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seed = 0
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obs = env.reset(seed=seed)
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wrapped_obs = wrapped_env.reset(seed=seed)
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assert np.allclose(obs, wrapped_obs)
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obs, reward, _, _ = env.step([1.5])
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with pytest.raises(AssertionError):
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wrapped_env.step([1.5])
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wrapped_obs, wrapped_reward, _, _ = wrapped_env.step([0.75])
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assert np.allclose(obs, wrapped_obs)
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assert np.allclose(reward, wrapped_reward)
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