mirror of
https://github.com/Farama-Foundation/Gymnasium.git
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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
38 lines
1.2 KiB
Python
38 lines
1.2 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 GrayScaleObservation
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from gym.wrappers import AtariPreprocessing
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pytest.importorskip("gym.envs.atari")
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pytest.importorskip("cv2")
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@pytest.mark.parametrize(
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"env_id", ["PongNoFrameskip-v0", "SpaceInvadersNoFrameskip-v0"]
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)
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@pytest.mark.parametrize("keep_dim", [True, False])
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def test_gray_scale_observation(env_id, keep_dim):
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gray_env = AtariPreprocessing(gym.make(env_id), screen_size=84, grayscale_obs=True)
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rgb_env = AtariPreprocessing(gym.make(env_id), screen_size=84, grayscale_obs=False)
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wrapped_env = GrayScaleObservation(rgb_env, keep_dim=keep_dim)
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assert rgb_env.observation_space.shape[-1] == 3
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seed = 0
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gray_obs = gray_env.reset(seed=seed)
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wrapped_obs = wrapped_env.reset(seed=seed)
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if keep_dim:
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assert wrapped_env.observation_space.shape[-1] == 1
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assert len(wrapped_obs.shape) == 3
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wrapped_obs = wrapped_obs.squeeze(-1)
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else:
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assert len(wrapped_env.observation_space.shape) == 2
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assert len(wrapped_obs.shape) == 2
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# ALE gray scale is slightly different, but no more than by one shade
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assert np.allclose(gray_obs.astype("int32"), wrapped_obs.astype("int32"), atol=1)
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