mirror of
https://github.com/Farama-Foundation/Gymnasium.git
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69 lines
2.1 KiB
Python
69 lines
2.1 KiB
Python
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import pytest
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import numpy as np
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from gym.spaces import Box
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from gym.vector.tests.utils import make_env
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from gym.vector.sync_vector_env import SyncVectorEnv
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def test_create_sync_vector_env():
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env_fns = [make_env('CubeCrash-v0', i) for i in range(8)]
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try:
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env = SyncVectorEnv(env_fns)
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finally:
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env.close()
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assert env.num_envs == 8
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def test_reset_sync_vector_env():
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env_fns = [make_env('CubeCrash-v0', i) for i in range(8)]
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try:
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env = SyncVectorEnv(env_fns)
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observations = env.reset()
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finally:
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env.close()
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assert isinstance(env.observation_space, Box)
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assert isinstance(observations, np.ndarray)
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assert observations.dtype == env.observation_space.dtype
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assert observations.shape == (8,) + env.single_observation_space.shape
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assert observations.shape == env.observation_space.shape
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def test_step_sync_vector_env():
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env_fns = [make_env('CubeCrash-v0', i) for i in range(8)]
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try:
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env = SyncVectorEnv(env_fns)
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observations = env.reset()
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actions = [env.single_action_space.sample() for _ in range(8)]
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observations, rewards, dones, _ = env.step(actions)
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finally:
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env.close()
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assert isinstance(env.observation_space, Box)
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assert isinstance(observations, np.ndarray)
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assert observations.dtype == env.observation_space.dtype
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assert observations.shape == (8,) + env.single_observation_space.shape
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assert observations.shape == env.observation_space.shape
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assert isinstance(rewards, np.ndarray)
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assert isinstance(rewards[0], (float, np.floating))
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assert rewards.ndim == 1
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assert rewards.size == 8
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assert isinstance(dones, np.ndarray)
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assert dones.dtype == np.bool_
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assert dones.ndim == 1
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assert dones.size == 8
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def test_check_observations_sync_vector_env():
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# CubeCrash-v0 - observation_space: Box(40, 32, 3)
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env_fns = [make_env('CubeCrash-v0', i) for i in range(8)]
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# MemorizeDigits-v0 - observation_space: Box(24, 32, 3)
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env_fns[1] = make_env('MemorizeDigits-v0', 1)
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with pytest.raises(RuntimeError):
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env = SyncVectorEnv(env_fns)
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env.close()
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