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107 lines
3.4 KiB
Python
107 lines
3.4 KiB
Python
import pytest
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import numpy as np
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from gym.spaces import Box, Tuple, Discrete, MultiDiscrete
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from tests.vector.utils import CustomSpace, make_env, make_custom_space_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("FrozenLake-v1", 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("CartPole-v1", 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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@pytest.mark.parametrize("use_single_action_space", [True, False])
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def test_step_sync_vector_env(use_single_action_space):
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env_fns = [make_env("FrozenLake-v1", 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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assert isinstance(env.single_action_space, Discrete)
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assert isinstance(env.action_space, MultiDiscrete)
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if use_single_action_space:
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actions = [env.single_action_space.sample() for _ in range(8)]
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else:
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actions = env.action_space.sample()
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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, MultiDiscrete)
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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_spaces_sync_vector_env():
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# CartPole-v1 - observation_space: Box(4,), action_space: Discrete(2)
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env_fns = [make_env("CartPole-v1", i) for i in range(8)]
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# FrozenLake-v1 - Discrete(16), action_space: Discrete(4)
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env_fns[1] = make_env("FrozenLake-v1", 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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def test_custom_space_sync_vector_env():
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env_fns = [make_custom_space_env(i) for i in range(4)]
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try:
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env = SyncVectorEnv(env_fns)
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reset_observations = env.reset()
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assert isinstance(env.single_action_space, CustomSpace)
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assert isinstance(env.action_space, Tuple)
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actions = ("action-2", "action-3", "action-5", "action-7")
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step_observations, rewards, dones, _ = env.step(actions)
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finally:
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env.close()
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assert isinstance(env.single_observation_space, CustomSpace)
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assert isinstance(env.observation_space, Tuple)
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assert isinstance(reset_observations, tuple)
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assert reset_observations == ("reset", "reset", "reset", "reset")
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assert isinstance(step_observations, tuple)
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assert step_observations == (
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"step(action-2)",
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"step(action-3)",
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"step(action-5)",
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"step(action-7)",
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)
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