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88 lines
2.2 KiB
Markdown
88 lines
2.2 KiB
Markdown
---
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title: Vector
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---
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# Vector
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```{eval-rst}
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.. autofunction:: gymnasium.vector.make
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```
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## VectorEnv
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```{eval-rst}
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.. attribute:: gymnasium.vector.VectorEnv.action_space
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The (batched) action space. The input actions of `step` must be valid elements of `action_space`.::
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>>> envs = gymnasium.vector.make("CartPole-v1", num_envs=3)
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>>> envs.action_space
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MultiDiscrete([2 2 2])
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.. attribute:: gymnasium.vector.VectorEnv.observation_space
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The (batched) observation space. The observations returned by `reset` and `step` are valid elements of `observation_space`.::
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>>> envs = gymnasium.vector.make("CartPole-v1", num_envs=3)
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>>> envs.observation_space
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Box([[-4.8 ...]], [[4.8 ...]], (3, 4), float32)
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.. attribute:: gymnasium.vector.VectorEnv.single_action_space
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The action space of an environment copy.::
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>>> envs = gymnasium.vector.make("CartPole-v1", num_envs=3)
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>>> envs.single_action_space
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Discrete(2)
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.. attribute:: gymnasium.vector.VectorEnv.single_observation_space
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The observation space of an environment copy.::
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>>> envs = gymnasium.vector.make("CartPole-v1", num_envs=3)
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>>> envs.single_action_space
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Box([-4.8 ...], [4.8 ...], (4,), float32)
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```
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### Reset
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```{eval-rst}
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.. automethod:: gymnasium.vector.VectorEnv.reset
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```
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```python
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>>> envs = gymnasium.vector.make("CartPole-v1", num_envs=3)
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>>> envs.reset()
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(array([[-0.02240574, -0.03439831, -0.03904812, 0.02810693],
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[ 0.01586068, 0.01929009, 0.02394426, 0.04016077],
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[-0.01314174, 0.03893502, -0.02400815, 0.0038326 ]],
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dtype=float32), {})
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```
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### Step
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```{eval-rst}
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.. automethod:: gymnasium.vector.VectorEnv.step
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```
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```python
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>>> envs = gymnasium.vector.make("CartPole-v1", num_envs=3)
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>>> envs.reset()
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>>> actions = np.array([1, 0, 1])
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>>> observations, rewards, dones, infos = envs.step(actions)
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>>> observations
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array([[ 0.00122802, 0.16228443, 0.02521779, -0.23700266],
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[ 0.00788269, -0.17490888, 0.03393489, 0.31735462],
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[ 0.04918966, 0.19421194, 0.02938497, -0.29495203]],
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dtype=float32)
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>>> rewards
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array([1., 1., 1.])
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>>> dones
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array([False, False, False])
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>>> infos
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{}
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```
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