UnityMLAgentsEnv¶
- torchrl.envs.UnityMLAgentsEnv(*args, **kwargs)[原始碼]¶
Unity ML-Agents 環境封裝器。
GitHub: https://github.com/Unity-Technologies/ml-agents
文件: https://unity-technologies.github.io/ml-agents/Python-LLAPI/
此類別可以提供
mlagents_envs.environment.UnityEnvironment類別提供的任何可選初始化引數。有關這些引數的列表，請參閱: https://unity-technologies.github.io/ml-agents/Python-LLAPI-Documentation/#__init__如果同時提供了
file_name和registered_name，則會引發錯誤。如果既未提供
file_name也未提供 ``registered_name``，則環境設定會在本地主機埠上等待，使用者必須執行 Unity ML-Agents 環境二進位制檔案以連線到它。- 引數:
file_name (str, 可選) – 如果提供，則為 Unity 環境二進位制檔案的路徑。預設為
None。registered_name (str, 可選) – 如果提供，Unity 環境二進位制檔案將從預設的 ML-Agents 登錄檔中載入。註冊環境列表位於
available_envs中。預設為None。
- 關鍵字引數:
device (torch.device, 可選) – 如果提供，則為資料將被轉換到的裝置。預設為
None。batch_size (torch.Size, 可選) – 環境的批次大小。預設為
torch.Size([])。allow_done_after_reset (bool, 可選) – 如果為
True，則允許環境在呼叫reset()後立即處於done狀態。預設為False。group_map (MarlGroupMapType 或 Dict[str, List[str]]], 可選) – 如何在 tensordicts 中對智慧體進行分組以進行輸入/輸出。有關更多資訊，請參閱
MarlGroupMapType。如果未指定，智慧體將根據 Unity 環境提供的組 ID 進行分組。預設為None。categorical_actions (bool, 可選) – 如果為
True，分類 spec 將被轉換為 TorchRL 的等效表示 (torchrl.data.Categorical)，否則將使用獨熱編碼 (torchrl.data.OneHot)。預設為False。
- 變數:
available_envs – 可構建的註冊環境列表
示例
>>> from torchrl.envs import UnityMLAgentsEnv >>> env = UnityMLAgentsEnv(registered_name='3DBall') >>> td = env.reset() >>> td = env.step(td.update(env.full_action_spec.rand())) >>> td TensorDict( fields={ group_0: TensorDict( fields={ agent_0: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), continuous_action: Tensor(shape=torch.Size([2]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_10: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), continuous_action: Tensor(shape=torch.Size([2]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_11: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), continuous_action: Tensor(shape=torch.Size([2]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_1: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), continuous_action: Tensor(shape=torch.Size([2]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_2: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), continuous_action: Tensor(shape=torch.Size([2]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_3: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), continuous_action: Tensor(shape=torch.Size([2]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_4: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), continuous_action: Tensor(shape=torch.Size([2]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_5: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), continuous_action: Tensor(shape=torch.Size([2]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_6: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), continuous_action: Tensor(shape=torch.Size([2]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_7: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), continuous_action: Tensor(shape=torch.Size([2]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_8: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), continuous_action: Tensor(shape=torch.Size([2]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_9: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), continuous_action: Tensor(shape=torch.Size([2]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), next: TensorDict( fields={ group_0: TensorDict( fields={ agent_0: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), group_reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_10: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), group_reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_11: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), group_reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_1: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), group_reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_2: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), group_reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_3: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), group_reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_4: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), group_reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_5: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), group_reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_6: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), group_reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_7: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), group_reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_8: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), group_reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False), agent_9: TensorDict( fields={ VectorSensor_size8: Tensor(shape=torch.Size([8]), device=cpu, dtype=torch.float32, is_shared=False), done: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), group_reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), reward: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.float32, is_shared=False), terminated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False), truncated: Tensor(shape=torch.Size([1]), device=cpu, dtype=torch.bool, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False)}, batch_size=torch.Size([]), device=None, is_shared=False)
